Particle measurement device and particle measurement method

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The particle measuring device addresses the challenge of machine calibration and size range limitations by using a normalized signal to relate particle size to interference patterns, achieving accurate and simplified measurements across a broader size range.

JP2025072790APending Publication Date: 2025-05-12HITACHI HIGH TECH CORP

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Patent Information

Application Number: JP2023183114
Authority / Receiving Office: JP · JP
Patent Type: Applications
Current Assignee / Owner
Filing Date: 2023-10-25
Publication Date: 2025-05-12

AI Technical Summary

Technical Problem

Existing particle measurement technologies face challenges in calibrating multiple devices to suppress machine differences and accurately measuring particle sizes across a wide size range, especially in nonlinear detection signals from the Rayleigh scattering region to the Mie scattering region.

Method used

The particle measuring device uses a normalized signal derived from the interference between signal light and reference light, employing a function to relate the normalized signal to the particle size, allowing for simplified calibration and measurement across a broader size range.

Benefits of technology

This approach enables the suppression of machine differences between devices, allowing for accurate particle size measurements in a wider size range, while simplifying the calibration process and reducing manufacturing costs.

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Abstract

To provide a technique that enables particle size measurement using nonlinear detection signals ranging from the Rayleigh scattering region to the Mie scattering region, and offers easy calibration for suppressing individual differences among multiple devices.SOLUTION: A particle measurement device of the present invention is configured to acquire a normalized signal S obtained by dividing the maximum value of an interference signal caused by interference between a signal light and reference light by a reference value, and measure the size of a particle using a function representing a relationship between S and (d-d0), where d represents the size of the particle and d0 represents the smallest measurable particle size.SELECTED DRAWING: Figure 2A

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Description

[Technical field]

[0001] The present invention relates to a technique for measuring the size of particles in a solvent using light. [Background technology]

[0002] In recent years, the focus of pharmaceutical development has been shifting from small molecule drugs to biopharmaceuticals. Biopharmaceuticals are polymeric and therefore prone to aggregation, which may cause toxicity. For example, the U.S. Food and Drug Administration and others are trying to strengthen regulations on aggregate concentration management. Therefore, a technology is needed to quantitatively measure the size distribution of desired density for aggregates in the submicron region of 0.1 to 1 um. Protein aggregates float in a solvent, and their position changes over time due to Brownian motion. In the following, this invention describes a technology for measuring the size and density of protein aggregates and standard particles such as polystyrene beads. These test objects are collectively referred to as "particles."

[0003] Patent Document 1 describes a technique for detecting particles using optical measurement. The document discloses "an optical measurement method for generating an optical spot by converging light and measuring an object having a size approximately three times or less than the size of the optical spot, the optical measurement method comprising a signal acquisition step of detecting reflected light reflected from the object by irradiating the object with the light while moving at least the focal position of the light in the optical axis direction, a step of acquiring correspondence data describing the correspondence between the intensity of the reflected light and the size of the object, and a size calculation step of acquiring the size of the object by consulting the correspondence data using the intensity of the reflected light" (Claim 1). The technology described in the document can achieve high-resolution measurement without pre-processing by causing the reflected light to interfere with a reference light to enhance the signal.

[0004] The following Patent Document 2 discloses a technology that eliminates the need for phase adjustment of a reference light by mirror scanning in time domain OCT (Optical Coherence Tomography) by physically scanning an objective lens and receiving the interference between signal light and interference light with four detectors with different phase conditions. Furthermore, based on the technology of Patent Document 1, a technology for speeding up scanning of a light spot is disclosed so as not to be affected by the movement of particles undergoing Brownian motion in a liquid.

[0005] Patent Document 3 discloses a technology for measuring tomographic images of a living body using a semiconductor laser as a light source, in which a high frequency is superimposed on a driving current to control the coherence length within a predetermined range, thereby reducing the effect of noise contained in the acquired tomographic images. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2017-102032 A [Patent Document 2] WO2020 / 144754 publication [Patent Document 3] JP 2015-049204 A Summary of the Invention [Problem to be solved by the invention]

[0007] The technology described in Patent Document 1 and Patent Document 2 based on it can obtain the size of a particle from the measured maximum detection signal by acquiring correspondence data between the particle size and the maximum detection signal obtained at the focal position in advance. Furthermore, the density of the particles can be obtained from the number of detected particles. On the other hand, when suppressing the machine difference between multiple devices of the same product type to manage the performance, it is inevitable that the characteristics of individual parts, such as the emission angle and current sensitivity of a semiconductor laser and the sensitivity of a photodetector, will vary. According to Patent Document 1 and Patent Document 2, it is necessary to acquire the above-mentioned correspondence data individually for multiple devices. This is a cumbersome task and ultimately leads to an increase in the manufacturing cost of the device.

[0008] Furthermore, the correspondence relationship data described in Patent Document 1 is a linear relationship as shown in Figure 17 of the same document. When such a linear relationship is used, it is not possible to handle nonlinear characteristic changes from the Rayleigh scattering region to the Mie scattering region.

[0009] The present invention has been made in consideration of the above problems, and aims to provide a technique that allows easy calibration to suppress differences between multiple devices and that can measure particle size using nonlinear detection signals that span from the Rayleigh scattering region to the Mie scattering region. [Means for solving the problem]

[0010] The particle measuring device of the present invention obtains a normalized signal S by dividing the maximum value of an interference signal generated by interference between a signal light and a reference light by a reference value, and measures the size of the particle using a function that describes the relationship between S and (d-d0), where d is the size of the particle and d0 is the lower measurement limit of the size of the particle. Effect of the Invention

[0011] According to the particle measuring device of the present invention, in a particle measuring device that measures the size of particles contained in a liquid sample, it is possible to suppress the machine-to-machine difference of the product, and to realize particle measurement over a wider size range than conventionally. Problems, configurations, and effects other than those described here will become clear from the description of the embodiments below. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a schematic diagram showing the relationship between focus deviation and detection signals in Patent Documents 1 and 2. [Figure 2A] 1 shows the results of a simulation in which the relationship between particle size and maximum detection signal was calculated using the interference detection optical system described in Patent Documents 1 and 2. [Figure 2B] The simulation results in Figure 2A are shown with background scattering added. [Figure 2C] The background scattering level is shown to be equal to the interference signal of a particle of size 0.10 μm. [Diagram 3] 4 is a flow chart illustrating a simplified apparatus calibration procedure provided by the present invention. [Figure 4] 6 is an experimental result showing the relationship between the objective lