Optical measuring method and optical measuring device

Abstract

Provided are an optical measuring method and an optical measuring device for accurately measuring the particle size and particle size distribution of particles contained in a dispersion liquid containing particles having the property of absorbing light. The optical measuring method for a dispersion liquid containing particles includes: a measurement step for measuring, a plurality of times, scattered light obtained by causing incident light to be incident on the dispersion liquid, while changing the intensity of the incident light; a conversion step for converting a signal of the scattered light measured a plurality of times in the measurement step into a plurality of items of time-varying characteristic data of a scattered electric field or a scattering intensity; and a particle size calculation step for obtaining the particle size of the particles using the plurality of items of time-varying characteristic data of the scattered electric field or the scattering intensity obtained by the conversion step.

Description

Light measurement method and light measurement device

[0001] The present invention relates to an optical measurement method and an optical measurement device for a dispersion liquid containing particles, and more particularly to an optical measurement method and an optical measurement device for measuring the particle size or particle size distribution of particles that have the property of absorbing light.

[0002] In a wide range of fields, including industry, the environment, medicine, and academia, accurate size quantification of nanoparticles of approximately 1 to 100 nm in liquid is important and necessary. Representative techniques for quantifying nanoparticles include dynamic light scattering, low-coherence dynamic light scattering, particle tracking analyzers that measure particle displacement under a microscope, and multimodal light scattering measurement methods that combine Mie scattering angle profiles and dynamic light scattering information. These techniques are used to measure the diffusion coefficient of particles, which is then converted into particle size. More specific particle measurement methods are currently being proposed.

[0003] For example, Patent Document 1 describes a measurement device for performing dynamic light scattering measurement of particles in a sample medium, the measurement device including a light splitting unit that splits light from a low-coherence light source, an irradiation unit that irradiates the sample medium with one of the light beams split by the light splitting unit, a phase modulation unit that phase-modulates the other of the light beams split by the light splitting unit, a spectrum acquisition unit that resolves the phase-modulated light and scattered light from the sample medium by wavelength and acquires a spectrum of interference light between the phase-modulated light and the scattered light, and a measurement unit that performs dynamic light scattering measurement of particles based on the acquired spectrum, wherein the measurement unit calculates an intensity signal for each scattering point position in the sample medium based on the acquired spectrum, calculates a power spectrum for each scattering point position based on a time change in the intensity signal for each scattering point position, and calculates a diffusion coefficient of the particle for each scattering point position based on the calculated power spectrum. Patent Document 1 also describes that the particle size distribution in the sample medium (particle size for each scattering point position) can be simultaneously measured by calculating the particle size from the diffusion coefficient using the Stokes-Einstein formula.

[0004] International Publication No. 2013 / 077137

[0005] Patent Document 1 describes determining particle size and particle size distribution from the diffusion coefficient using the Stokes-Einstein formula (see Equation (1) below). However, Patent Document 1 does not take into account particle absorption of light from a low-coherence light source. When particles absorb light, their temperature may increase. The Stokes-Einstein formula includes a temperature term, and accurate particle size cannot be obtained when the temperature changes, such as when the particle temperature increases. For this reason, Patent Document 1 is unable to accurately determine the particle size and particle size distribution of black particles such as carbon black and particles that absorb light, such as pigment particles. To avoid the influence of particle light absorption, it is possible to use a light source with a wavelength that is not absorbed by the particles, but in this case, preparing the light source is costly. Furthermore, because black particles and the like absorb light over a wide wavelength range, it is difficult to eliminate the influence of light absorption. As such, it is currently difficult to accurately quantify the particle size and particle size distribution of particles that absorb light.

[0006] An object of the present invention is to provide a light measurement method and a light measurement device that can accurately measure the particle size and particle size distribution of particles contained in a dispersion liquid containing particles that have the property of absorbing light.

[0007] In order to achieve the above-mentioned object, invention [1] is an optical measurement method for a dispersion liquid containing particles, which comprises a measurement step of measuring scattered light obtained by irradiating incident light into the dispersion liquid with varying intensities multiple times, a conversion step of converting the scattered light signals measured multiple times in the measurement step into multiple time-varying characteristic data of scattered electric fields or scattering intensities, and a particle size calculation step of determining particle size using the multiple time-varying characteristic data of scattered electric fields or scattering intensities obtained in the conversion step.

[0008] Invention [2] is the optical measurement method according to Invention [1], in which the particle size calculation step determines the particle size by analyzing a plurality of pieces of time-varying characteristic data of the scattered electric field or the scattered intensity, assuming that the dependence of the particle diffusion coefficient on the intensity of the incident light is linear, and determining the particle size by determining the relationship between the particle size or the particle diffusion coefficient and the intensity of the incident light. Invention [3] is the optical measurement method according to Invention [2], further comprising the steps of: obtaining a second temperature after the temperature of the particles at the first temperature has risen due to optical absorption of the incident light; and determining the particle size at the second temperature using an equation expressing the diffusion coefficient when a temperature rise occurs, relative to the particle size of the particles determined in the particle size calculation step.

[0009] Invention [4] is an optical measurement method for a dispersion liquid containing particles, the optical measurement method comprising: a measurement step of measuring scattered light obtained by irradiating incident light into the dispersion liquid at different intensities, a conversion step of obtaining a plurality of pieces of time-varying characteristic data of scattered electric fields or scattering intensities from the plurality of scattered light pieces obtained by the measurement step; and a particle size distribution calculation step of determining the particle size distribution of the particles using the plurality of time-varying characteristic data of scattered electric fields or scattering intensities obtained by the conversion step.

[0010] Invention [5] is the optical measurement method according to Invention [4], wherein the particle size distribution calculation step further comprises a step of determining an index value representing the temperature dependence of particle size using a plurality of pieces of time-varying characteristic data of the scattered electric field or the scattered intensity, and a step of correcting the particle size distribution of the particles determined in the particle size distribution calculation step using the index value representing the temperature dependence of particle size. Invention [6] is the optical measurement method according to Invention [4], further comprising a step of obtaining a second temperature after the particles at a first temperature have risen in temperature due to light absorption of incident light, and wherein the particle size distribution calculation step determines the particle size distribution of the particles using the second temperature and a diffusion coefficient obtained from the plurality of pieces of time-varying characteristic data of the scattered electric field or the scattered intensity.

[0011] Invention [7] is the light measurement method according to any one of Inventions [1] to [6], in which the scattered light is obtained by changing the value of at least one of the scattering angle and the measurement wavelength among the measurement parameters.

[0012] Invention [8] is the optical measurement method according to any one of Inventions [1] to [7], in which the measurement step is a step of measuring the scattering intensity of scattered light obtained by irradiating incident light at different intensities into the dispersion liquid multiple times to obtain multiple scattering intensity data, and the conversion step is a step of acquiring multiple pieces of scattered electric field or scattering intensity time variation characteristic data from the multiple scattering intensity data obtained in the measurement step. Invention [9] is the optical measurement method according to Invention [7], in which the dispersion liquid contains multiple types of particle species, and the method includes a conversion step of converting the multiple scattered light signals obtained in the measurement step into multiple pieces of time-averaged scattered electric field data or time-averaged scattered intensity data, and a calculation step of calculating the particle size or particle size distribution for each of the multiple types of particle species from the time-averaged scattered electric field data or time-averaged scattered intensity data and the time variation characteristic data. Invention

[10] is the optical measurement method according to Invention [9], in which the measurement step is a step of measuring the scattering intensity of scattered light obtained by irradiating incident light into the dispersion liquid with varying intensities multiple times to obtain multiple scattering intensity data, and a step of measuring the scattering intensity of scattered light obtained by irradiating the dispersion liquid with varying values ​​of at least one of the scattering angle and the measurement wavelength multiple times to obtain multiple scattering intensity data, and the conversion step is a step of calculating multiple time-varying characteristic data of the scattered electric field or scattering intensity from the multiple scattering intensity data obtained in the measurement step. Invention

[11] is the optical measurement method according to any one of Inventions [1] to

[10] , in which the time-varying characteristic data of the scattered electric field or scattering intensity is an autocorrelation function or a power spectrum.

[0013] Invention

[12] is an optical measurement device for a dispersion liquid containing particles, the optical measurement device having a light source that causes incident light to be incident on the dispersion liquid at varying intensities, a measurement unit that multiple times measures scattered light obtained by causing incident light to be incident on the dispersion liquid at varying intensities, a conversion unit that obtains multiple pieces of time-varying characteristic data of scattered electric fields or scattering intensities from the multiple pieces of scattered light obtained by the measurement unit, and a particle size calculation unit that calculates particle size using the multiple pieces of time-varying characteristic data of scattered electric fields or scattering intensities obtained by the conversion unit. Invention

[13] is the optical measurement device according to Invention

[12] , in which the particle size calculation unit analyzes the multiple pieces of time-varying characteristic data of scattered electric fields or scattering intensities, assuming that the dependency of the particle diffusion coefficient on the intensity of the incident light is linear, to determine the relationship between the particle size or the particle diffusion coefficient and the intensity of the incident light, thereby determining the particle size. Invention

[14] is an optical measurement device according to invention

[12] or

[13] , wherein the particle size calculation unit obtains a second temperature after a particle at a first temperature has risen in temperature due to light absorption of incident light, and calculates the particle size of the particle at the second temperature using an equation that represents the diffusion coefficient when a temperature rise occurs for the particle size of the particle calculated by the particle size calculation unit.

[0014] Invention

[15] is an optical measurement device for a dispersion liquid containing particles, the optical measurement device having a light source that causes incident light to be incident on the dispersion liquid at varying intensities, a measurement unit that multiple times measures scattered light obtained by causing incident light to be incident on the dispersion liquid at varying intensities, a conversion unit that obtains multiple pieces of time-varying characteristic data of scattered electric fields or scattering intensities from the multiple pieces of scattered light obtained by the measurement unit, and a particle size distribution calculation unit that calculates a particle size distribution of the particles using the multiple pieces of time-varying characteristic data of scattered electric fields or scattering intensities obtained by the conversion unit. Invention

[16] is the optical measurement device according to Invention

[15] , in which the particle size distribution calculation unit uses the multiple pieces of time-varying characteristic data of scattered electric fields or scattering intensities obtained by the conversion unit to obtain an index value that represents the temperature dependence of particle size, and corrects the particle size distribution of the particles using the index value that represents the temperature dependence of particle size. Invention

[17] is the optical measurement device according to Invention

[15] , wherein the particle size distribution calculation unit obtains a second temperature after particles at a first temperature have risen in temperature due to light absorption of incident light, and calculates the particle size distribution of the particles by using the second temperature as a diffusion coefficient obtained from a plurality of pieces of time-varying characteristic data of scattered electric fields or scattered intensities.

[0015] Invention

[18] is the light measurement device according to any one of inventions

[12] to

[17] , wherein the scattered light is obtained by changing the value of at least one of the scattering angle and the measurement wavelength among the measurement parameters.

[0016] Invention

[19] is the light measurement device according to any one of Inventions

[12] to

[118] , which has a measurement unit that measures the intensity of incident light. Invention

[20] is the light measurement device according to any one of Inventions

[12] to

[19] , which has a low-coherence interferometer. Invention

[21] is the light measurement device according to any one of Inventions

[12] to

[20] , in which the measurement unit measures the scattering intensity of scattered light obtained by irradiating incident light at different intensities into the dispersion liquid multiple times to obtain multiple scattering intensity data, and the conversion unit obtains multiple pieces of time-varying characteristic data of the scattered electric field or scattering intensity from the multiple scattering intensity data obtained by the measurement unit.

[0017] Invention

[22] is the optical measurement device according to any one of Inventions

[12] to

[24] , wherein the dispersion contains a plurality of types of particle species, the conversion unit converts a plurality of scattered light signals obtained by the measurement unit into a plurality of time-averaged scattered electric field data or time-averaged scattered intensity data, and the particle size calculation unit calculates the particle size of each of the plurality of types of particle species from the time-averaged scattered electric field data or time-averaged scattered intensity data and the time-varying characteristic data. Invention

[23] is the optical measurement device according to any one of Inventions

[12] to

[24] , wherein the dispersion contains a plurality of types of particle species, the conversion unit converts a plurality of scattered light signals obtained by the measurement unit into a plurality of time-averaged scattered electric field data or time-averaged scattered intensity data, and the particle size distribution calculation unit calculates the particle size distribution of each of the plurality of types of particle species from the time-averaged scattered electric field data or time-averaged scattered intensity data and the time-varying characteristic data.

[0018] Invention

[24] is the light measurement device according to Invention

[22] or

[23] , wherein the measurement unit measures the scattering intensity of scattered light obtained by irradiating incident light into the dispersion liquid with varying intensities a plurality of times to obtain a plurality of scattering intensity data, and measures the scattering intensity of scattered light obtained by irradiating the dispersion liquid with varying values ​​of at least one of the scattering angle and the measurement wavelength a plurality of times to obtain a plurality of scattering intensity data, and the conversion unit calculates a plurality of time-varying characteristic data of the scattered electric field or scattering intensity from the plurality of scattering intensity data obtained by the measurement unit. Invention

[25] is the light measurement device according to any one of Inventions

[12] to

[24] , wherein the time-varying characteristic data of the scattered electric field or scattering intensity is an autocorrelation function or a power spectrum.

[0019] According to the present invention, it is possible to provide a light measurement method and a light measurement device for accurately measuring the particle size and particle size distribution of particles contained in a dispersion liquid containing particles that have the property of absorbing light.

[0020] 1 is a graph showing the dependency of the autocorrelation function on the intensity of incident light. FIG. 1 is a graph showing the relationship between the diffusion coefficient of a particle and the intensity of incident light. FIG. 2 is a graph showing the relationship between the reciprocal of the particle diameters of multiple types of particles and the intensity of incident light. FIG. 3 is a graph showing the relationship between the diffusion coefficient of a particle and the intensity of incident light for each wavelength of incident light. FIG. 4 is a graph showing an example of the power spectrum of a particle for each intensity of incident light. FIG. 5 is a graph showing the relationship between the reciprocal of the particle diameter and the intensity of incident light. FIG. 6 is a schematic diagram showing a first example of an optical measurement device according to an embodiment of the present invention. FIG. 7 is a schematic diagram showing a second example of an optical measurement device according to an embodiment of the present invention. FIG. 8 is a schematic diagram showing a third example of an optical measurement device according to an embodiment of the present invention. FIG. 9 is a flowchart showing a fourth example of an optical measurement method according to an embodiment of the present invention. FIG. 10 is a histogram of particle A. FIG. 11 is a histogram of particle B. FIG. 12 is a flowchart showing a fifth example of an optical measurement method according to an embodiment of the present invention. FIG. 13 is a graph showing calculated values ​​of scattering angle and scattering intensity for each refractive index of particles having the same particle size. FIG. 14 is a graph showing an example of the relationship between scattering intensity and measurement wavelength. FIG. 15 is a graph showing another example of the relationship between scattering intensity and measurement wavelength. FIG. 16 is a flowchart showing a sixth example of an optical measurement method according to an embodiment of the present invention.

[0021] The light measurement method and light measurement device of the present invention will be described in detail below based on preferred embodiments shown in the accompanying drawings. Note that the drawings described below are merely illustrative for explaining the present invention, and the present invention is not limited to the drawings shown below. Note that in the following, the "to" symbol indicating a numerical range includes the numerical values ​​written on both sides. For example, when ε is a numerical value ε α ~Number ε β That is, the range of ε is the number ε α and the number ε β The range includes ε α ≦ε≦ε β Unless otherwise specified, "angles expressed by specific numerical values" and "parallel" include a generally acceptable error range in the relevant technical field. Similarly, unless otherwise specified, temperatures also include a generally acceptable error range in the relevant technical field.

[0022] (Measurement principle of optical measurement) First, the measurement principle of particle diameter will be described. A method is known in which the diffusion coefficient of a particle is measured and converted to a particle diameter from the diffusion coefficient. From the Stokes-Einstein formula shown in the following formula (1), the particle diameter d ０ In the following formula (1), k Ｂ is the Boltzmann constant, T ０ is the temperature of the solvent, η ０ is the viscosity of the solvent. In the following formula (1), light absorption by particles is not taken into consideration. Note that the solvent is the solvent in the dispersion liquid containing the particles. Here, particle light absorption means that light incident on the particle is taken inside the particle. When particles absorb light, the temperature of the particle may increase. Therefore, particles that have the property of absorbing light may experience an increase in particle temperature when they absorb light. Note that light absorption is used to mean the same as absorbing light as described above.

[0023]

[0024] Here, when considering the light absorption of particles, particles with light-absorbing properties exhibit an autocorrelation function obtained for each intensity of incident light by dynamic light scattering measurement, which changes depending on the intensity of the incident light, as shown in Figure 1. Figure 1 shows the dependency of the autocorrelation function on the intensity of incident light in an aqueous dispersion of a yellow pigment. That is, it shows the dependency of the autocorrelation function of the particles on the intensity of incident light. In Figure 1, two yellow pigments with different particle sizes are used, and the yellow pigment is PY74 (C.I. Pigment Yellow 74). The solvent for the aqueous dispersion of the yellow pigment is water. The measurement wavelength is 488 nm. Note that ND shown below represents the amount of incident light transmitted through the filter, with ND50 representing a transmitted light amount of 50% and ND100 representing a transmitted light amount of 100%.

[0025] Reference numeral 10a in FIG. 1 indicates the autocorrelation function measured for an aqueous dispersion of a yellow pigment under conditions of an incident light intensity of 20 mW and ND50. That is, the actual intensity of light incident on the yellow pigment dispersed in the liquid is 10 mW. Reference numeral 10b indicates the autocorrelation function measured for an aqueous dispersion of a yellow pigment under conditions of an incident light intensity of 40 mW and ND50. That is, the actual intensity of light incident on the yellow pigment dispersed in the liquid is 20 mW. Reference numeral 10c indicates the autocorrelation function measured for an aqueous dispersion of a yellow pigment under conditions of an incident light intensity of 60 mW and ND50. That is, the actual intensity of light incident on the yellow pigment dispersed in the liquid is 30 mW. Reference numeral 10d indicates the autocorrelation function measured for an aqueous dispersion of a yellow pigment under conditions of an incident light intensity of 80 mW and ND50. That is, the actual intensity of light incident on the yellow pigment dispersed in the liquid is 40 mW. Reference numeral 10e denotes the autocorrelation function measured for an aqueous dispersion of a yellow pigment under conditions of an incident light intensity of 100 mW and ND50. In other words, the actual intensity of light incident on the yellow pigment dispersed in the liquid is 50 mW. Reference numeral 10f denotes the autocorrelation function measured for an aqueous dispersion of a yellow pigment under conditions of an incident light intensity of 80 mW and ND100. In other words, the actual intensity of light incident on the yellow pigment dispersed in the liquid is 80 mW. Reference numeral 10g denotes the autocorrelation function measured for an aqueous dispersion of a yellow pigment under conditions of an incident light intensity of 100 mW and ND100. In other words, the actual intensity of light incident on the yellow pigment dispersed in the liquid is 100 mW.

[0026] The autocorrelation function of the scattering intensity is expressed by the following formula (2). In the following formula (2), q represents the scattering vector. τ represents the time lag of the autocorrelation function. The diffusion coefficient D and the scattering vector q have the relationship shown in the following formula (2). G ２ (τ)-1=exp(-2Dq ２ τ) (2)

[0027] The scattering vector q is a constant determined by the wavelength of the light source and the scattering angle. For this reason, the exponential function exp(-2Dq ２ τ) to obtain the diffusion coefficient D, and the particle size d０ For example, if the particle has a particle size, then equation (2) can be expressed as G ２ (τ)-1=A ０ ・exp(-2Dq ２ In this case, the exponential function exp(-2Dq ２ τ) to obtain the diffusion coefficient D, and the particle size d ０ It should be noted that the above-mentioned A ０ is a component corresponding to the ratio of the histogram described later. As a result, the particle size can be determined using time-varying characteristic data of a plurality of scattered electric fields or scattered intensities, for example, an autocorrelation function or a power spectrum, as described later. In addition, the exponential function exp(-2Dq ２ By fitting the exponential function exp(-2Dq ２ The method of fitting τ) is not particularly limited, and any known method can be used as appropriate.

[0028] Here, when the relationship between the diffusion coefficient of a particle obtained by analyzing the autocorrelation function and the intensity of incident light was investigated, it was found to be linear, as shown in FIG. 2 , for example, as indicated by line 12. That is, the dependency of the diffusion coefficient of the particle on the intensity of incident light is linear. In this case, the particle size obtained by extrapolating the diffusion coefficient of the incident light intensity to 0 (zero) on the above-mentioned line 12 is a particle size independent of the intensity of incident light. By utilizing this linear dependency of the diffusion coefficient of the particle on the intensity of incident light, even for particles that have the property of absorbing light, a particle size independent of the intensity of incident light can be obtained. This allows the particle size of particles contained in a dispersion containing particles that have the property of absorbing light to be measured with high accuracy. Note that the extrapolation method for extrapolating the intensity of incident light to 0 is not limited to linear. Even if the extrapolation is nonlinear, it is possible to perform the extrapolation by fitting with an arbitrary function.

[0029] The relationship between the particle diffusion coefficient obtained by analyzing the autocorrelation function and the intensity of incident light is not limited to that shown in FIG. 2 , but also applies to particles of other colors. While the diffusion coefficient was used in the above analysis example, even if the reciprocal of the particle diameter is used instead of the diffusion coefficient, the same relationship between the reciprocal of the particle diameter and the intensity of incident light applies. Specifically, for example, the relationship between the reciprocal of the particle diameter and the intensity of incident light applies, as shown by lines 13 and 14 in FIG. 3 . While the vertical axis in FIG. 2 represents the diffusion coefficient, the vertical axis in FIG. 3 represents the reciprocal of the particle diameter. On the other hand, for particles with low light absorption, such as particles transparent to light of the wavelength of the incident light, the dependency on the intensity of incident light is extremely small, as shown by line 15 in FIG. 3 . Therefore, the difference between the particle diameter obtained by extrapolating the intensity of incident light to 0 (zero) and the particle diameter obtained when the intensity of incident light is greater than 0 is extremely small. Therefore, for particles with low light absorption, it is not necessary to obtain the particle diameter by extrapolating the intensity of incident light to 0 (zero).

[0030] Here, when the complex refractive index of the material that makes up a particle is expressed as N≡n+ik, the particle is said to be transparent when k=0. In other words, a transparent particle is a particle where k=0 in N≡n+ik. In the formula N≡n+ik that represents the complex refractive index, i represents an imaginary number. The real part n of the complex refractive index is called the refractive index. The imaginary part k of the complex refractive index is called the extinction coefficient, which represents absorption. Furthermore, although it depends on the intensity of the irradiated light, even if k=0 is not strictly true, particles can be treated as being almost transparent when k≒0.

[0031] Line 13 shows the results for a dispersion of a red pigment using PR254 (C.I. Pigment Red 254) as the red pigment. Line 14 shows the results for a dispersion of a red pigment using PR272 (C.I. Pigment Red 272) as the red pigment. Lines 13 and 14 are measured at a wavelength of 488 nm. Line 15 shows the results for a dispersion using polystyrene particles with a particle size of 100 nm. The polystyrene particles have low light absorption, and Nanobead NIST Traceable Particle Size Standard, 100 nm, was used. The solvent for the above dispersion is water. Line 15 is measured at a wavelength of 488 nm.

[0032] Even when measurements are taken on a dispersion containing the same particles with different wavelengths of incident light, the particle size can be obtained from the diffusion coefficient, which is the value extrapolated to an incident light intensity of 0 (zero), regardless of the wavelength of the incident light, as shown in Figure 4. Note that Figure 4 is a graph showing the relationship between the particle diffusion coefficient and the incident light intensity for each wavelength of incident light. In Figure 4, line 16 shows the results when the incident light wavelength is 488 nm. Line 17 shows the results when the incident light wavelength is 633 nm. The results are for a yellow pigment dispersion using the yellow pigment PY74 (C.I. Pigment Yellow 74) as the particles. The solvent for the above-mentioned yellow pigment dispersion is water.

[0033] The above explanation is an example of an analysis using an autocorrelation function for a particle dispersion system with a low concentration, for example, 0.1 to 0.001 volume %. While the above analysis example uses a diffusion coefficient, instead of the diffusion coefficient, the reciprocal of the particle diameter can be used as shown in Figure 3. By extrapolating the reciprocal of the particle diameter to an incident light intensity of 0 (zero), it is possible to determine the particle diameter independent of the incident light intensity. The above explanation uses an autocorrelation function. However, even in the case of a particle dispersion system with a high concentration, for example, 1 to 20 volume %, using a power spectrum, it is possible to extrapolate the incident light intensity to 0 (zero) and determine the particle diameter independent of the incident light intensity, similar to the above autocorrelation function. As shown in Figure 5, the power spectrum differs depending on the incident light intensity. The power spectrum also depends on the incident light intensity. Note that Figure 5 shows the results of measuring a dispersion of a blue pigment. The blue pigment is PB15:6 (C.I. Pigment Blue 15:6).

[0034] The autocorrelation function can be obtained by inverse Fourier transforming the power spectrum. As described above, the diffusion coefficient can be obtained from the autocorrelation function, and the particle size can be obtained from the diffusion coefficient. For example, as shown in FIG. 6, there is a linear relationship between the inverse of the particle size obtained by analyzing the power spectrum and the intensity of incident light. The particle diffusion coefficient obtained by analyzing the power spectrum and the intensity of incident light are represented by the line 18 shown in FIG. 6. Note that in FIG. 6, the vertical axis is the inverse of the particle size. However, as described above, even if the vertical axis is the diffusion coefficient, there is a linear relationship between the diffusion coefficient and the intensity of incident light. Therefore, even when using the power spectrum, similar to the results of analysis using low-coherence dynamic light scattering (LC-DLS), particle size independent of the intensity of incident light can be obtained, even for particles that have the property of absorbing light, by using a diffusion coefficient extrapolated to 0 (zero) for the intensity of incident light. For example, a particle dispersion with a high concentration of 1 to 20% by volume can be measured using low-coherence dynamic light scattering (LC-DLS). In low-coherence dynamic light scattering, the diffusion coefficient can be obtained by fitting a theoretical equation to the power spectrum. Furthermore, the power spectrum can be subjected to an inverse Fourier transform to obtain an autocorrelation function, and then a theoretical formula can be fitted to obtain the diffusion coefficient.

[0035] Next, we will explain the case where a particle absorbs light and the temperature rises. When light absorption causes a local temperature rise near the particle and the system reaches equilibrium, the diffusion coefficient D' is expressed by the following formula (3). T' in the following formula (3) is the temperature of the solvent after light absorption, and η' in the following formula (3) is the viscosity of the solvent at temperature T'. In this case, it is assumed that the temperature rise is localized only near the particle, and the temperature cannot be detected by the thermometer attached to the device. In this case, the thermometer attached to the device measures temperature T ０ If the particle size measured using dynamic light scattering (DLS) is the apparent particle size d', the relationship between the particle size d' and the above-mentioned diffusion coefficient D' is expressed by the following formula (4). Therefore, the following formula (5) can be obtained from formulas (2) and (3).

[0036]

[0037]

[0038]

[0039] Here, if the temperature rise in the vicinity of the particle due to light absorption is ΔT, the temperature rise is expressed by the following formula (6): T′=T ０ +ΔT (6) If the following equation (7) is established between the intensity I of the incident light and the temperature rise ΔT of the particle due to light absorption, then substituting equations (5) and (6) into equation (4) yields the following equation (8): ΔT = α·I (7)

[0040]

[0041] The relationship between the viscosity of a solvent and the temperature of the solvent is expressed by the Andrade equation as follows: In the equation (9), B is a proportionality constant, E is flow activation energy, and R is a gas constant.

[0042]

[0043] Here, the following formula (10) is defined for 1 / η'. Then, when the following formula (10) is expanded by Taylor with respect to temperature, the following formula (11) is obtained. Then, when the following formula (10) is substituted into formula (7), the following formula (12) is obtained.

[0044]

[0045]

[0046]

[0047] Here, in equation (12), ΔT<T ０ In this case, the reciprocal of the particle size is linear with respect to the intensity I of the incident light. In this case, the following equation (13) is obtained. In the following equation (13), if only the linear terms are considered, the following equation is obtained, which further becomes the following equation (14).

[0048]

[0049]

[0050]

[0051] The term proportional to the intensity I of the incident light in equation (12) is defined as β, and β is defined as in equation (15) below. In this case, 1 / d' can be expressed by equation (16) below. Using equation (16) below, d ０ When solving for, the following equation (17) is obtained.

[0052]

[0053]

[0054] Furthermore, multiplying equation (16) by kBT / (3πη) gives the following equation (16-1). In equation (16-1), D' and D ０ is the diffusion coefficient. D' = D ０ +βD ０ ・I (16-1)

[0055] d ０ = (1 + β) I d' (17) From equation (16-1), the slope of the line 12 showing the intensity dependency of the incident light shown in FIG. 2 is βD ０ and the intercept of the line 12 is the diffusion coefficient D ０ From this, it can be seen that the slope of βD ０ and the intercept, i.e., the diffusion coefficient D ０ The above-mentioned β can be obtained from the equation (16-1) using the incident light intensity I and the diffusion coefficient D' at the incident light intensity I. ０ can be obtained, and the particle size d ０ The above-mentioned β is an index value representing the temperature dependency of particle diameter. The particle diameter d' when the intensity of incident light is I can also be obtained from equation (4) using the diffusion coefficient D'. When the vertical axis of the above-mentioned FIG. 2 is the reciprocal of the particle diameter, for example, in FIG. 3, from equation (16), the slope of the line 12 representing the dependency on the intensity of incident light is β / d ０ and the intercept of the line 12 is the particle size d ０ From this, it can be seen that the slope β / d ０ and the intercept, i.e., the particle size d ０ The particle diameter d' at the intensity of incident light I can be calculated from equation (16). ０The above-mentioned β is an index value representing the temperature dependence of particle diameter. The particle diameter d' when the intensity of incident light is I can also be obtained from equation (4) using the diffusion coefficient D'.

[0056] Furthermore, from equation (14) and FIG. 2, the particle diameter d' and particle diameter d ０ is known, the constant E / R related to the viscosity of the solvent and the temperature T ０ Since is known, the temperature rise ΔT at each intensity of incident light can be obtained. This allows the proportional coefficient α of the incident light intensity I and the temperature rise ΔT in equation (7) to be determined, and the true temperature during measurement T' = T ０ In this case, by measuring the particle size at an arbitrary incident light intensity, the particle size d ０ It is assumed that the temperature dependence of the viscosity of the solvent is known. From the above, it is possible to accurately measure the particle size of particles contained in a dispersion containing particles that have the property of absorbing light.

[0057] The above is an explanation for monodisperse particles. The above method can also be applied to particles having a particle size distribution P(d). The procedure is explained below. When there is a particle size distribution P(d), formula (2) is expressed by the following formula (18). The left side of formula (18) below is the sum of particle sizes d between 0 and ∞. A(d) is the frequency distribution of the component of particle size d, and ΣA(d) represents the particle size distribution of the particles. Furthermore, D(d) is the diffusion coefficient of particle size d. The relationship between the diffusion coefficient D(d) and particle size d is expressed by formula (1).

[0058]

[0059] In addition, when particles have a particle size distribution, as described above, the exponential function exp(-2Dq ２By fitting τ), the particle size distribution A(d) can be obtained. The average value of the particle size distribution A(d) is, for example, the average value based on the scattering intensity, and is therefore the average particle size of the particles. Therefore, assuming that the dependency of the particle diffusion coefficient on the intensity of incident light is linear, the average value of this particle size distribution A(d) is plotted against the intensity I of the incident light as shown in FIG. 2. This yields a straight line that shows the dependency of the average particle size on the intensity of incident light. The slope of this straight line that shows the dependency on the intensity of incident light is β / d ０ When the intensity of the incident light is 0 (zero), the particle size is d ０ d ０ corresponds to the intercept of the line. ０ and the intercept d ０ Then, for the obtained particle size distribution A(d), the particle size distribution A(d) is calculated by the following equation (17): ０ ), the particle size distribution A(d ０ ) can be obtained. This allows the particle size distribution of particles contained in a dispersion containing particles with light-absorbing properties to be measured with high accuracy. When fitting Equation (18) to the autocorrelation function graph in FIG. 1 as described above, any of the autocorrelation function graphs in FIG. 1 may be used. d ０ Using the formula (17) expressed as = (1 + β) I d', the particle size distribution A(d) is calculated as follows: ０ ), the intensity of the incident light in the graph of the autocorrelation function used for fitting (see FIG. 1) is set as I in equation (17).

[0060] Furthermore, as described above, from equation (14) and FIG. 2, the particle diameters d′ and d ０ If the equation (18) is known, it can be applied to particles having a particle size distribution P(d). In this case, for example, as described above, equation (18) is fitted to the graph of the autocorrelation function in FIG. 1. Then, when calculating the particle size from the diffusion coefficient D, the particle size distribution A(d) that takes into account the influence of incident light can be calculated by using the temperature T' and the viscosity η' of the solvent at temperature T' as shown in equation (3). ０) can be obtained. This also means that the particle size distribution of particles contained in a dispersion containing particles with light-absorbing properties can be measured with high accuracy. Note that Andrade's formula is only one example in deriving the above formula, and the present invention is not solely dependent on Andrade's formula. If the temperature dependence of the viscosity of the solvent or dispersion system is known, the particle size can be obtained in the same way as when Andrade's formula is used.

[0061] (First Example of Optical Measurement Device) Next, a light measurement device used in the light measurement method will be described. FIG. 7 is a schematic diagram showing a first example of a light measurement device according to an embodiment of the present invention. The light measurement device 20 shown in FIG. 7 is a light measurement device that utilizes low-coherence dynamic light scattering (LC-DLS). The light measurement device 20 uses a Mach-Zehnder interferometer. The light measurement device 20 includes a light source 22, a first coupler 24, a circulator 26, a collimating lens 28, an objective lens 30, a sample cell 32 that accommodates a particle-containing dispersion liquid Lq, a second coupler 34, a detector 36, and a processing unit 38. The light measurement device 20 also includes a first collimating lens 40, a modulator 42, and a second collimating lens 43. The first collimating lens 40, the modulator 42, and the second collimating lens 43 form a phase modulation unit 44.

[0062] The light source 22 has a function of changing the intensity of incident light (not shown) and making it incident on the dispersion liquid Lq in the sample cell 32. The light source 22 emits, for example, low-coherence light. Unlike monochromatic laser light, low-coherence light is light with a wide bandwidth. For example, a xenon lamp, a superluminescence diode (SLD), an LED (light emitting diode), or a supercontinuum (SC) light source is used as the light source 22. The first coupler 24 branches the light emitted from the light source 22 and has multiple input / output ports. For example, the first coupler 24 has a two-input and two-output configuration, where light is input to an end face 24a and output from an end face 24b. It is preferable that the light branching ratio of the first coupler 24 be changeable depending on the measurement target.

[0063] The light source 22 and an end face 24a of the first coupler 24 are connected by an optical fiber 23a. An optical fiber 23b is connected to the end face 24a of the first coupler 24, but the optical fiber 23b is not connected to anything other than the first coupler 24. The light emitted from the light source 22 is branched by the first coupler 24 into optical fibers 23c and 23d connected to the end face 24b and then output. The first coupler 24 branches the light emitted from the light source 22 at an intensity ratio of, for example, 99:1 and outputs the branched light to the optical fibers 23c and 23d. The branching ratio of the light emitted from the light source 22 is, in terms of intensity, such that, for example, 99% of the light is output to the optical fiber 23c and 1% of the light is output to the optical fiber 23d. The light from the optical fiber 23c becomes incident light on the dispersion liquid Lq, and the light from the optical fiber 23d becomes reference light.

[0064] The first coupler 24 is connected to a circulator 26 via an optical fiber 23c. The circulator 26 is also connected to the optical fiber 23c and the optical fiber 23f. The circulator 26 is an optical path changer that guides light from the optical fiber 23c to the optical fiber 23e and guides incident light from the optical fiber 23e to the optical fiber 23f. For example, a known circulator used in a dynamic light scattering measurement device can be used as the circulator 26. The optical fiber 23e is connected to a collimating lens 28. An objective lens 30 is disposed on the exit side of the collimating lens 28. A sample cell 32 is disposed on the opposite side of the objective lens 30 from the collimating lens 28.

[0065] The collimating lens 28 converts the light from the optical fiber 23e into parallel light. The objective lens 30 focuses the incident light that has passed through the collimating lens 28 via the optical fiber 23e and irradiates it onto the dispersion liquid Lq. That is, the objective lens 30 irradiates the incident light from the light source 22 onto the dispersion liquid Lq. The light emitted from the light source 22 passes through the optical fiber 23a, the first coupler 24, the optical fiber 23c, the circulator 26, the optical fiber 23e, the collimating lens 28, and the objective lens 30, and is incident on the dispersion liquid Lq as incident light. At this time, scattered light is generated in the dispersion liquid Lq. The scattered light generated in the dispersion liquid Lq passes through the objective lens 30, the collimating lens 28, the optical fiber 23e, and the circulator 26 in this order, and is guided to the optical fiber 23f. The optical fiber 23f is connected to the second coupler 34. The objective lens 30 focuses the incident light onto the dispersion liquid Lq and also collects scattered light generated in the dispersion liquid Lq by the incident light. The magnification of the objective lens 30 is not particularly limited, and for example, a 10x objective lens is used. Note that the objective lens 30 is not necessarily required, and the light measurement device 20 may be configured without the objective lens 30. Furthermore, it is preferable to provide the optical fiber 23f with a wavelength filter for cutting out fluorescence generated in the dispersion liquid Lq (sample).

[0066] The second coupler 34 couples the input light and has multiple input / output ports. For example, the second coupler 34 has two inputs and two outputs, with light input to an end face 34a and output from an end face 34b. Optical fibers 23f and 23g are connected to the end face 34a. Optical fibers 23h and 23i are connected to the end face 34b. The optical fibers 23h and 23i are connected to a detector 36.

[0067] The optical fiber 23d connected to the first coupler 24 is connected to a first collimating lens 40. The first collimating lens 40, the modulator 42, and the second collimating lens 43 are arranged in this order. The second collimating lens 43 is connected to the second coupler 34 by an optical fiber 23g. The first collimating lens 40 and the second collimating lens 43 collimate the incident light. The modulator 42 applies phase modulation, and an electro-optic modulator (EOM) is used, for example. The light collimated by the first collimating lens 40 is incident on the modulator 42, where it is phase-modulated. The light is then collimated by the second collimating lens 43 and output to the optical fiber 23g. The reference light is obtained by the first collimating lens 40, the modulator 42, and the second collimating lens 43, i.e., by the phase modulation unit 44.

[0068] The scattered light is input to the second coupler 34 via the optical fiber 23f. The reference light is input to the second coupler 34 via the optical fiber 23g. The second coupler 34 causes interference between the reference light and the scattered light. The second coupler 34 splits the interference light obtained by the interference, for example, at an intensity ratio of 1:1, and outputs two beams of light to the detector 36. The second coupler 34 preferably has a beam splitting ratio that can be changed depending on the object to be measured. The detector 36 is connected to a processing unit 38. The difference light between the two beams of light described below obtained by the detector 36 is output to the processing unit 38. For example, a balanced detector is used as the detector 36. The first coupler 24, the circulator 26, the collimating lens 28, the objective lens 30, the second coupler 34, the detector 36, and the optical fibers 23a to 23i constitute the measurement unit 37. The configuration of the optical fibers 23a to 23i is not particularly limited as long as it is capable of transmitting light, and known optical fibers can be used as appropriate.

[0069] The detector 36 takes the difference between the two beams of light output from the second coupler 34. This removes common-mode noise and obtains a scattered light signal containing interference components. The detector 36 converts the scattered light signal, which is the difference between the two beams of light, into an electrical signal, and outputs the scattered light signal, which is the difference between the two beams of light converted into an electrical signal, to the processing unit 38. In this way, the detector 36, i.e., the measurement unit 37, obtains the scattered light signal and scattering intensity data. The scattering intensity data is data that represents the scattering intensity of the scattered light. The light measurement device 20 measures the scattered light obtained by irradiating incident light into the dispersion liquid Lq with varying intensities multiple times, and the measurement unit 37 obtains scattering intensity data for each measurement. This allows the measurement unit 37 to obtain multiple scattering intensity data.

[0070] The processing unit 38 performs data processing and analysis. The processing unit 38 converts the plurality of scattering intensity data into a plurality of time-varying characteristic data of the scattered electric field or scattering intensity. Then, the processing unit 38 determines particle diameters using the obtained plurality of time-varying characteristic data of the scattered electric field or scattering intensity. The processing unit 38 also determines the particle size distribution using the obtained plurality of time-varying characteristic data of the scattered electric field or scattering intensity.

[0071] The processing unit 38 has a conversion unit 38a that converts the multiple scattering intensity data output from the detector 36 as described above into multiple time-varying characteristic data of the scattered electric field or scattering intensity. In this way, signals of scattered light measured multiple times are obtained, and the multiple scattering intensity data are converted to obtain multiple time-varying characteristic data of the scattered electric field or scattering intensity. Specifically, the conversion unit 38a of the processing unit 38 converts the scattering intensity data into multiple time-varying characteristic data of the scattered electric field or scattering intensity. The time-varying characteristic data of the scattered electric field or scattering intensity is, for example, an autocorrelation function or a power spectrum. The autocorrelation function is calculated from the scattering intensity data of the scattering intensity of the dispersion using a known method. The power spectrum is also calculated from the scattering intensity data of the scattering intensity of the dispersion using a known method.

[0072] The particle size calculation unit 38b calculates particle size using the time-varying characteristic data of the scattered electric field or scattered intensity obtained by the conversion unit 38a. The particle size calculation unit 38b obtains an autocorrelation function for each intensity of incident light as shown in FIG. 1 and calculates the exponential function exp(-2Dq ２ τ) is fitted to determine the particle size. The above-described fitting is used to determine the diffusion coefficient D, and the particle size is obtained from the diffusion coefficient D. The particle size calculation unit 38b can also determine the particle size by assuming that the dependency of the particle diffusion coefficient on the intensity of incident light is linear, as shown in FIG. 2 above. In this case, the particle size calculation unit 38b analyzes multiple autocorrelation functions to obtain multiple diffusion coefficients for the particles. Then, as shown in FIG. 2 above, the relationship between the particle diffusion coefficient and the intensity of incident light is determined. Next, the diffusion coefficient is extrapolated to a value where the intensity of incident light is 0 (zero), and the particle size is obtained. In this way, a particle size independent of the intensity of incident light is obtained. This makes it possible to accurately measure the particle size of particles contained in a dispersion containing particles that have the property of absorbing light.

[0073] Furthermore, the particle size calculation unit 38b can obtain a second temperature after the particles at the first temperature have risen in temperature due to light absorption of the incident light, and calculate the particle size of the particles at the second temperature by using an equation that represents the diffusion coefficient when a temperature rise occurs with respect to the particle size calculated by the particle size calculation unit 38b. Here, the first temperature is the temperature before the temperature rise due to light absorption. For example, if the particles are dispersed in a dispersion liquid Lq, it is the temperature of the dispersion liquid Lq before light absorption. Specifically, the second temperature after the temperature rise due to light absorption of the incident light is obtained using a thermometer or the like. In this case, as described above, the particle size d' and particle size d at an arbitrary incident light intensity I are calculated. ０ is known, the constant E / R related to the viscosity of the solvent and the temperature T ０ Since is known, the temperature rise ΔT at each intensity of incident light can be obtained. This allows us to calculate the proportionality coefficient α between the intensity I of incident light and the temperature rise ΔT in equation (7), and the true temperature during measurement T' = T ０ +ΔT is obtained. Temperature T ０is the first temperature, and temperature T' is the second temperature. The equation representing the diffusion coefficient when a temperature rise occurs is Equation (3). In this case, by measuring the particle size at an arbitrary incident light intensity, the particle size at the second temperature, for example, the particle size at temperature T', can be obtained from Equation (3).

[0074] The particle size distribution calculation unit 38c calculates the particle size distribution of particles using the time-varying characteristic data of the scattered electric field or scattered intensity obtained by the conversion unit 38a. The above-mentioned equation (18) is an autocorrelation function and an exponential function exp(-2Dq ２ The particle size distribution calculation unit 38c calculates the autocorrelation function using the exponential function exp(-2Dq ２ By fitting τ), the particle size distribution A(d) of the particles can be obtained. ０ ) can be obtained. Fitting and particle size distribution A(d ０ ) is determined as described above. From the above, in a dispersion containing particles having the property of absorbing light, the particle size distribution of the particles contained therein can be measured with high accuracy.

[0075] The particle size distribution calculation unit 38c may calculate an index value representing the temperature dependence of particle size using the time variation characteristic data of the plurality of scattered electric fields or scattered intensities obtained by the conversion unit 38a, and may correct the particle size distribution of the particles using the index value representing the temperature dependence of particle size. The index value representing the temperature dependence of particle size is β defined by equation (15). The particle size distribution calculation unit 38c obtains the particle size distribution A(d) by fitting equation (18) to the graph of the autocorrelation function in FIG. 1 as described above. Then, for the obtained particle size distribution A(d), d is calculated in the same manner as equation (17). ０ = (1 + β) I d. The intensity of the incident light in the graph of the autocorrelation function used for fitting (see Figure 1) is calculated as d ０ = (1 + β) I d where I is the particle size distribution A(d) obtained. ０ ) is corrected to obtain the particle size distribution A(d ０) can be obtained. The graph of the autocorrelation function in FIG. 1 can be obtained by calculating the autocorrelation function for each intensity of incident light for particles having a particle size distribution.

[0076] Furthermore, the particle size distribution calculation unit 38c can also obtain a second temperature after particles at a first temperature have risen in temperature due to light absorption of incident light, and calculate the particle size distribution of the particles by using the second temperature as a diffusion coefficient obtained from multiple time-varying characteristic data of scattered electric fields or scattered intensities. In this case, the particle size distribution is obtained by fitting Equation (18) to the graph of the autocorrelation function in FIG. 1 as described above. In this case, when calculating the particle size from the diffusion coefficient D, the temperature T', i.e., the second temperature, and the viscosity η' of the solvent at temperature T' are used as shown in Equation (3). This allows the particle size distribution A(d) taking into account the influence of incident light to be calculated. ０ ) is obtained.

[0077] The processing unit 38 executes a program (computer software) stored in a ROM (Read Only Memory) or the like, thereby determining the particle size distribution of the particles as described above. The processing unit 38 may be configured as a computer in which each component functions by executing the program as described above, or may be a dedicated device in which each component is configured with a dedicated circuit, or may be configured as a server to be executed on the cloud. The above-mentioned computer, dedicated device, and server each have, for example, a processor. The processor may be configured as one or more pieces of hardware, and the type of hardware is not limited. For example, the processor may be configured with hardware such as a programmable logic device such as a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or an FPGA (Field Programmable Gate Array), a dedicated circuit for executing specific processing such as an ASIC (Application Specific Integrated Circuit), a GPU (Graphic Processing Unit), or an NPU (Neural Processing Unit). The processor also has various units or means for executing various processes in this embodiment. The type of hardware may also be a combination of different types of hardware. When multiple pieces of hardware are configured to execute one or more processes of a certain processor, the multiple pieces of hardware may be located in devices physically separated from each other, or may be located in the same device. Furthermore, in any embodiment, the order of each process performed by the processor is not limited to the order described above and may be changed as appropriate. The hardware is configured by an electric circuit (circuitry) or the like that combines circuit elements such as semiconductor elements.

[0078] The sample cell 32 is, for example, a rectangular or cylindrical container made of optical glass or optical plastic. The sample cell 32 contains a particle-containing dispersion liquid Lq, which is the measurement target. Incident light is irradiated onto the dispersion liquid Lq. The sample cell 32 may be placed inside an immersion bath (not shown). The immersion bath is used to eliminate refractive index differences with the surrounding environment and to homogenize the temperature. Any known immersion bath can be used as the immersion bath. The temperature of the sample cell 32 can also be adjusted by bringing the sample cell 32 into contact with metal that is in contact with a Peltier element.

[0079] As described above, the light measurement device 20 measures scattered light generated when incident light from the light source 22 is scattered by the dispersion liquid Lq a plurality of times while changing the intensity of the incident light. The incident light intensity is the measurement parameter.

[0080] (Second Example of Optical Measurement Device) The optical measurement device 20 is not limited to the configuration shown in FIG. 7 , and may be an optical measurement device 20a shown in FIG. 8 . FIG. 8 is a schematic diagram showing a second example of an optical measurement device according to an embodiment of the present invention. In FIG. 8 , components identical to those in the optical measurement device 20 shown in FIG. 7 are designated by the same reference numerals, and detailed descriptions thereof will be omitted. The optical measurement device 20a shown in FIG. 8 differs from the optical measurement device 20 shown in FIG. 7 in that it includes a measurement unit 46 that measures the intensity of incident light. In the optical measurement device 20a, the first coupler 24, the circulator 26, the collimator lens 28, the objective lens 30, the second coupler 34, the third coupler 45, the measurement unit 46, the detector 36, and the optical fibers 23a to 23m form a measurement section 37.

[0081] By providing the measurement unit 46, the light measurement device 20a can more accurately measure the intensity of the incident light entering the sample cell 32. Therefore, when using the dependency of the diffusion coefficient of a particle on the intensity of incident light or the dependency of the reciprocal of the particle diameter on the intensity of incident light, as shown in FIG. 2 , more accurate measurements of particle diameter and particle diameter distribution are possible. Specifically, in the light measurement device 20a, as shown in FIG. 8 , a third coupler 45 is provided to the optical fiber 23e connected to the circulator 26. The third coupler 45 has a configuration similar to the first coupler 24, with two inputs and two outputs, where light is input to the end face 45a and output from the end face 45b. The optical fibers 23e and 23j are connected to the end face 45a. The optical fibers 23k and 23m are connected to the end face 45b. The optical fiber 23k is connected to the collimating lens 28. The optical fiber 23m is connected to the measurement unit 46.

[0082] The third coupler 45 branches the light from the optical fiber 23e into the optical fiber 23k and the optical fiber 23m. The optical fiber 23k is connected to the collimator lens 28, and the light incident on the optical fiber 23k is used to measure particles. For this reason, it is preferable that the branching ratio of the third coupler 45 is greater for the optical fiber 23k than for the optical fiber 23m. Furthermore, the light incident on the optical fiber 23m is used to measure the intensity of the incident light. Therefore, the proportion of light incident on the optical fiber 23 is not particularly limited as long as the intensity can be measured by the measurement unit 46. Furthermore, the position of the measurement unit 46 is not particularly limited as long as the intensity of light from the light source 22 can be measured.

[0083] The measurement unit 46 is connected to the processing unit 38. The intensity of the incident light measured by the measurement unit 46 is output to the processing unit 38. The configuration of the measurement unit 46 is not particularly limited as long as it can measure the intensity of the incident light. For example, a photomultiplier tube, a photodiode, an avalanche photodiode, a time correlator, or the like can be used for the measurement unit 46. Although an optical fiber 23j is connected to the end face 45a of the third coupler 45, the optical fiber 23j is connected only to the third coupler 45. The configuration of the optical fibers 23a to 23m is not particularly limited as long as they are capable of transmitting light, and known optical fibers can be used as appropriate. Furthermore, while the above-described optical measurement devices 20 and 20a are both optical measurement devices utilizing low-coherence dynamic light scattering (LC-DLS), the present invention is not limited thereto. As long as the intensity of the light source 22 can be changed, an optical measurement device utilizing dynamic light scattering (DLS) can also be used.

[0084] (First Example of Optical Measurement Method) Optical measurement is performed based on the measurement principle described above. For example, the optical measurement device 20 shown in FIG. 7 and the optical measurement device 20a shown in FIG. 8 are used for the optical measurement. The first example of the optical measurement method is an optical measurement method for a dispersion liquid containing particles. In the first example of the optical measurement method, first, incident light is irradiated into the dispersion liquid Lq with varying intensities, and the scattering intensity of the resulting scattered light is measured multiple times to obtain multiple scattering intensity data (measurement step). In this case, the dispersion liquid Lq containing particles is measured using, for example, a supercontinuum light source as the light source 22 shown in FIG. 7. The light emitted from the light source 22 is branched by a first coupler 24 at an intensity ratio of, for example, 99:1, and 99% of the branched light is output to an optical fiber 23c, passes through a circulator 26, an optical fiber 23e, and a collimating lens 28, and is then focused by an objective lens 30, causing the incident light to enter the dispersion liquid Lq. The scattered light, which is the incident light scattered by the particles, is collected by the objective lens 30, passes through the collimator lens 28 and the optical fiber 23e, and is output to the optical fiber 23f by the circulator 26, and the scattered light is input to the second coupler 34.

[0085] Meanwhile, the 1% of the light split by the first coupler 24 is used as reference light. The split 1% of the light is output to the optical fiber 23d, passes through the first collimating lens 40, the modulator 42, and the second collimating lens 43, where it is phase-modulated. The split 1% of the light passes through the optical fiber 23g and is input to the second coupler 34 as reference light. The reference light and the scattered light interfere with each other in the second coupler 34 to obtain interference light. The interference light is then split into two beams, each with an intensity ratio of, for example, 1:1, and output to the detector 36. The detector 36 calculates the difference between the two beams output from the second coupler 34. This removes common-mode noise, and a scattered light signal containing interference components is obtained. The scattered light signal representing the difference between the two beams is converted into an electrical signal to obtain scattering intensity data. The detector 36 outputs the scattering intensity data to the processing unit 38. The above-mentioned process is carried out multiple times by changing the intensity of the incident light, and for each measurement, a scattered light signal is obtained by the detector 36, i.e., the measurement unit 37, and further scattered intensity data is obtained, thereby obtaining multiple scattered intensity data.

[0086] Next, the plurality of scattering intensity data obtained from the scattered light signal obtained in the measurement step by the measurement unit 37 is converted into a plurality of time-varying characteristic data of the scattered electric field or scattering intensity as described above (conversion step). The plurality of time-varying characteristic data of the scattered electric field or scattering intensity is, for example, a plurality of autocorrelation functions or a plurality of power spectra. Specifically, the conversion unit 38a uses a known method to convert the plurality of scattering intensity data into a plurality of time-varying characteristic data of the scattered electric field or scattering intensity, for example, a plurality of autocorrelation functions or a plurality of power spectra.

[0087] The particle size is calculated using the time-varying characteristic data of the scattered electric field or scattered intensity obtained in the conversion step (particle size calculation step). Specifically, the particle size calculation unit 38b uses the autocorrelation function or power spectrum obtained in the conversion unit 38a of the processing unit 38. For example, the autocorrelation function shown in FIG. 1 is used. The above-mentioned formula (2) is a function of the autocorrelation function and the exponential function exp(-2Dq ２ The particle size calculation unit 38b calculates the autocorrelation function using the exponential function exp(-2Dq ２The diffusion coefficient D is obtained by fitting τ. The fitting is as described above. The particle size is obtained from the diffusion coefficient D obtained as described above.

[0088] Alternatively, the particle size calculation step may involve analyzing multiple pieces of time-varying characteristic data of the scattered electric field or scattering intensity to determine the relationship between the particle size or particle diffusion coefficient and the intensity of incident light, assuming that the dependency of the particle diffusion coefficient on the intensity of incident light is linear, as shown in FIG. 2 . Specifically, the particle size is obtained by assuming that the relationship between the particle diffusion coefficient obtained by analyzing the autocorrelation function and the intensity of incident light is linear, for example, as shown by a straight line 12 in FIG. 2 . In this case, the particle diffusion coefficient is determined for each intensity of incident light by analyzing multiple autocorrelation functions or multiple power spectra, for example, by analyzing the autocorrelation function. Next, the particle diffusion coefficient is plotted for each intensity of incident light to determine the relationship between the particle diffusion coefficient and the intensity of incident light. Next, the diffusion coefficient when the intensity of incident light is 0 is determined. The particle size is obtained from this diffusion coefficient. This particle size is independent of the intensity of incident light. In this way, the particle size can be determined even for particles that have the property of absorbing light.

[0089] Furthermore, even if the particle absorbs light and its temperature rises, the particle size can be calculated as follows. In this case, the second temperature after the particle at the first temperature rises due to the absorption of incident light is obtained. Next, the particle size at the second temperature is calculated using the equation representing the diffusion coefficient when a temperature rise occurs, relative to the particle size calculated in the particle size calculation step. The first temperature is as described above. The second temperature after the temperature rise due to the absorption of incident light is obtained using a thermometer or the like. Once the temperature rise can be obtained, the particle size at the second temperature can be calculated using equation (3) representing the diffusion coefficient when the temperature rise occurs. Note that, as described above, T' is the temperature after light absorption, which is the second temperature in this case. η' is the viscosity of the solvent at temperature T', which is the viscosity at the second temperature in this case. Furthermore, since the temperature rise is defined by the above equations (6) and (7), these may also be used. The particle size at the second temperature can be calculated using the above equation (17). In this case, d' in the above equation (17) is the particle size at the second temperature. As for β, as described above, β / d, which indicates the slope of the line showing the intensity dependency of incident light shown in FIG. ０ and the intercept, i.e., the particle size d ０ Search from.

[0090] (Second Example of Optical Measurement Method) Although the above description has been given for monodisperse particles, the particle size distribution can also be determined for particles having a particle size distribution. As described above, the particle size distribution calculation unit 38c calculates the particle size distribution by applying the exponential function exp(-2Dq ２ By fitting τ), the particle size distribution A(d) can be obtained (particle size distribution calculation step).

[0091] The particle size distribution calculation step may further include a step of calculating an index value representing the temperature dependence of particle size using a plurality of pieces of time variation characteristic data of scattering intensity, and a step of correcting the particle size distribution of the particles calculated in the particle size distribution calculation step using the index value representing the temperature dependence of particle size. The index value representing the temperature dependence of particle size is β defined by equation (15) as described above. β is the slope βD of the straight line representing the intensity dependence of incident light shown in FIG. 2 as described above. ０ and the intercept, the diffusion coefficient D０ Furthermore, by using equation (17), the intensity of the incident light in the graph used in FIG. 1 is set to I in equation (17), and the particle size distribution A(d) obtained can be calculated as A(d ０ ) and corrected to obtain the particle size distribution A(d ０ ) is obtained.

[0092] Furthermore, even in the case of particle size distribution, the particle size distribution can be calculated even if the particles absorb light and the temperature rises as described above. In this case, the method includes a step of obtaining a second temperature after the particles at a first temperature have risen in temperature due to light absorption of incident light, and the particle size distribution calculation step can calculate the particle size distribution of the particles by using the second temperature as a diffusion coefficient obtained from multiple time-varying characteristic data of the scattered electric field or scattering intensity. If the temperature rise can be obtained in the particle size distribution, the particle size at the second temperature can be calculated using Equation (3), which represents the diffusion coefficient when the temperature rise occurs. As described above, T is the second temperature after light absorption, and η' is the viscosity at the second temperature after light absorption. Furthermore, since the temperature rise is defined by Equations (6) and (7), these may also be used. The particle size at the second temperature can be calculated using Equation (17). In this case, the particle size at the second temperature can be calculated and the particle size distribution can be obtained using the particle size at the second temperature.

[0093] (Third Example of Light Measurement Device) Figure 9 is a schematic diagram showing a third example of a light measurement device according to an embodiment of the present invention. In Figure 9, the same components as those in the light measurement device 20 shown in Figure 7 are given the same reference numerals, and detailed description thereof will be omitted. The light measurement device 20b shown in Figure 9 differs from the light measurement device 20 shown in Figure 7 in that it further has a function of obtaining multiple scattering intensity data by measuring multiple times the scattering intensity of scattered light obtained by incident light while changing the value of at least one of the measurement parameters, namely the scattering angle and the measurement wavelength.

[0094] 9 includes a low-coherence interferometer 50, a detection section 52 having a first detection unit 52a and a second detection unit 52b, a conversion section 54, a processing section 38, and a storage section 55. The light measurement device 20b includes a sample cell 32. In the light measurement device 20b, the low-coherence interferometer 50 and the detection section 52 having the first detection unit 52a and the second detection unit 52b constitute a measurement section 37. In the light measurement device 20b, the conversion section 54 is not provided in the processing section 38, but the conversion section 54 has the same function as the conversion section 38a of the light measurement device 20 shown in FIG. 7 described above and has the same configuration as the conversion section 38a.

[0095] The low-coherence interferometer 50 is an optical interferometer using a light source that emits low-coherence light. The low-coherence interferometer 50 includes, for example, a light source 22 and four beam splitters 61a, 61b, 61c, and 61d. Each of the four beam splitters 61a, 61b, 61c, and 61d has a transmissive-reflecting surface 61e that splits incident light into two beams or combines two incident beams. The transmissive-reflecting surface 61e is an inclined surface at an angle of 45°. Each of the four beam splitters 61a, 61b, 61c, and 61d is a cube-shaped beam splitter. The shape of the beam splitter is not limited to a cube-shaped beam splitter, and a flat plate-shaped beam splitter may also be used. The low-coherence interferometer 50 is not limited to the configuration shown in FIG. 9 .

[0096] The four beam splitters 61a, 61b, 61c, and 61d are arranged at the vertices of a rectangle. The diagonally arranged beam splitters 61a and 61d have parallel transmission-reflection surfaces 61e. The diagonally arranged beam splitters 61b and 61c have parallel transmission-reflection surfaces 61e. The transmission-reflection surfaces 61e of the four beam splitters 61a, 61b, 61c, and 61d are oriented in different directions from the transmission-reflection surfaces 61e of the adjacent beam splitters 61a, 61b, 61c, and 61d, and are non-parallel, specifically anti-parallel. The beam splitters 61a and 61c are arranged side by side, and a reflector 62 is arranged on the opposite side of the beam splitter 61c from the beam splitter 61a. Between the beam splitter 61c and the reflector 62, a dispersion compensation adjustment unit 63a and an objective lens 63b are arranged from the beam splitter 61c side.

[0097] The reflector 62 reflects incident light, and the reflecting surface 62a of the reflector 62 serves as a reference surface. The reflector 62 is not particularly limited as long as it can reflect incident light, and may be, for example, a mirror or a glass plate. The dispersion compensation adjuster 63a compensates for group velocity dispersion caused by the sample cell 32. When the sample cell 32 is made of optical glass as described below, the dispersion compensation adjuster 63a compensates for group velocity dispersion caused by the thickness of the optical glass constituting the sample cell 32. A glass plate having a thickness similar to that of the optical glass constituting the sample cell 32 is disposed between the beam splitter 61c and the objective lens 63b to compensate for the group velocity dispersion of the passing light. That is, the dispersion compensation adjuster 63a adjusts the difference in optical path length caused by differences in wavelength of the reference light Lr, thereby matching the optical path lengths of the reference light Lr and the scattered light Ld for each wavelength. The objective lens 63 b focuses the light incident on the reflector 62 onto the reflecting surface 62 a of the reflector 62 .

[0098] Beam splitters 61a and 61b are arranged side by side, and an ND (Neutral Density) filter 64a is arranged between the beam splitters 61a and 61b. An ND filter 64b is arranged between the beam splitters 61a and 61c. The ND filters 64a and 64b adjust the amount of light in order to balance the light intensity between the reference light Lr reflected by the reflecting surface 62a of the reflector 62 and the scattered light Ld from the sample cell 32. Known ND filters can be used as the ND filters 64a and 64b as appropriate.

[0099] The sample cell 32 is disposed on the opposite side of the beam splitter 61b from the beam splitter 61a. An objective lens 65 that focuses the incident light Ls onto the sample cell 32 is disposed between the beam splitter 61b and the sample cell 32.

[0100] The beam splitter 61c and the beam splitter 61d are arranged side by side, and the first detection unit 52a is arranged on the opposite side of the beam splitter 61d from the beam splitter 61c. A polarization adjustment unit 66 is arranged between the beam splitter 61d and the first detection unit 52a. The polarization adjustment unit 66 controls the polarization state of the scattered light emitted from the beam splitter 61d and incident on the first detection unit 52a. The polarization adjustment unit 66 is composed of, for example, a polarizing element, and a polarizing element is appropriately used to adjust the polarization state of the scattered light Ld scattered from the dispersion liquid Lq in the sample cell 32 to circular polarization, linear polarization, elliptically polarization, or the like. More specifically, the polarization adjustment unit 66 is composed of, for example, a polarizer. Measurement may be performed by changing the direction of the transmission axis of the polarizer in multiple ways.

[0101] The beam splitter 61b and the beam splitter 61d are arranged side by side, and the second detection unit 52b is arranged on the opposite side of the beam splitter 61d from the beam splitter 61b.

[0102] The first detection unit 52a includes a mirror 70 and a diffraction grating 72 onto which light reflected from the mirror 70 is incident. The diffraction grating 72 is an optical element that wavelength-separates incident light, including scattered light, into light of each wavelength. The diffraction grating 72 can obtain scattered light of each wavelength. The first detection unit 52a further includes a photodetector 73 onto which diffracted light, obtained by diffracting the scattered light according to wavelength by the diffraction grating 72, is incident. The wavelength-separated scattered light is detected by the photodetector 73. The photodetector 73 may be, for example, a line camera in which photoelectric conversion elements are arranged in a line. Note that instead of a line camera, the photodetector 73 may be a line detector in which photomultiplier tubes are arranged in a line. The photodetector 73 of the first detection unit 52a receives diffracted light, including scattered light, diffracted by the diffraction grating 72. The diffraction angle differs for each wavelength, determining the position at which the line camera, which is the photodetector 74, receives the light. Therefore, in the first detection unit 52a, the wavelength is identified based on the position where the light is received by the line camera, which is the photodetector 73. In this way, the first detection unit 52a wavelength-resolves the scattered light and detects the wavelength-resolved scattered light for each wavelength. This makes it possible to easily measure the scattering intensity of scattered light at different wavelengths. Note that, although the diffraction grating 72 is used to obtain light for each wavelength, the device is not limited to the diffraction grating 72 as long as light for each wavelength can be obtained. For example, it is also possible to prepare multiple bandpass filters with different cutoff wavelength bands and obtain scattered light for each wavelength by changing the bandpass filters. Furthermore, a prism can be used instead of the diffraction grating 72.

[0103] The second detection unit 52b has a photodetector 74. The photodetector 74 detects scattered light for each scattering angle. For example, a line camera with photoelectric conversion elements arranged in a straight line is used as the photodetector 74. In the second detection unit 52b, the scattering angle is identified based on the position at which the line camera, which is the photodetector 74, receives light. This makes it possible to easily measure the scattering intensity of the scattered light at different scattering angles. The photodetector 74 also detects the intensity of interference light for each scattering angle, which is light produced by interference between the scattered light and the reference light. Note that the photodetector 74 may be a high-speed camera instead of a line camera. The photoelectric conversion elements used in the photodetectors 73 and 74 are, for example, photodiodes.

[0104] As described above, particle-containing dispersion liquid Lq, which is the measurement target, is stored in sample cell 32. Incident light Ls is irradiated onto dispersion liquid Lq. Although not shown, sample cell 32 may be placed in an immersion bath.

[0105] The light source 22 is disposed on the opposite side of the beam splitter 61a from the beam splitter 61b. The light source 22 irradiates the sample cell 32 with incident light Ls, and causes the emitted light to enter the beam splitter 61a. As described above, the light source 22 changes the intensity of the incident light Ls and emits low-coherence light.

[0106] Between the light source 22 and the beam splitter 61a, a spectral adjustment unit 67 and a polarization control unit 68 are provided from the light source 22 side. The spectral adjustment unit 67 cuts unnecessary wavelength ranges according to the spectrum of the incident light Ls from the light source 22. For example, if the near-infrared light range of the supercontinuum light source cannot be detected by the photodetector 73 of the first detection unit 52a and the photodetector 74 of the second detection unit 52b, the spectral adjustment unit 67 may include, for example, a filter that cuts the near-infrared light range. Furthermore, when measuring the scattering intensity for each scattering angle in the second detection unit 52b, the spectral adjustment unit 67 may include, for example, a bandpass filter to limit the wavelength band. When measuring the scattered light of the dispersion liquid Lq using light of multiple wavelengths, it is also possible to provide multiple light sources with different emission wavelengths as the light source 22. However, using a bandpass filter as the spectral adjustment unit 67 can cut wavelength ranges, simplifying the configuration of the light source 22 and the device configuration.

[0107] The polarization control unit 68 controls the polarization state of the incident light and adjusts the polarization of the incident light. The polarization control unit 68 is composed of, for example, a polarizing element, and a polarizing element such as circularly polarized light, linearly polarized light, or elliptically polarized light is appropriately used depending on the polarization of the light irradiated onto the sample cell 32. When determining the shape of a particle, polarized light is used for the incident light. More specifically, the polarization control unit 68 is composed of a combination of a polarizer and a λ / 4 plate. This makes it possible to convert unpolarized incident light Ls into circularly polarized light. Note that in the light measurement device 20b, if the polarization of the light emitted from the light source 22 is used as is, the polarization adjustment unit 66 and the polarization control unit 68 are not necessarily required.

[0108] The light measurement device 20b, which has the first detection unit 52a and the second detection unit 52b, can easily measure scattering intensity at different scattering angles or different wavelengths. Furthermore, when the light measurement device 20b uses only one of the scattering angle and the wavelength, the detection unit 52 only needs to have either the first detection unit 52a or the second detection unit 52b.

[0109] Light emitted from the light source 22 is split by the transmission-reflection surface 61e of the beam splitter 61a, passes through the transmission-reflection surface 61e to enter the beam splitter 61b, and then passes through the transmission-reflection surface 61e of the beam splitter 61b to be irradiated as incident light Ls onto the sample cell 32. Scattered light Ld generated when the incident light Ls is scattered by the dispersion liquid Lq in the sample cell 32 is reflected by the transmission-reflection surface 61e of the beam splitter 61b to the beam splitter 61d. Of the light emitted from the light source 22, the scattered light Ld reflected by the transmission-reflection surface 61e of the beam splitter 61d is incident on the first detection unit 52a.

[0110] The light split by the transmission-reflection surface 61e of the beam splitter 61a and incident on the beam splitter 61c passes through the transmission-reflection surface 61e, enters the reflector 62, and is reflected by the reflection surface 62a of the reflector 62. This reflected light is the reference light Lr. The reference light Lr is reflected by the transmission-reflection surface 61e of the beam splitter 61c and enters the beam splitter 61d. The reference light Lr transmitted through the transmission-reflection surface 61e of the beam splitter 61d enters the first detection unit 52a. In this manner, the scattered light Ld and the reference light Lr enter the first detection unit 52a and interfere with each other. Note that it is sufficient that at least a portion of the scattered light Ld interferes with the reference light Lr, and it is preferable to adjust the optical path length so that only the scattered light Ld generated at a specific depth in the dispersion liquid Lq interferes with the reference light Lr. In the first detection unit 52a, the light receiving position of the photodetector 73 is determined for each wavelength by the diffraction grating 72, and interference light can be detected for each wavelength, thereby obtaining data on the interference light intensity for each wavelength. As a result, the conversion unit 54 can obtain scattering intensity data for a specific depth and specific wavelength in the dispersion liquid Lq from the interference spectrum of the scattered light. Note that the depth can be considered to refer to the optical path length traveled by the scattered light through the dispersion liquid Lq. Furthermore, the first detection unit 52a can detect interference light for each intensity of incident light for incident light of a specific wavelength, thereby obtaining data on the interference light intensity for each intensity of incident light.

[0111] Furthermore, the scattered light Ld passes through the transmission-reflection surface 61e of the beam splitter 61d and enters the second detection unit 52b. Of the reference light Lr, the reference light Lr reflected by the transmission-reflection surface 61e of the beam splitter 61d enters the second detection unit 52b. In this manner, the scattered light Ld and the reference light Lr enter the second detection unit 52b and interfere with each other. Note that it is sufficient that at least a portion of the scattered light Ld interferes with the reference light Lr, and it is preferable to adjust the optical path length so that only the scattered light generated at a specific depth in the dispersion liquid Lq interferes with the reference light Lr. Depending on the scattering angle θb of the dispersion liquid Lq, the reflection position of the scattered light Ld on the transmission-reflection surface 61e of the beam splitter 61b varies, and the light-receiving position in the photodetector 74 also varies. Therefore, the second detection unit 52b has a predetermined light receiving position of the photodetector 74 for each scattering angle, and can detect the interference light between the reference light and the scattered light for each scattering angle, thereby obtaining data on the interference light intensity for each scattering angle. As a result, the conversion unit 54 can obtain scattering intensity data for a specific scattering angle from the interference light intensity data for each scattering angle for scattered light at a specific depth in the dispersion liquid Lq that corresponds to the same optical path length as the reference light. The scattering angle θb (°) in FIG. 9 is an angle based on backscattered light at a scattering angle of 180°. The general notation for the scattering angle θ (°), in which the angle of forward scattering is 0°, has the relationship θ (°) = 180° - θb (°). Furthermore, the second detection unit 52b can detect interference light at a specific scattering angle for each intensity of incident light, thereby obtaining data on the interference light intensity for each intensity of incident light.

[0112] The converter 54 is connected to the processing unit 38, and the memory unit 55 is connected to the converter 54 and the processing unit 38. The converter 54 extracts multiple values ​​proportional to the scattering intensity or electric field of scattered light of a specific wavelength from the interference light intensity data detected by the first detection unit 52a, or multiple values ​​proportional to the scattering intensity or electric field of light at a specific scattering angle from the interference light intensity data detected by the second detection unit 52b. The converter 54 also extracts multiple values ​​proportional to the scattering intensity or electric field of scattered light of a specific wavelength from the interference light intensity data obtained for each intensity of incident light detected by the first detection unit 52a. The converter 54 also extracts multiple values ​​proportional to the scattering intensity or electric field of light at a specific scattering angle from the interference light intensity data obtained for each intensity of incident light detected by the second detection unit 52b. The converter 54 then converts the extracted scattering intensity data into time-varying characteristic data of the scattering intensity of scattered light at a specific depth in the dispersion liquid Lq.

[0113] The converter 54 is connected to the photodetector 73 of the first detection unit 52a and the photodetector 74 of the second detection unit 52b. The converter 54 acquires data on the light intensity at a specific wavelength detected by the photodetector 73 of the first detection unit 52a and extracts multiple pieces of scattering intensity data for the specific wavelengths. The converter 54 then converts the extracted scattering intensity data into, for example, a power spectrum or an autocorrelation function as time-varying characteristic data on the scattering intensity of scattered light at a specific depth in the dispersion liquid Lq. The converter 54 also causes only scattered light generated at a specific depth in the dispersion liquid Lq by controlling the position of the reflector 62 to interfere, and acquires data on the intensity of the interference light at a specific scattering angle, as detected by the photodetector 74 of the second detection unit 52b, and extracts multiple pieces of scattering intensity at a specific scattering angle. The converter 54 converts the extracted scattering intensity data into, for example, a power spectrum or an autocorrelation function as time-varying characteristic data on the scattering intensity of scattered light at a specific depth in the dispersion liquid Lq. The converter 54 also acquires data on the interference light intensity for each intensity of incident light obtained by the first detection unit 52 a or data on the interference light intensity for each intensity of incident light obtained by the second detection unit 52 b, and extracts multiple scattered intensities for each intensity of incident light. The converter 54 converts the extracted scattered intensity data into, for example, a power spectrum or an autocorrelation function as time-varying characteristic data on the scattering intensity of scattered light at a specific depth in the dispersion liquid Lq.

[0114] The scattered light from the dispersion Lq described above includes light components scattered at various depths in the dispersion Lq, with different numbers of scatterings and different intensities. For accurate measurement of particle size and other characteristics, analysis must be performed using scattered light at a specific depth in the dispersion Lq. By setting a specific depth in the dispersion Lq, it is possible to obtain, for example, single-scattered light, which is light scattered only once, from the scattered light. The analysis performed by the conversion unit 54 to convert the extracted scattering intensity data into time-varying data on the scattering intensity of scattered light at a specific depth in the dispersion Lq will be described later.

[0115] Furthermore, the converter 54 converts the multiple scattered light signals into multiple time-averaged scattered electric field data or time-averaged scattered intensity data. The time-averaged scattered electric field data or time-averaged scattered intensity data is output to the particle size distribution calculation unit 38c of the processing unit 38. The time-averaged scattered electric field data or time-averaged scattered intensity data is a time average of the scattered light signals. As described above, the converter 54 calculates the time average of the multiple scattered light signals and converts them into multiple time-averaged scattered electric field data or time-averaged scattered intensity data, thereby obtaining, for example, the time-averaged scattered intensity at different scattering angles or different wavelengths. For example, data showing the relationship between the scattering angle and the time-averaged scattered intensity can be obtained, which corresponds to scattering angle-dependent data. Note that it is also possible to obtain data showing the relationship between the wavelength and the time-averaged scattered intensity, which corresponds to wavelength-dependent data.

[0116] Furthermore, the multiple pieces of time-averaged scattered electric field data or time-averaged scattered intensity data may be calculated values ​​obtained by simulation. In this case, the simulation is performed by the conversion unit 54. For example, the above-mentioned simulation uses at least one of the Mie scattering theory, the discrete dipole approximation (DDA), and the finite difference time domain (FDTD) method. Note that the discrete dipole approximation (DDA) and the finite difference time domain (FDTD) method correspond to simulations based on the theory of electromagnetic wave behavior. Any simulation based on the theory of electromagnetic wave behavior can be used as appropriate, and is not particularly limited to the above-mentioned discrete dipole approximation (DDA) and the finite difference time domain (FDTD) method. Furthermore, the theoretical formula is not particularly limited to the above-mentioned formulas, and various theoretical formulas such as those based on scattering theory can be used as appropriate.

[0117] The conversion unit 54 extracts multiple scattering intensities as described above and converts the extracted scattering intensity data into time-varying characteristic data of the scattering intensity of scattered light at a specific depth in the dispersion liquid Lq by executing a program (computer software) stored in a ROM (Read Only Memory) or the like in the conversion unit 54. The conversion unit 54 may be configured by a computer in which each part functions by executing a program as described above, or may be a dedicated device in which each part is configured with a dedicated circuit, or may be configured by a server to be executed on the cloud.

[0118] The processing unit 38 has a configuration similar to that of the optical measurement device 20 described above, and includes a particle size calculation unit 38b, a particle size distribution calculation unit 38c, and an arithmetic unit 38d. The particle size calculation unit 38b of the processing unit 38 uses the time-varying characteristic data of the scattering intensity acquired by the conversion unit 54 to calculate particle size in a manner similar to that of the optical measurement device 20 shown in FIG. 7 described above. The processing unit 38 also obtains particle size distributions for multiple particle species contained in the dispersion by fitting the time-varying characteristic data of the scattering intensity acquired by the conversion unit 54 and the time-averaged scattered electric field data or time-averaged scattered intensity data acquired by the conversion unit 54 to a theoretical formula that defines the relationship between particle size and scattering intensity. The processing unit 38 can appropriately use various calculation methods used in dynamic light scattering to calculate particle size. Obtaining particle size distributions for multiple particle species contained in the dispersion will be described later.

[0119] The memory unit 55 stores at least one of scattering angle-dependent data on the scattered light intensity of a known particle and wavelength-dependent data on the scattered light intensity, which are determined from the complex refractive index, particle size, and shape of the known particle. By storing at least one of the scattering angle-dependent data on the scattered light intensity of a known particle and the wavelength-dependent data on the scattered light intensity of a known particle in the memory unit 55, the data can be referenced when determining the particle size distribution of the particle or during fitting. For this reason, it is preferable to store at least one of the scattering angle-dependent data on the scattered light intensity of a known particle and the wavelength-dependent data on the scattered light intensity of a known particle for various particles, thereby constructing a model library. The memory unit 55 also stores various data obtained by the conversion unit 54. Note that the memory unit 55 is not particularly limited as long as it can store the scattering angle-dependent data on the scattered light intensity of a known particle and the wavelength-dependent data on the scattered light intensity of a known particle, as well as the various data obtained by the conversion unit 54. For example, various storage media such as a hard disk or an SSD (solid state drive) can be used.

[0120] Similar to the above-described optical measurement device 20, the optical measurement device 20b changes the intensity of incident light from the light source 22, and measures the scattering intensity of the scattered light obtained by causing the incident light to be incident on the dispersion liquid Lq multiple times to obtain multiple scattering intensity data in the conversion unit 54. The conversion unit 54 converts the multiple scattering intensity data into multiple time-varying characteristic data of the scattered electric field or the scattered intensity. Then, the particle size calculation unit 38b calculates the particle size d that does not depend on the intensity of the incident light described above using the multiple time-varying characteristic data of the scattered electric field or the scattered intensity. ０ The particle diameter d, which does not depend on the intensity of the incident light, is calculated. ０ is the measured particle size of the particle. The optical measurement device 20b has a particle size distribution calculation unit 38c, similar to the optical measurement device 20 described above.

[0121] The processing unit 38 also has a calculation unit 38d that performs fitting to obtain particle size distributions for multiple particle types using at least one of the scattering angle-dependent data of scattered light intensity and the wavelength-dependent data of scattered light intensity for known particles stored in the memory unit 55. The calculation unit 38d obtains particle size distributions by fitting multiple pieces of time-variation characteristic data of the scattered electric field or scattering intensity obtained by the conversion unit 38a and multiple pieces of time-averaged scattered electric field data or time-averaged scattered intensity data to a theoretical formula that defines the relationship between particle size and scattering intensity. The fitting by the calculation unit 38d will be described later.

[0122] The calculation unit 38d of the processing unit 38 can also read various data obtained by the conversion unit 54 and stored in the memory unit 55, and perform fitting. The processing unit 38 can also determine the aggregation state or particle type of particles by comparing the particle size distribution value obtained from the actual measurement fluctuation data and the wavelength dependence or intensity dependence of the actual measurement scattered light with the particle scattering characteristics stored in the model library. The scattering characteristics of particles are, for example, data on the scattering angle dependence of scattered light intensity and data on the wavelength dependence of scattered light intensity for known particles. These particle scattering characteristics may be actual measurements obtained using known particles such as standard particles, or calculated values ​​obtained using a theoretical formula that defines the relationship between particle size and scattering intensity, such as the Mie scattering theory formula. The scattering characteristics of particles may also be calculated values ​​obtained by simulation. The calculated values ​​obtained by simulation are, for example, obtained using the finite-difference time-domain method (FDTD) or the discrete dipole approximation (DDA) method. The scattering characteristics of the particles described above are stored in the storage unit 55 as, for example, a model library.

[0123] In the light measurement device 20b, the reference light Lr may be blocked to prevent interference with the scattered light. In this case, blocking the reference light Lr allows for normal dynamic light scattering measurement. For example, a retractable light shielding plate may be provided between the beam splitters 61a and 61c to prevent the light split by the beam splitter 61a from reaching the reflector 62. Alternatively, a retractable light shielding plate may be provided between the beam splitters 61c and 61d to shield the reference light Lr from reaching the beam splitter 61d. Note that the light shielding plate is not limited to a retractable light shielding plate, as long as it can shield light. For example, a light shutter using a liquid crystal shutter may be used. With the above configuration, the light measurement device 20b can also be used as a normal homodyne detection dynamic light scattering device.

[0124] In the light measurement device 20b, the measurement unit 37 detects the intensity of interference light for each intensity of incident light. As a result, the scattering intensity of the scattered light obtained by making the light incident on the dispersion liquid Lq as described above is measured multiple times, and the conversion unit 54 obtains multiple scattering intensity data for each intensity of incident light, and converts the multiple scattering intensity data into multiple time-varying characteristic data of the scattered electric field or scattering intensity. The particle size calculation unit 38b calculates the measured particle size of the particles using the multiple time-varying characteristic data of the scattered electric field or scattering intensity. In other words, the particle size d ０ The optical measurement device 20b first determines the measured particle size of the particles, and the measured particle size is used when the calculation unit 38d determines the particle size distribution.

[0125] The light measurement device 20b detects, for example, the interference light intensity for each wavelength. From the interference light spectrum obtained by the first detection unit 52a, for example, interference intensity spectra for three wavelengths with center wavelengths of 620 nm, 640 nm, and 660 nm are extracted as representatives. Note that the wavelength width for each of the center wavelengths 620 nm, 640 nm, and 660 nm is ±9 nm. Next, the conversion unit 54 acquires signal component data proportional to the electric field of the scattered light at each wavelength at a specific depth from the interference light intensity detected by the first detection unit 52a. The scattering intensity data for each wavelength is converted into a power spectrum as time-varying characteristic data of the scattering intensity of the scattered light at a specific depth in the dispersion liquid Lq. This results in a power spectrum. Furthermore, the conversion unit 54 performs an inverse Fourier transform on the power spectrum to obtain an autocorrelation function for each wavelength.

[0126] Next, in the processing unit 38, for example, the common logarithm (log １０ The gradient Γg is used to calculate the diffusion coefficient D at each wavelength. The diffusion coefficient D is calculated as follows: D = Γg / q ２ where q is the scattering vector. Here, the diffusion coefficient D and particle size d are expressed by the Stokes-Einstein formula (see formula (1)) as described above. Note that the method of calculating the particle size distribution from the slope of the autocorrelation function is not limited to this method, and the CONTIN method, histogram method, cumulant expansion, etc. are also known, and these methods can be used.

[0127] Next, in the processing unit 38, the hydrodynamic particle size of the particle at each wavelength is calculated using the diffusion coefficient D of each wavelength. This hydrodynamic particle size is the particle size d described above. The above-mentioned light measurement devices 20, 20a, and 20b are all light measurement devices that use low-coherence dynamic light scattering (LC-DLS), and acquire time-varying characteristic data of the scattered electric field, rather than time-varying characteristic data of the scattered intensity. Note that the scattering intensity and the scattered electric field are expressed as follows: Scattering intensity = |Scattering electric field| ２ There is a relationship between

[0128] (Third Example of Optical Measurement Method) In the third example of the optical measurement method, multiple intensities of incident light are used in the optical measurement device 20b. As described above, the scattering intensity of the scattered light obtained by injecting light into the dispersion liquid Lq is measured multiple times, and multiple scattering intensity data are obtained in the conversion unit 54, and the multiple scattering intensity data are converted into multiple time-varying characteristic data of the scattered electric field or scattering intensity. In the particle size calculation unit 38b, the multiple time-varying characteristic data of the scattered electric field or scattering intensity is used to determine the measured particle size. Furthermore, in the third example of the optical measurement method, multiple wavelengths are used in the optical measurement device 20b. For example, a supercontinuum light source is used to measure the dispersion liquid containing particles. Through measurement, light of each wavelength is detected by the photodetector 73 of the first detection unit 52a. The light of each wavelength incident on the photodetector 73 includes interference light between the scattered light and the reference light, and is represented, for example, by an interference spectrum. The intensity I of the interference spectrum ｋ is expressed by the following formula: In the following formula, E Ｓ is the electric field of the scattered light, and E Ｓ ＊ is E Ｓ is the complex conjugate of E Ｒ is the electric field of the reference beam, and E Ｒ ＊ is E Ｒ is the complex conjugate of I ｋ =|E Ｒ +E Ｓ | ２ =|E Ｒ | ２ + | E Ｓ | ２ +E Ｒ E Ｓ ＊ +E Ｓ E Ｒ ＊

[0129] Next, for example, a wavelength region (not shown) with a central wavelength of 620 nm is extracted from the interference spectrum. The width of the wavelength region is ±9 nm from the central wavelength of 620 nm. In this way, the scattering intensity of a specific wavelength region is extracted from the scattering intensity data for each wavelength. After extracting the scattering intensity of a specific wavelength region, the intensity I of the interference spectrum for the wavelength region is calculated. ｋ For the inverse Fourier transform F ‐１As a result, for example, a scattering profile F in the depth direction of the dispersion liquid Lq at a center wavelength of 620 nm is obtained. ‐１ (I Ｋ The depth direction of the dispersion liquid Lq is the optical axis direction of the objective lens 65.

[0130] The inverse Fourier transform described above is expressed by the following equation: F ‐１ (I Ｋ ) = |r ｒ | ２ E ０ ２ δ(z)+r ｒ E ０ ２ ρ(s / 2)+E ０ ２ Gamma ρ (s / 2) where r ｒ is the reflectivity of the reflector 62 to the electric field, and E ０ is the electric field of the light irradiated onto the sample, δ(z) is a delta function, ρ is the diffuse reflectance of the scattered electric field from a position at a depth s / 2 from the interface of the dispersion, and Γ ρ is the autocorrelation function for the depth dependence of the diffuse reflectance of the scattered electric field. In the depth profile of the dispersion, for example, a single scattering region is extracted as the depth region of interest. The single scattering region, i.e., the region where light is scattered only once, is determined by the optical path length in the light measurement device 20b, and it is preferable to specify the optical path length of the single scattering region in advance in the light measurement device 20b. Note that the above-mentioned depth region of interest corresponds to a specific depth in the dispersion Lq.

[0131] The first detection unit 52a obtains the time response of the electric field in the depth of interest region. All the time series data of the signals obtained by the photodetector 73 are processed in the same manner to obtain the scattered electric field E ０ The time dependence of the signal amount proportional to ρ(s / 2) is obtained. The time dependence of the scattered electric field is Fourier transformed and squared. This gives the frequency response of the scattered light intensity, i.e., the power spectrum. Note that the power spectrum I ＥＳ is expressed by the following formula. ＥＳ is the autocorrelation function of the electric field.

[0132]

[0133] Next, the power spectrum I ＥＳ The inverse Fourier transform is then performed on F, which gives the autocorrelation function of the scattered electric field. The inverse Fourier transform is expressed by the following equation: ‐１ (I ＥＳ ) = Γ ＥＳ (τ) = G ＥＳ （１） (τ) In this manner, a power spectrum or autocorrelation function is obtained as time-varying characteristic data of the scattering intensity of scattered light at a specific depth in the dispersion liquid Lq from the extracted interference light intensity data. The conversion of the scattering intensity data for each wavelength detected by the first detection unit 52a into a power spectrum or autocorrelation function for a specific depth in the dispersion liquid Lq is performed by the conversion unit 54. Next, the particle size calculation unit 38b of the processing unit 38 calculates the particle size using the power spectrum or autocorrelation function, which is the time-varying characteristic data of the scattering intensity acquired by the conversion unit 54. The method of calculating the particle size using the autocorrelation function is as described above. This particle size is different from the measured particle size described above.

[0134] The wavelength dependence of the time-averaged scattered electric field can be obtained by extracting the wavelength region, calculating the time average of the signal in the depth of interest region, and dividing this by the intensity signal in the reference light spectrum for the same wavelength region. Further squaring this gives the scattered light intensity normalized by the light source spectrum. In this manner, information on single-scattered static light scattering in the wavelength region with a central wavelength of 620 nm can be obtained. For example, for the wavelength region with a central wavelength of 640 nm, or for the wavelength region with a central wavelength of 660 nm, information on single-scattered static light scattering at each wavelength can be obtained by extracting the wavelength region with a central wavelength of 640 nm and the wavelength region with a central wavelength of 660 nm from the interference spectrum. The width of the wavelength region is, for example, ±9 nm relative to the central wavelengths of 640 and 660 nm.

[0135] In the case of a bridged aggregate, the average interparticle distance is equal to or greater than the particle size of a single particle. Data on single particles and bridged aggregates is stored as a model library in the memory unit 55 (see Figure 9). The bridged aggregate is composed of, for example, particles of a predetermined size and a polymer present between the particles. The polymer is often a polymer having a functional group (e.g., a polar group) that aggregates the particles together. In the case of a bridged aggregate, the scattering intensity decreases with increasing wavelength. On the other hand, in the case of a single particle, the scattering intensity increases with increasing wavelength.

[0136] Dynamic light scattering (DLS) only determines the hydrodynamic size of particles. Therefore, even if the particle size is known, it is not possible to determine whether a particle is a crosslinked aggregate or a single particle. Since the scattering intensity of a single particle increases with increasing wavelength, the particle can be determined to be a single particle. The determination of a single particle is performed by the processing unit 38. By combining the wavelength dependence of dynamic light scattering and static light scattering and comparing them with data from the model library using the procedure described below (see FIG. 10 ), it is possible to determine not only the hydrodynamic particle size but also the state and type of particles in the dispersion. The state of particles in the dispersion is, for example, an aggregated state. The type and state of particles in the dispersion are determined by the processing unit 38. It is sufficient for the processing unit 38 to determine at least one of the type and state of particles in the dispersion.

[0137] (Fourth Example of Light Measurement Method) In the fourth example of the light measurement method, the scattered light is obtained by varying the value of at least one of the scattering angle and the measurement wavelength among the measurement parameters. The method includes a conversion step of converting the multiple scattered light signals obtained in the measurement step into multiple time-averaged scattered electric field data or time-averaged scattered intensity data, and a calculation step of calculating the particle size or particle size distribution for each of multiple particle species from the time-averaged scattered electric field data or time-averaged scattered intensity data and the time-varying characteristic data. The measurement step includes a step of measuring the scattering intensity of the scattered light obtained by varying the intensity of incident light into the dispersion liquid multiple times to obtain multiple scattering intensity data, and a step of measuring the scattering intensity of the scattered light obtained by varying the value of at least one of the scattering angle and the measurement wavelength among the measurement parameters to obtain multiple scattering intensity data. The conversion step is a step of calculating multiple time-varying characteristic data of the scattered electric field or scattering intensity from the multiple scattering intensity data obtained in the measurement step. The fourth example of the light measurement method will be described in detail below, but the following description is merely an example and is not particularly limited to the following description.

[0138] In a fourth example of the light measurement method, a dispersion containing multiple particle species is measured using the scattering angle, which is one of the measurement parameters of scattering angle and measurement wavelength, and the particle size or particle size distribution for each of the multiple particle species is calculated. Furthermore, a supercontinuum light source, for example, is used as the light source. In the light measurement device 20b, incident light of multiple different wavelengths is irradiated onto a dispersion Lq containing particles (not shown), resulting in scattered light. The first detection unit 52a detects the scattered light at each wavelength using a photodetector 74, and obtains interference light intensity data for each wavelength. In the conversion unit 54, scattering intensity data for a specific scattering angle is obtained from the interference light intensity data. Next, the extracted scattering intensity data is converted into an autocorrelation function as time-varying characteristic data of the scattering intensity of the scattered light at a specific depth in the dispersion. This process is repeated multiple times by changing the intensity of the incident light, thereby obtaining multiple scattering intensity data for each intensity of the incident light (first measurement step). The multiple scattering intensity data obtained in the first measurement step are converted into multiple time-varying characteristic data of the scattering electric field or scattering intensity (first conversion step). In the first conversion step, for example, multiple autocorrelation functions are acquired for each intensity of incident light. Next, as described above, the measured particle size of the particles is calculated using the multiple autocorrelation functions for each intensity of incident light (particle size calculation step). The measured particle size of the particles obtained in the particle size calculation step is a particle size that does not depend on the intensity of incident light. As described below, the particle size distribution is calculated using the measured particle size of the particles (particle size distribution measurement step).

[0139] Next, the scattered light obtained by varying at least one of the measurement parameters, the scattering angle and the measurement wavelength, is measured multiple times to obtain multiple scattering intensity data (second measurement step). The multiple scattering intensity data obtained in the second measurement step are then converted into multiple time-varying characteristic data of the scattered electric field or scattering intensity and multiple time-averaged scattered electric field data or time-averaged scattered intensity data (second conversion step). Next, the multiple time-varying characteristic data of the scattered electric field or scattering intensity obtained in the second conversion step and the multiple time-averaged scattered electric field data or time-averaged scattered intensity data are fitted to a theoretical formula defining the relationship between particle size and scattering intensity to obtain the particle size distribution (particle size distribution measurement step). When obtaining the particle size distribution, the measured particle size obtained in the particle size calculation step is used as the particle size in the theoretical formula defining the relationship between particle size and scattering intensity. This allows for highly accurate particle size distribution to be obtained even for particles that have light-absorbing properties.

[0140] More specifically, in the light measurement device 20b, the dispersion liquid Lq is irradiated with a plurality of different incident light beams to generate scattered light, and the light at each wavelength is detected by the photodetector 74 in the first detection unit 52a, to obtain data on the intensity of the interference light. The conversion unit 54 obtains scattering intensity data for each wavelength from the scattering intensity data. Next, the extracted scattering intensity data is converted into an autocorrelation function as time-varying characteristic data of the scattering intensity of scattered light at a specific depth in the dispersion liquid, as described above.

[0141] Next, the fitting of the time variation characteristic data of the scattering intensity acquired by the conversion unit 54 and the time averaged scattered electric field data or time averaged scattered intensity data acquired by the conversion unit 54 to a theoretical formula that defines the relationship between particle size and scattering intensity in the processing unit 38 will be described. By the above-mentioned fitting, the particle size distribution of each of the multiple particle types contained in the dispersion liquid can be obtained. The following calculation formula can also be applied to quantification or particle type determination when there are two or more types of particles contained in the dispersion liquid. The method for this is described below. For fitting, in addition to the theoretical formula that defines the relationship between particle size and scattering intensity, known particle scattering characteristics can also be used.

[0142] FIG. 10 is a flowchart showing a fourth example of an optical measurement method according to an embodiment of the present invention. In the fourth example of the optical measurement method, the measured particle size, which is independent of the intensity of the incident light, is calculated before the measurement step (step S10) of FIG. 10 . As shown in FIG. 10 , the optical measurement method includes, for example, a measurement step (step S10), an experimental data acquisition step (step S12), a pre-calculated value acquisition step (step S14), and an optimization step (step S16). The optimization step (step S16) provides analysis results, i.e., particle size distributions for multiple particle types (step S18). The measurement step (step S10) measures, for example, the time fluctuation of the interference light intensity and the scattering angle dependence or wavelength dependence of the time-averaged interference light intensity. Step S10 corresponds to a second measurement step. The experimental data acquisition step (step S12) obtains, for example, a time correlation with the time fluctuation of the interference light intensity based on the measurement value of the measurement step (step S10). Furthermore, the scattering angle dependence of the time average value of the interference light intensity or the wavelength dependence of the time average value of the interference light intensity is obtained. Step S12 corresponds to the second conversion step.

[0143] In the step of obtaining pre-calculated values ​​(step S14), the scattering properties of the particles are obtained using, for example, the data on single particles and cross-linked aggregates stored in the memory unit 55 as a model library. The scattering properties of known particles may be actual measurements using standard particles as described above. Calculated values ​​obtained by theoretical formulas or simulations may also be used as the scattering properties of the particles. As described above, the scattering properties of the particles are, for example, data on the scattering angle dependence of scattered light intensity and data on the wavelength dependence of scattered light intensity for known particles. The scattering properties of the particles obtained in step S14 are used, for example, to identify particles in a dispersion or multiple particle species in a dispersion. For example, the particle species and the state of the particles in the dispersion are determined by comparing the measured values ​​obtained in step S10, such as particle size distribution values ​​obtained from actual measurement fluctuation data, and actual measurement data on the wavelength dependence of scattered light or data on the intensity dependence of scattered light, with the scattering properties of the particles in step S14. The wavelength-dependent data and intensity-dependent data of the actually measured scattered light are obtained from the time-fluctuation characteristic data of the scattering intensity of the scattered light acquired by the conversion unit 54. In the optimization step (step S16), for example, a first-order autocorrelation function and a theoretical formula for scattering intensity are fitted to the time correlation of the time fluctuation of the interference light intensity and the time average value of the interference light intensity obtained in step S12. In step S16, initial values ​​are set for the number of particles for all particle sizes, and then the evaluation values ​​are updated to minimize the evaluation values, thereby obtaining the final number of particles. The fitting will be described in more detail below.

[0144] (First Example of Fitting) An example will be described in which there are two types of particles, particle A and particle B, in a dispersion liquid. It is assumed that the types of particles A and B, and the wavelength dependence of the complex refractive index of particles at each particle size are known. In this case, there is data on the wavelength dependence of scattered light intensity, which is calculated from the complex refractive index, particle size, and shape of the known particles, and this data is stored in the storage unit 55 (see FIG. 9) as a model library. The first-order autocorrelation function g （１） (τ) is g （１） (τ) = exp(-Dq ２When two types of particles, particle A and particle B, exist in the dispersion liquid, the first-order autocorrelation function is expressed by the following formula (19). The scattering intensity is expressed by the following formula (20). The following formulas (19) and (20) are theoretical formulas, and Is in formulas (19) and (20) total are all calculated values. ｄ´ A and I ｄ´ B is a theoretical value, and the pre-calculated value obtained in step S14 above can be used. （１） denotes the first-order autocorrelation function. total indicates the total scattering intensity. d' and d ０ indicates particle size. d' and d ０ The subscripts 0 to M of ( ) indicate the ordinal numbers of the bins in the histograms shown in Figures 11 and 12. N indicates the number of particles. The subscripts 0 to M of N indicate the ordinal numbers of the bins in the histograms shown in Figures 11 and 12. Note that a histogram bin refers to a data interval in the histogram, and is represented by a bar in the histogram. D indicates the diffusion coefficient. The subscript d' of the diffusion coefficient D indicates that it depends on the particle size d'. q indicates the scattering vector. τ indicates the time lag of the first-order autocorrelation function. θ indicates the scattering angle. Is indicates the scattering intensity. The subscript d of the scattering intensity Is indicates that it depends on the particle size d. In the following equations (19) and (20), the superscripts A and B indicate that the wavelength dependence of the scattering intensity corresponds to particle A and particle B.

[0145]

[0146] In the above formula (19), the following term corresponds to particle A and corresponds to the histogram of particle A shown in FIG. 11. In the following term, exp(-Dqτ) is a first-order autocorrelation function, and the other N ｄ´ A Is ｄ´ A / Is total The part of Is in equation (19) indicates the ratio of the scattering intensity of all particles A belonging to the bin of particle size d' to the total reflection intensity. In other words, it is the weighting of particle A. totalis a theoretical value determined by particle size. The Mie scattering theory formula can be used as the theoretical value. Is in formula (19) total corresponds to parameter-dependent data of scattering intensity, and corresponds to time-averaged scattered electric field data or time-averaged scattered intensity data.

[0147]

[0148] In the above formula (19), the following term corresponds to particle B, and corresponds to the histogram of particle B shown in FIG. 12. In the following term, exp(-Dqτ) is a first-order autocorrelation function, and the other N ｄ´ B Is ｄ´ B / Is total The part indicates the ratio of the scattering intensity of all particles B belonging to the bin of particle size d' to the total reflection intensity. In other words, it is the weighting of particle B.

[0149]

[0150]

[0151] In the above formula (20), N ｄ０ A Is ｄ０ A corresponds to the scattering intensity of particle A, and N ｄ０ B Is ｄ０ B corresponds to the scattering intensity of particle B.

[0152] The fitting for determining the particle size distribution for each of a plurality of particle types will be described below. In the fitting, particle size is used as a fitting parameter, and the number of particles is used as a variable, and the number of particles for each particle size is finally determined. The first-order autocorrelation function g （１）(τ) is actually measured for each wavelength, and there are multiple values. The actually measured values ​​are, for example, the autocorrelation functions of the multiple wavelengths described above. In fitting, for the first-order autocorrelation function for each wavelength, the number of particles is used as a variable to set the initial number of particles in Equation (19). The calculated value of the first-order autocorrelation function of Equation (19) based on the set initial number of particles is obtained. The first-order autocorrelation function for each wavelength corresponds to the time variation characteristic data of the scattering intensity derived from the scattering characteristics using the theoretical formula. For each wavelength, the difference between the value of the actually measured first-order autocorrelation function and the calculated value of the first-order autocorrelation function of Equation (19) is obtained. Note that the difference between this actually measured value of the first-order autocorrelation function and the calculated value of the first-order autocorrelation function of Equation (19) is called the difference of the first-order autocorrelation functions. The difference of the first-order autocorrelation functions is obtained for each wavelength.

[0153] For example, the total scattering intensity Is total is measured for each wavelength. total From this, it can also be determined that the particles are not aggregates but single particles. In equation (20), the number of particles is set as a variable. The total scattering intensity Is in equation (20) based on the set initial number of particles is total The measured total scattering intensity Is for each wavelength is calculated. total and the total scattering intensity Is of Equation (20) total The difference between the calculated value and the measured total scattering intensity Is at any wavelength is calculated. total and the total scattering intensity Is of Equation (20) total The difference between the calculated value and the total scattering intensity at wavelength Is total The difference between the total scattering intensity Is total For the total scattering intensity at wavelength Is total The difference between the total scattering intensity Is in Equation (20) is obtained. total The calculated value corresponds to the time-averaged data obtained by averaging the time-variation characteristic data of the scattering intensity.

[0154] In fitting, the difference between the first-order autocorrelation functions obtained for each wavelength and the difference between the total scattering intensities at each wavelength are used to determine the final particle number. For example, an evaluation value is used that is obtained by adding, for all wavelengths, the squared value of the difference between the first-order autocorrelation functions obtained for each wavelength and the squared value of the difference between the total scattering intensities at each wavelength. The number of particles that minimizes the evaluation value is taken as the final particle number. Therefore, in fitting, the number of particles is repeatedly updated in equations (19) and (20) to minimize the evaluation value, thereby obtaining the final particle number. This corresponds to step S16 described above. After initial values ​​are set for the particle numbers for all particle sizes, they are updated to minimize the evaluation value. By obtaining the final particle number described above for each particle size, for example, the histogram of particle A shown in FIG. 11 and the histogram of particle B shown in FIG. 12 can be obtained. That is, N ｄ´ A , N ｄ´ B For all d' = d ０ ~d Ｍ The particle size distribution can be obtained by calculating the following. This corresponds to step S18 described above. The particle size distribution is the distribution of particle numbers relative to particle size, and is expressed in units of %, for example. The above steps are steps for determining the particle size distribution for each of a plurality of particle types. Note that the evaluation values ​​used in fitting are not limited to those described above.

[0155] The first-order autocorrelation function in the following formula (19) is a value obtained by measurement, and if the particles have the property of absorbing light, the particle size will change depending on the intensity of the incident light as described above. On the other hand, formula (20) is a theoretical value, and the particle size in formula (20) is a particle size that is not affected by the intensity of the incident light. Therefore, the particle size in formula (19) does not match the particle size in formula (20). The particle size d' of the autocorrelation function in formula (19) is calculated based on the measured particle size obtained in advance, i.e., the particle size d that is not dependent on the intensity of the incident light. ０(19) and the particle size in equation (20) are made to coincide with each other. In this state, the particle size distribution of the particles is obtained by fitting a plurality of pieces of time-varying characteristic data of the scattered electric field or scattering intensity and a plurality of pieces of time-averaged scattered electric field data or time-averaged scattered intensity data to a theoretical equation that defines the relationship between particle size and scattering intensity, with particle size as a fitting parameter and the number of particles as a variable. This makes it possible to accurately measure the particle size distribution of particles contained in a dispersion containing particles that have the property of absorbing light.

[0156] The light measurement device 20b can determine the type of particles in the dispersion liquid by utilizing the difference in scattering intensity with respect to wavelength. Therefore, by specifying the relationship between the type of particle and the scattering intensity with respect to wavelength in advance, the type of particle and the particle size distribution of the particles can also be determined. It is preferable to store the relationship between the type of particle and the interference light intensity with respect to wavelength in the memory unit 55. The processing unit 38 can also read out the relationship between the type of particle and the interference light intensity with respect to wavelength from the memory unit 55 and determine the type of particle and the particle size distribution of the particles.

[0157] As described above, the two theoretical equations (19) and (20) are used to calculate the first-order autocorrelation function and the total scattering intensity Is totalThe final particle count is determined by fitting to the above-described equation. However, the optimization method for fitting is not limited to the above-described one. For example, Bayesian optimization can be used for fitting. Although a first-order autocorrelation function was used to determine the particle count as described above, this is not limiting. A power spectrum can also be used instead of the first-order autocorrelation function. Furthermore, by fitting the autocorrelation function or power spectrum of the scattering intensity and the scattering intensity for each wavelength to the theoretical formula as described above, the particle count and particle size distribution for each particle type, such as particle A and particle B, can be obtained. Furthermore, if the dispersion contains impurity components, the impurity components and the particle size distribution for each particle type can be obtained, thereby isolating the influence of the impurity components. For fitting, in addition to the theoretical formula, time-varying characteristic data of the scattering intensity derived from the scattering characteristics of known particles, time-averaged scattering electric field data, or time-averaged scattering intensity data can also be used. Although the example using two wavelengths has been described, the number of wavelengths is not limited to two. As long as there are multiple wavelengths, the number of wavelengths can be three or four.

[0158] Furthermore, although the particle size distribution for each of a plurality of particle species is calculated by fitting or the like from the time-averaged scattered electric field data or the time-averaged scattered intensity data and the time-varying characteristic data as described above, the present invention is not limited to this. For example, the particle size for each of a plurality of particle species can also be calculated from the time-averaged scattered electric field data or the time-averaged scattered intensity data and the time-varying characteristic data. In this case, for example, the average particle size for each of the plurality of particle species is calculated from the particle size distribution for each of the plurality of particle species. This average particle size for each particle species is set as the particle size of each particle. The average particle size for each particle species is calculated by particle size calculation unit 38b.

[0159] The complex refractive index can also be determined. As described above, the real part of the complex refractive index is what is called the refractive index. The imaginary part of the complex refractive index is what is called the extinction coefficient, which represents absorption. The conversion unit 54 (see FIG. 9 ) converts the multiple scattering intensity data obtained by the first detection unit 52 a into time-varying characteristic data of the scattering intensity and time-averaged scattered electric field data or time-averaged scattered intensity data, and fits the acquired time-varying characteristic data of the scattering intensity and the time-averaged scattered electric field data or time-averaged scattered intensity data using a theoretical formula that defines the relationship between the refractive index, particle size, and scattering intensity, or a simulation based on the theory of electromagnetic wave behavior. The fitting identifies the number of multiple particle species in the dispersion, the refractive index of the particles, and the particle size distribution of the particles, and can also identify the material of each particle species identified in the dispersion. The fitting will be described later. In this case, as with the above-described light measurement device 20, the intensity of incident light from the light source 22 is changed, and the scattered light obtained by causing the incident light to enter the dispersion liquid Lq is measured multiple times to obtain multiple scattering intensity data, which are then converted into multiple pieces of time-varying characteristic data for the scattered electric field or scattering intensity. The multiple pieces of time-varying characteristic data for the scattered electric field or scattering intensity are then used to determine the measured particle size of the particles. The measured particle size of the particles is first determined, and this measured particle size is used to determine the particle size distribution.

[0160] In addition to the theoretical formula defining the relationship between particle size and scattering intensity, time-varying characteristic data of the scattering intensity of the measurement parameter calculated by a simulation based on the theory of electromagnetic wave behavior, and time-averaged scattered electric field data or time-averaged scattered intensity data of the calculated measurement parameter may also be used. Note that the processing unit 38 calculates the time-varying characteristic data of the scattering intensity of the calculated measurement parameter as described above.

[0161] When measuring the scattered light of a dispersion, the scattering angle is used as a measurement parameter. When the measurement parameter is the scattering angle, the scattered light of the dispersion is measured by changing the scattering angle by two or more angles as the measurement parameter value. In this case, for example, the measurement wavelength is fixed to one. When the measurement parameter is the measurement wavelength of the measurement light, the scattered light of the dispersion is measured using two or more measurement wavelengths. In this case, for example, the scattering angle is fixed to one. The two wavelengths are the measurement parameter value. The measurement parameters may also be the scattering angle and the measurement wavelength. In this case, the scattering angle value is set to two or more angles, and the scattered light of the dispersion is measured using two or more measurement wavelengths, each combination of the scattering angle and the measurement wavelength. The scattering angle value is not particularly limited as long as it is two or more angles, but is appropriately determined based on the number of scattering intensity data points, the measurement time, etc. The scattering angle value is preferably greater than 0° and 180°. The measurement wavelength is also not particularly limited as long as it is two or more wavelengths. The measurement wavelength is appropriately determined taking into consideration that a larger number of measurement wavelengths requires more light sources and optical elements for separating wavelengths. Furthermore, the measurement wavelength is not particularly limited, and light of various wavelengths such as ultraviolet light, visible light, and infrared light can be used as appropriate.

[0162] As described above, the scattering intensity can be measured using a single measuring device, either by the light scattering measurement method or by combining the light scattering measurement method and the light scattering goniophotometer. Alternatively, measurement data from two different devices, a dynamic light scattering measurement device and a light scattering goniophotometer, can be used in combination. In the case of wavelength, a spectrometer may also be used. As described above, the device is not limited to the light measurement device 20b shown in FIG. 9 . The dispersion liquid may contain at least one type of particle, and may contain multiple types. In other words, assuming that there are multiple types of particle species in the dispersion liquid, a theoretical formula is established that defines the relationship between the refractive index, particle size, and scattering intensity, and the material of each particle type is identified.

[0163] (Fifth Example of Optical Measurement Method) FIG. 13 is a flowchart showing a fifth example of an optical measurement method according to an embodiment of the present invention. In the fifth example of the optical measurement method, the measured particle size is determined before the measurement step (step S20) of FIG. 13 . In the fifth example of the optical measurement method, the measurement parameter is the scattering angle, and the scattering intensity of the scattered light from the dispersion is measured while changing the scattering angle value by two or more degrees. As shown in FIG. 13 , the fifth example of the optical measurement method includes, for example, a measurement step (step S20), a step of obtaining experimental data (step S22), a step of obtaining pre-calculated values ​​(step S24), an optimization step (step S26), a step of obtaining optimization results (step S28), a step of performing refractive index matching (step S30), and a step of obtaining analysis results (step S32). Furthermore, the fifth example of the optical measurement method includes a step of preparing a library (step S34). The step of obtaining analysis results (step S32) identifies the material of each particle type of particles contained in the dispersion.

[0164] The library associates materials with their refractive indices. The refractive indices in the library are actual measured values ​​or values ​​described in literature. The refractive indices may also be complex refractive indices. For example, the library is stored in the storage unit 55. The processing unit 38 performs refractive index matching using the refractive indices of the materials in the library. The processing unit 38 also calculates pre-calculated values, which will be described later, and performs a series of processes for calculating the pre-calculated values.

[0165] In the measurement step (step S20), at least one of the scattering angle and the measurement wavelength is set as a measurement parameter, and the values ​​of the set measurement parameters are changed multiple times to measure the scattering intensity of the scattered light emitted from the dispersion liquid by the measurement light. In the measurement step (step S20), for example, the time fluctuation of the scattering intensity and the scattering angle dependence of the time average value of the scattering intensity are measured. In the step (step S22) of obtaining experimental data, for example, an autocorrelation function for the time fluctuation of the scattering intensity is obtained based on the measurements in the measurement step (step S20). Furthermore, the scattering angle dependence of the time average value of the scattering intensity or the time average value of the wavelength-dependent scattering intensity is obtained. This allows, for example, the scattering intensity for each scattering angle to be obtained as shown in FIG. 14.

[0166] Here, Figure 14 is a graph showing calculated values ​​of scattering angle and scattering intensity for each refractive index of particles of the same particle size, and shows the calculated scattering intensity profile. In Figure 14, reference numeral 80 is a profile showing the relationship between scattering angle and scattering angle when the refractive index is 1.48. Reference numeral 81 is a profile showing the relationship between scattering angle and scattering angle when the refractive index is 1.59. Reference numeral 82 is a profile showing the relationship between scattering angle and scattering angle when the refractive index is 2.2. As shown in Figure 14, even if the particles have the same particle size, if the refractive index is different, the profile of scattering intensity relative to the scattering angle will be different.

[0167] The step of obtaining pre-calculated values ​​(step S24) obtains calculated values ​​of scattering intensity, for example, using a theoretical formula defining the relationship between refractive index, particle size, and scattering intensity or a simulation based on the theory of electromagnetic wave behavior. Furthermore, time-varying characteristic data of the scattering intensity of the measurement parameters calculated using a theoretical formula defining the relationship between refractive index, particle size, and scattering intensity, and time-averaged scattered electric field data or time-averaged scattered intensity data of the calculated measurement parameters are obtained. Alternatively, time-varying characteristic data of the scattering intensity of the measurement parameters calculated using a simulation based on the theory of electromagnetic wave behavior, and time-averaged scattered electric field data or time-averaged scattered intensity data of the calculated measurement parameters are obtained. The method of calculating the time-averaged scattered electric field data or time-averaged scattered intensity data in step S24 is similar to the method of calculating multiple time-averaged scattered electric field data or time-averaged scattered intensity data by the conversion unit 54 described above, and therefore detailed description thereof will be omitted. Furthermore, step S24 may also obtain actual measured values ​​of scattering intensity using known particles such as standard particles. The pre-calculated values ​​obtained in step S24 are used to identify the number of particle species, the refractive index for each particle species, and the number of particles, as described below.

[0168] In the optimization process (step S26), for example, the autocorrelation function and theoretical equation for scattering intensity are fitted to the autocorrelation function of the time fluctuation of scattering intensity and the time average value of scattering intensity obtained in step S22. In step S26, initial values ​​are set for the number of particle species, the refractive index of each particle species, and the number of particles contained in the dispersion, and then updated to minimize the evaluation value to identify the final combination of the number of particle species, the refractive index of each particle species, and the number of particles. The initial values ​​are set by generating random variables. Next, after obtaining the optimization results (step S28), the refractive index of each particle species for the particle whose combination of the number of multiple particle species, the refractive index of each particle, and the particle size distribution of each particle in the dispersion is identified by fitting is matched with the refractive index of the material in the library (step S30). This identifies the material for each particle species of the multiple types of particles contained in the dispersion, and the material for each particle species of the multiple types of particles contained in the dispersion is obtained as an analysis result (step S32). For refractive index matching (step S30), for example, a material that minimizes the square of the refractive index difference is selected. The refractive indexes of the materials are prepared in advance as a library (step S34). The light scattering measurement method, including fitting, will be described in more detail below.

[0169] First, for example, laser light of a specific wavelength is incident on the dispersion liquid Lq from the light source 22 of the light measurement device 20b shown in FIG. 9 . The scattered light from the incident light is detected at different scattering angles by the second detection unit 52b. This allows signals (scattering intensity) of the scattered light from the dispersion liquid Lq at different scattering angles to be obtained. The scattering angle values ​​are two or more. The above steps constitute the measurement step, which corresponds to the above-mentioned step S20 (see FIG. 13 ). Next, the conversion unit 54 calculates, using a known method, for example, an autocorrelation function or a power spectrum as time-varying characteristic data of the scattering intensity from the time dependence of the scattering intensity of the dispersion liquid Lq obtained in the measurement step. In this way, time-varying characteristic data of the scattering intensity is obtained for each scattering angle. Multiple time-varying characteristic data are obtained. Next, the conversion unit 54 acquires time-averaged scattering electric field data or time-averaged scattering intensity data from the scattered light signal from the dispersion liquid obtained in the measurement step. The time-averaged scattering electric field data or time-averaged scattering intensity data of the dispersion liquid can be obtained, for example, by calculating the time-averaged value of scattering intensity from the signal of scattered light from the dispersion liquid for each scattering angle. This results in scattering intensity data for each scattering angle as shown in Figure 14. The process of acquiring the time-variation characteristic data of the scattering intensity of the dispersion liquid and the time-averaged scattering electric field data or time-averaged scattering intensity data of the dispersion liquid is the second conversion process, which corresponds to step S22 described above.

[0170] Next, in the processing unit 38, the time variation characteristic data of the scattering intensity at two or more scattering angles and the multiple time-averaged scattering electric field data or time-averaged scattering intensity data are fitted using a theoretical formula that defines the relationship between refractive index, particle size, and scattering intensity, or a simulation based on the theory of electromagnetic wave behavior. The above fitting identifies the number of multiple types of particle species in the dispersion, the refractive index of the particles, and the particle size distribution of the particles. This corresponds to the above steps S26 and S28. As mentioned above, the dispersion contains at least one type of particle. Also, as mentioned above, the first-order autocorrelation function is g （１） (τ) = exp(-Dq ２The relationship between the diffusion coefficient obtained from the autocorrelation function and the particle size is determined by the Stokes-Einstein formula (see formula (1)) used in ordinary dynamic light scattering methods.

[0171] When particles have a particle size distribution, the first-order autocorrelation function is expressed by the following formula (21). The scattering intensity is expressed by the following formula (22). The following formulas (21) and (22) are theoretical formulas. I in formulas (21) and (22) θ total is a calculated value, and corresponds to the time-averaged scattered electric field data or the time-averaged scattered intensity data. Note that the first-order autocorrelation function in equation (21) is a value obtained by measurement, and if the particle has the property of absorbing light, the particle size will change depending on the intensity of the incident light, as described above. On the other hand, equation (22) is a theoretical value, and the particle size in equation (22) is a particle size that is not affected by the intensity of the incident light. For this reason, the particle size in equation (21) and the particle size in equation (22) do not match. Therefore, the previously determined measured particle size, i.e., the particle size d ０ (21) is used to make the particle size in equation (22) coincide with the particle size in equation (21). In this state, with particle size as a fitting parameter and the number of particles as a variable, a plurality of pieces of time-varying characteristic data of the scattered electric field or scattering intensity and a plurality of pieces of time-averaged scattered electric field data or time-averaged scattered intensity data are fitted to a theoretical formula that defines the relationship between particle size and scattering intensity, thereby obtaining the particle size distribution and the relative complex refractive index m of the particles.

[0172]

[0173]

[0174] In addition, in the formula (21), g （１） indicates a first-order autocorrelation function. The first-order autocorrelation function in equation (21) is the first-order autocorrelation function for each scattering angle. The scattering intensity in equation (22) is the scattering intensity for each scattering angle. Therefore, equations (21) and (22) are obtained for each scattering angle to be measured. In equations (21) and (22), Is θ total indicates the total scattering intensity. d' and d ０ indicates particle size. d' and d ０The subscripts 0 to M in indicate the ordinal numbers of the bins in the particle histogram. N indicates the number of particles. D indicates the diffusion coefficient. The subscript d' for the diffusion coefficient D indicates that it depends on the particle size d'. q indicates the scattering vector. τ indicates the time lag of the first-order autocorrelation function. θ indicates the scattering angle. Is indicates the scattering intensity. The subscript d' for the scattering intensity Is indicates that it depends on the particle size d'. The subscript θ for the scattering intensity Is indicates that it depends on the scattering angle θ. Note that the bins in the histogram are the data intervals in the histogram, and are indicated by bars in the histogram. N ｄ´ Is ｄ´, θ / Is θ total The part indicates the ratio of the scattering intensity caused by all single particles belonging to the bin of particle size d' to the total scattering intensity. The scattering intensity for a particle with particle size d' and relative complex refractive index m is given by the following formula according to the Mie scattering theory. The following formula is a theoretical formula that defines the relationship between refractive index, particle size, and scattering intensity.

[0175]

[0176] Here, P ｌ is a function obtained by partially differentiating the Legendre polynomial with respect to θ, and the subscript l (l) represents the degree of the Legendre polynomial. λ indicates the wavelength in the solvent. d is the particle diameter, r is the distance from the particle, and m is the relative complex refractive index of the particle to the medium. Note that the refractive index of the solvent is expressed as n ０ and the refractive index of the particle is n, m = n / n ０ Furthermore, the coefficient A ｌ (m, d') and B ｌ (m, d') is given by the following formula: In the formula, the ' attached to ψ and ζ is a differential with respect to a factor in each function, and has a different meaning from the ' attached to d.

[0177]

[0178]

[0179] Here, x is expressed by the following formula: １ (ρ) and ζ １ (ρ) is expressed by the following formula, in which J is a Bessel function and ζ is a Hankel function.

[0180]

[0181]

[0182]

[0183] When the number of particle species is two, the number of terms becomes two, and the above equations (21) and (22) become the following equations (23) and (24). When the number of particle species is three or more, the same applies as when the number of particle species is two.

[0184]

[0185]

[0186] (Second Example of Fitting) Hereinafter, fitting for identifying the number of particle species of particles contained in a dispersion liquid and the material of each particle species will be described. （２） (τ) is measured for each scattering angle, preferably at two or more angles, but may be at one angle. The number of scattering angles to be measured is determined appropriately depending on the number of variables to be determined or the number of time-averaged scattered electric field data or time-averaged scattered intensity data of the measurement parameters.

[0187] In fitting, for the first-order autocorrelation function for each scattering angle, the number of particle species, the refractive index for each particle species, and the number of particles are used as variables to set the initial particle number in equations (21) and (23), or similar equations for particle species 3 and above. The calculated value of the first-order autocorrelation function of equation (21) is obtained based on the set initial particle number. The second-order autocorrelation function g is calculated from the calculated value of the first-order autocorrelation function. （２） (τ) = 1 + βg | g （１） (τ) | ２ The calculated value of is obtained. Note that βg is an instrument constant. For each scattering angle, the difference between the measured value of the second-order autocorrelation function and the calculated value of the second-order autocorrelation function is obtained. Note that the difference between the measured value of the second-order autocorrelation function and the calculated value of the second-order autocorrelation function is called the difference of the second-order autocorrelation function. The difference of the second-order autocorrelation function is obtained for each scattering angle. The calculated value of the second-order autocorrelation function for each scattering angle corresponds to the time variation characteristic data of the scattering intensity of the measurement parameter calculated by the theoretical formula.

[0188] Total scattering intensity Is total is actually measured for each scattering angle. In the equations (22), (24) or similar equations for particle types 3 or more, the total scattering intensity Is θ total For each scattering angle, the measured total scattering intensity Is as shown in FIG. total and the total scattering intensity I θ total The difference between the calculated value and the measured total scattering intensity Is at any scattering angle is calculated. total and the total scattering intensity I θ total The difference between the calculated value and the total scattering intensity at the scattering angle Is total The difference between the total scattering intensity Is total For the scattering angle, the total scattering intensity Is total The difference between the total scattered intensity I θ total The calculated value corresponds to the time-averaged scattered electric field data or the time-averaged scattered intensity data of the measurement parameter calculated by the theoretical formula.

[0189] In fitting, the difference between the second-order autocorrelation functions obtained for each scattering angle and the difference between the total scattering intensities at the scattering angles are used to determine the final number of particle species, the refractive index for each particle species, and the number of particles. For example, an evaluation value is used that is obtained by adding, for all scattering angles, the squared value of the difference between the second-order autocorrelation functions obtained for each scattering angle and the squared value of the difference between the total scattering intensities at the scattering angles. The combination of the number of particle species, the refractive index for each particle species, and the number of particles that minimizes the evaluation value is determined to be the final combination of the number of particle species, the refractive index for each particle species, and the number of particles. Since the particle species and the number of particles are obtained, a particle size distribution for each particle species can be obtained.

[0190] In fitting, the number of particle species, the relative complex refractive index m for each particle species, and the number of particles are repeatedly updated using equations (23) and (24), etc., depending on the number of particle species, so as to minimize the evaluation value, to obtain the final number of particles and the relative complex refractive index m. This corresponds to step S26 described above. In fitting, when the number of particle species, the relative complex refractive index m for each particle species, and the number of particles are repeatedly updated so as to minimize the evaluation value, the number of particle species, the relative complex refractive index m for each particle species, and the number of particles are updated using, for example, a genetic algorithm. This allows for more reliable updating of the number of particle species, the relative complex refractive index m for each particle species, and the number of particles.

[0191] In fitting, the values ​​of the particle number and the relative complex refractive index m are updated in equations (23) and (24) according to the number of particle species as described above, reflecting the equation showing the relative complex refractive index m, and fitting is performed between the measured value and the calculated value to obtain the final particle number and relative complex refractive index m. The refractive index is fitted through the equation showing the relative complex refractive index m described above. A particle histogram can be obtained by obtaining the particle number for each particle size of all particle species. That is, for particles, N ｄ´ A ... for all d' = d ０ ~d Ｍ By obtaining the above, the particle size distribution of all particle species can be obtained. The above steps are the step (step S28) of determining the combination of the number of particle species, the relative complex refractive index m for each particle species, and the particle size distribution. Note that the evaluation values ​​used in fitting are not limited to those described above.

[0192] The finally obtained refractive index for each particle type is matched with the refractive index of the library material (step S30), and the material for each particle type is obtained as an analysis result (step S32). For example, matching is performed by selecting the material that minimizes the square of the refractive index difference between the obtained refractive index of the particle and the refractive index of the library material. The above process is a process for identifying the material for each particle type of unknown particles contained in the dispersion. Note that the evaluation values ​​used in fitting are not limited to those described above.

[0193] The first-order autocorrelation function in equation (23) is a value obtained by measurement, and if the particle has the property of absorbing light, the particle size will change depending on the intensity of the incident light as described above. On the other hand, equation (24) is a theoretical value, and the particle size in equation (24) is a particle size that is not affected by the intensity of the incident light. Therefore, the particle size in equation (23) does not match the particle size in equation (24). Therefore, in equations (23) and (24), the previously determined measured particle size, i.e., the particle size d that is not dependent on the intensity of the incident light, is also used. ０ (23) and the particle size in equation (24) are made to coincide with each other using the formula (24). In this state, the particle size is used as a fitting parameter and the number of particles is used as a variable, and fitting is performed to a theoretical formula that defines the relationship between particle size and scattering intensity to obtain the particle size distribution and the relative complex refractive index m of the particles.

[0194] In addition to the scattering angle, measurements at different wavelengths can also be added to determine the wavelength dependence of the refractive index. That is, two or more measurement wavelengths can be used to measure the scattered light intensity, obtain data on the scattered light, and determine the number of particle species, the refractive index for each particle species, and the particle size distribution. In this case, the scattering angle can be one angle, or multiple angles, two or more angles. By changing the measurement wavelength, the wavelength dependence of the refractive index can be obtained. This wavelength dependence of the refractive index is also called refractive index dispersion. When changing the measurement wavelength as a measurement parameter, the number of measurement wavelengths is not limited to two, but can be three or four, as long as there are multiple measurement wavelengths.

[0195] Here, the relationship between scattering intensity and measurement wavelength is shown in Figures 15 and 16. Figure 15 shows the scattering intensity calculated for two types of particles with different refractive indices at a measurement wavelength of 488 nm. As shown in Figure 15, the scattering intensity profile 84 of the first particle is different from the scattering intensity profile 85 of the second particle. Figure 16 shows the scattering intensity calculated for two types of particles at a measurement wavelength of 632.8 nm. As shown in Figure 16, the scattering intensity profile 86 of the first particle is different from the scattering intensity profile 87 of the second particle. As shown in Figures 15 and 16, the scattering intensity at the measurement wavelength differs depending on the refractive index. This can be used to identify the particle species. For example, time-averaged scattering electric field data or time-averaged scattering intensity data of a dispersion liquid can be obtained by calculating the time-averaged value of the scattering intensity of the dispersion liquid for each laser light wavelength.

[0196] The method for optimizing fitting is not limited to the above, and for example, Bayesian optimization can be used for fitting. As described above, a second-order autocorrelation function was used to determine the number of particle species, the refractive index for each particle species, and the number of particles contained in the dispersion liquid. However, this is not limited to this, and a power spectrum can also be used instead of the second-order autocorrelation function. Furthermore, when measuring a first-order autocorrelation function by heterodyne detection, a first-order autocorrelation function may also be used. In addition to the theoretical formula, the fitting can also use time-varying characteristic data of the scattering intensity of the measurement parameter calculated by simulation, and time-averaged scattering electric field data or time-averaged scattering intensity data of the calculated measurement parameter.

[0197] (Sixth Example of Optical Measurement Method) Figure 17 is a flowchart showing a sixth example of an optical measurement method according to an embodiment of the present invention. In the sixth example of the optical measurement method, detailed descriptions of the same steps as those in the fifth example of the optical measurement method shown in Figure 13 will be omitted. The sixth example of the optical measurement method differs from the fifth example of the optical measurement method in that it evaluates optimization and uses a library of refractive indexes for pre-calculated values, but is otherwise similar to the fifth example of the optical measurement method. Note that in the sixth example of the optical measurement method, the measured particle size described above is obtained before the measurement step (step S10) of Figure 10.

[0198] The sixth example of the optical measurement method, like the fifth example of the optical measurement method, includes a measurement step (step S40), a step of obtaining experimental data (step S42), a step of optimizing (step S44), a step of obtaining optimization results (step S46), and a step of obtaining analysis results (step S48). It also includes a step of preparing a library (step S50), a step of using the library to identify the number of particle species and candidate materials for each particle species (step S52), and a step of obtaining pre-calculated values ​​(step S54). The step of obtaining analysis results (step S48) identifies the material for each particle species of particles contained in the dispersion.

[0199] The measurement step (step S40), the experimental data acquisition step (step S42), and the optimization step (step S44) are the same as the measurement step (step S20), the experimental data acquisition step (step S22), and the optimization step (step S26) of the fifth example of the optical measurement method, and therefore detailed descriptions thereof will be omitted. In the sixth example of the optical measurement method, a prepared library (step S50) is used to select the number of particle species and candidate materials for each particle species (step S52). Pre-calculated values ​​are obtained based on the selected number of particle species and candidate materials for each particle species (step S54).

[0200] In steps S50, S52, and S54, refractive index data of candidate materials is extracted as initial values ​​from the library by the number of candidate particle species (step S50). Also, initial values ​​of particle size distribution of the candidate particle species are prepared (step S52). Using the refractive index data of the candidate particle species and the initial values ​​of the size distribution of the candidate particle species, scattering intensity and a second-order autocorrelation function are calculated (step S54). As pre-calculated values, the number of particle species and candidate materials for each particle species are set, and calculated values ​​of scattering intensity and second-order autocorrelation function are obtained. Meanwhile, in step S42, measured values ​​of scattering intensity for each scattering angle are obtained. Also, the second-order autocorrelation function g （２） (τ) is measured for each scattering angle.

[0201] In the optimization step (step S44), the measured values ​​in step S42 are compared with the pre-calculated values ​​in step S54, and fitting is performed. In this case, for example, as in the third example of fitting, the difference between the second-order autocorrelation functions obtained for each scattering angle and the difference between the total scattering intensities at the scattering angles are used. For example, an evaluation value obtained by adding, for all scattering angles, the squared value of the difference between the second-order autocorrelation functions obtained for each scattering angle and the squared value of the difference between the total scattering intensities at the scattering angles is used. Refractive index data for candidate particle species is extracted from the library so as to minimize the evaluation value (step S50), a particle size distribution for the candidate particle species is set (step S52), and the scattering intensity and second-order autocorrelation function for the candidate particle species are calculated (step S54). The combination of the number of particles, the candidate material, and the number of particle species of the candidate material that minimizes the evaluation value is obtained. This is considered as the optimal solution, and the final combination of the number of particle species, the refractive index for each particle species, and the particle size distribution contained in the dispersion is obtained (step S46). As a result of this analysis, the number of particle species contained in the dispersion liquid and the material of each particle species can be identified (step S48).

[0202] Note that, for example, a genetic algorithm is used to select the number of particle species and candidate materials for each particle species (step S52) to obtain pre-calculated values ​​(step S54). Furthermore, for example, a genetic algorithm is used to optimize the particle size distribution (step S44), i.e., for fitting. By using a genetic algorithm in the above process, the reliability of the selection of the number of particle species and candidate materials for each particle species (step S52) increases. Furthermore, the reliability of the optimization of the particle size distribution (step S44) also increases. Note that the number of particle species contained in the dispersion may be determined in advance. That is, the number of particle species may be set in advance as a convergence condition. In this case, in step S50, refractive index data of candidate particle species is extracted for the predetermined number of particle species (step S50), candidate materials for each particle species are selected (step S52), and pre-calculation is performed (step S54).

[0203] (Third Example of Fitting) The third example of fitting differs from the second example of fitting in that, as described above, the number of particle species and candidate materials for each particle species are selected from a library of refractive indices of materials, and their refractive indices are used. In the third example of fitting, in order to determine the number of particles, the difference between the second-order autocorrelation functions obtained for each scattering angle and the difference between the total scattering intensities at the scattering angles are used. For example, an evaluation value obtained by adding, for all scattering angles, the squared value of the difference between the second-order autocorrelation functions obtained for each scattering angle and the squared value of the difference between the total scattering intensities at the scattering angles is used. The number of particles that minimizes the evaluation value is determined.

[0204] In the fitting, the number of particle species, the relative complex refractive index m for each particle species, and the number of particles are repeatedly updated in equations (23) and (24), etc., corresponding to the number of particle species, so as to minimize the evaluation value, thereby obtaining the final number of particles and the relative complex refractive index m. This corresponds to step S26 described above. In the fitting, when the number of particle species, the relative complex refractive index m for each particle species, and the number of particles are repeatedly updated in order to minimize the evaluation value, the number of particle species, the relative complex refractive index m for each particle species, and the number of particles are updated using, for example, a genetic algorithm. This allows for more reliable updating of the number of particle species, the relative complex refractive index m for each particle species, and the number of particles. In the fitting, the values ​​of the number of particles and the relative complex refractive index m are updated in equations (23) and (24), etc., corresponding to the number of particle species, as described above, reflecting the equation indicating the relative complex refractive index m, and fitting is performed between the measured values ​​and the calculated values, thereby obtaining the final number of particles and the relative complex refractive index m. The refractive index is fitted through the equation indicating the relative complex refractive index m described above. In the third fitting example, the particle size in equation (23) and the particle size in equation (24) do not match. Therefore, in equations (23) and (24), the particle size d ０ (23) is used to make the particle size in equation (24) coincide with the particle size in equation (24). In this state, as described above, a plurality of pieces of time-varying characteristic data of the scattered electric field or scattering intensity and a plurality of pieces of time-averaged scattered electric field data or time-averaged scattered intensity data are fitted to a theoretical formula that defines the relationship between particle size and scattering intensity, thereby obtaining the particle size distribution and the relative complex refractive index m of the particles.

[0205] As described above, the number of particles that minimizes the evaluation value, the candidate material for the number of particles that minimizes the evaluation value, and the number of particle species of the candidate material are determined as the optimal solution, and the final combination of the number of particle species, the refractive index for each particle species, and the particle size distribution is obtained (step S46). As a result, the number of particle species and the material for each particle species contained in the dispersion can be identified as the analysis result (step S48). The above steps are the process of identifying the material for each particle species contained in the dispersion. Note that the evaluation values ​​used in the fitting in the third example of fitting are not limited to those described above. Note that in the third example of fitting, as in the second example of fitting, the wavelength dependence of the refractive index can be obtained by changing the measurement wavelength and performing measurements at two or more measurement wavelengths as described above. When changing the measurement wavelength, the number of measurement wavelengths is not limited to two; as long as there are multiple measurement wavelengths, three or four measurement wavelengths are also possible.

[0206] As described above, incident light is introduced into a dispersion containing particles at varying intensities, and the resulting scattered light is measured multiple times to obtain multiple scattering intensities and multiple scattering intensity data. The multiple scattering intensity data are then converted into multiple time-varying characteristic data for the scattered electric field or scattering intensity. However, this is not limiting. For example, the scattered light obtained by introducing incident light at varying intensities can be measured multiple times to obtain multiple time-varying characteristic data for the scattered electric field or scattering intensity from the multiple scattered lights. In this case, for example, by using an autocorrelator (correlator) to detect the scattered light in the light measurement device, the scattered light signals measured multiple times can be converted into multiple time-varying characteristic data for the scattered electric field or scattering intensity without obtaining scattering intensity data in the measurement unit, thereby obtaining, for example, multiple autocorrelation functions. In this case, the measurement step simply involves measuring the scattered light multiple times. The multiple autocorrelation functions obtained by converting the scattered light signals measured multiple times are used to measure the particle size and particle size distribution, as described above.

[0207] Furthermore, the position of the autocorrelator in the light measurement device is not particularly limited as long as it can detect scattered light and obtain a scattered light signal. The autocorrelator is not particularly limited as long as it can obtain an autocorrelation function from scattered light without obtaining scattering intensity data as described above, and a commercially available autocorrelator can be used as appropriate.

[0208] The present invention is basically configured as described above. Although the light measurement method and light measurement device of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various improvements and modifications may be made without departing from the spirit and scope of the present invention.

[0209] 10a, 10b, 10c, 10d Autocorrelation functions 10e, 10f, 10g Autocorrelation functions 12, 13, 14, 15, 16, 17, 18 Straight lines 20, 20a, 20b Light measurement device 22 Light source 23a, 23b, 23c, 23d, 23e, 23f Optical fibers 23g, 23h, 23i, 23j, 23k, 23m Optical fibers 24 First coupler 24a, 24b, 34a, 34b, 45a, 45b End face 26 Circulator 28 Collimating lens 30 Objective lens 32 Sample cell 34 Second coupler 36 Detector 37 Measuring unit 38 Processing unit 38a Conversion unit 38b Particle size calculation unit 38c Particle size distribution calculation unit 38d Calculation unit 40 First collimating lens 42 Modulator 43 Second collimating lens 44 Phase modulation unit 45 Third coupler 46 Measurement unit 50 Low coherence interferometer 52 Detection unit 52a First detection unit 52b Second detection unit 54 Conversion unit 55 Memory unit 61a, 61b, 61c, 61d Beam splitter 61e Transmission / reflection surface 62 Reflector 62a Reflection surface 63a Dispersion compensation adjustment unit 63b Objective lens 64a, 64b ND filter 65 Objective lens 66 Polarization adjustment unit 67 Spectral adjustment unit 68 Polarization control unit 70 Mirror 72 Diffraction grating 73, 74 Photodetector 84, 85, 86, 87 Profile Ld Scattered light Lq Dispersion liquid Lr Reference light Ls Incident light θb Scattering angle

Claims

1. A method for optically measuring a dispersion containing particles, A measurement step of measuring the scattered light obtained by incident light with varying intensity into the dispersion, A conversion step is provided to convert the scattered light signals measured multiple times in the measurement step into multiple time variation characteristic data of scattered electric fields or scattering intensities, A light measurement method comprising: a particle size calculation step of determining the particle size using the time variation characteristic data of the plurality of scattering electric fields or scattering intensities obtained by the conversion step.

2. The optical measurement method according to claim 1, wherein the particle size calculation step involves analyzing the time variation characteristic data of a plurality of scattering electric fields or scattering intensities, assuming that the dependence of the diffusion coefficient of the particles on the intensity of the incident light is linear, to determine the particle size, and thereby determining the relationship between the particle size or the diffusion coefficient of the particles and the intensity of the incident light.

3. Furthermore, the process involves obtaining a second temperature after the particle, which is at a first temperature, has its temperature increased due to the absorption of the incident light. The optical measurement method according to claim 2, further comprising the step of determining the particle size at a second temperature using an equation that represents the diffusion coefficient when a temperature rise occurs, with respect to the particle size of the particle determined in the particle size calculation step.

4. A method for optically measuring a dispersion containing particles, A measurement step of measuring the scattered light obtained by incident light with varying intensity into the dispersion, A conversion step is provided to convert the scattered light signals measured multiple times in the measurement step into multiple time variation characteristic data of scattered electric fields or scattering intensities, A light measurement method comprising: a particle size distribution calculation step of determining the particle size distribution of the particles using the plurality of time variation characteristic data of scattering electric fields or scattering intensities obtained by the conversion step.

5. The particle size distribution calculation step includes a step of determining an index value representing the temperature dependence of the particle size using the time variation characteristic data of the plurality of scattering electric fields or scattering intensities, The optical measurement method according to claim 4, further comprising the step of correcting the particle size distribution of the particles obtained in the particle size distribution calculation step using the index value representing the temperature dependence of the particle size.

6. Furthermore, the process includes a step of obtaining a second temperature after the particle, which is at a first temperature, has its temperature increased due to the absorption of incident light. The optical measurement method according to claim 4, wherein the particle size distribution calculation step determines the particle size distribution of the particles by using the second temperature in addition to the diffusion coefficient obtained from the time variation characteristic data of the plurality of scattering electric fields or scattering intensities.

7. The optical measurement method according to claim 1 or 4, wherein the scattered light is scattered light obtained by incident light with at least one of the measurement parameters, the scattering angle and the measurement wavelength, changed.

8. The measurement step involves measuring the scattering intensity of the scattered light obtained by incident light with varying intensity into the dispersion multiple times to obtain multiple scattering intensity data. The optical measurement method according to claim 1 or 4, wherein the conversion step is a step of acquiring a plurality of time variation characteristic data of scattering electric fields or scattering intensities from the plurality of scattering intensity data obtained by the measurement step.

9. The aforementioned dispersion contains multiple types of particle species, The measurement process includes a conversion step that converts the multiple scattered light signals obtained by the measurement step into multiple time-averaged scattered electric field data or time-averaged scattered intensity data. The optical measurement method according to claim 7, further comprising a calculation step of calculating the particle size or particle size distribution for multiple types of particle species from the time-averaged scattering electric field data or the time-averaged scattering intensity data and the time variation characteristic data.

10. The measurement step is a step of obtaining multiple scattering intensity data by measuring the scattering intensity of the scattered light obtained by incident light with a changed intensity into the dispersion multiple times, and a step of obtaining multiple scattering intensity data by measuring the scattering intensity of the scattered light obtained by incident light with at least one value of the measurement parameters, the scattering angle and the measurement wavelength, multiple times. The optical measurement method according to claim 9, wherein the conversion step is a step of calculating a plurality of time variation characteristic data of a scattering electric field or scattering intensity from the plurality of scattering intensity data obtained by the measurement step.

11. The optical measurement method according to any one of claims 1 to 6, wherein the time variation characteristic data of the scattered electric field or scattering intensity is an autocorrelation function or a power spectrum.

12. A photometric device for a dispersion containing particles, A light source that incidents light on the dispersion with varying intensity, A measuring unit that measures scattered light obtained by incident light with a modified intensity into the dispersion, A conversion unit converts the scattered light signals measured multiple times by the measurement unit into multiple time-varying characteristic data of scattered electric fields or scattering intensities, An optical measuring device comprising: a particle size calculation unit that determines the particle size using the time variation characteristic data of the plurality of scattered electric fields or scattering intensities obtained by the conversion unit.

13. The optical measuring device according to claim 12, wherein the particle size calculation unit determines the particle size by analyzing the time variation characteristic data of the plurality of scattering electric fields or scattering intensities, assuming that the dependence of the diffusion coefficient of the particle on the intensity of the incident light is linear, and determining the relationship between the particle size or the diffusion coefficient of the particle and the intensity of the incident light.

14. The particle size calculation unit obtains the second temperature of the particles at the first temperature after the temperature has risen due to the absorption of the incident light, The optical measuring device according to claim 12, wherein the particle size at a second temperature is determined using an equation that represents the diffusion coefficient when a temperature rise occurs, with respect to the particle size of the particle determined by the particle size calculation unit.

15. A photometric device for a dispersion containing particles, A light source that incidents light on the dispersion with varying intensity, A measuring unit that measures scattered light obtained by incident light with a modified intensity into the dispersion, A conversion unit that converts multiple scattered light signals obtained by the measurement unit into multiple time-varying characteristic data of scattered electric fields or scattering intensities, An optical measuring device comprising: a particle size distribution calculation unit that calculates the particle size distribution of the particles using the time variation characteristic data of the plurality of scattered electric fields or scattering intensities obtained by the conversion unit.

16. The particle size distribution calculation unit uses the time variation characteristic data of the plurality of scattering electric fields or scattering intensities obtained by the conversion unit to determine an index value representing the temperature dependence of the particle size, The optical measuring device according to claim 15, wherein the particle size distribution of the particles is corrected using the index value representing the temperature dependence of the particle size.

17. The optical measuring device according to claim 15, wherein the particle size distribution calculation unit obtains a second temperature after the particle at a first temperature has risen in temperature due to the absorption of incident light, and uses the second temperature to determine the particle size distribution of the particle using the diffusion coefficient obtained from the time variation characteristic data of the plurality of scattering electric fields or scattering intensities.

18. The optical measuring device according to claim 12 or 15, wherein the scattered light is scattered light obtained by changing the value of at least one of the measurement parameters, the scattering angle and the measurement wavelength, when the light is incident.

19. The optical measuring device according to any one of claims 12 to 17, comprising a measuring unit for measuring the intensity of the incident light.

20. An optical measuring device according to any one of claims 12 to 17, comprising a low-coherence interferometer.

21. The measurement unit obtains multiple scattering intensity data by measuring the scattering intensity of the scattered light obtained by incident light with a modified intensity into the dispersion multiple times. The optical measuring apparatus according to any one of claims 12 to 17, wherein the conversion unit acquires a plurality of time variation characteristic data of scattering electric fields or scattering intensities from the plurality of scattering intensity data obtained by the measurement unit.

22. The aforementioned dispersion contains multiple types of particle species, The conversion unit converts the multiple scattered light signals obtained by the measurement unit into multiple time-averaged scattered electric field data or time-averaged scattered intensity data. The optical measuring device according to claim 18, wherein the particle size calculation unit calculates the particle size for each of several types of particle species from time-averaged scattering electric field data or time-averaged scattering intensity data and time variation characteristic data.

23. The aforementioned dispersion contains multiple types of particle species, The conversion unit converts the multiple scattered light signals obtained by the measurement unit into multiple time-averaged scattered electric field data or time-averaged scattered intensity data. The optical measuring device according to claim 18, wherein the particle size distribution calculation unit calculates the particle size distribution for each of several types of particle species from the time-averaged scattering electric field data or the time-averaged scattering intensity data and the time variation characteristic data.

24. The measurement unit obtains multiple scattering intensity data by measuring the scattering intensity of the scattered light obtained by incident light with varying intensity into the dispersion multiple times, and also obtains multiple scattering intensity data by measuring the scattering intensity of the scattered light obtained by incident light with at least one of the measurement parameters, the scattering angle and the measurement wavelength, multiple times. The optical measuring apparatus according to claim 22, wherein the conversion unit calculates a plurality of time variation characteristic data of scattering electric fields or scattering intensities from the plurality of scattering intensity data obtained by the measurement unit.

25. The optical measuring device according to any one of claims 12 to 17, wherein the time variation characteristic data of the scattered electric field or scattering intensity is an autocorrelation function or a power spectrum.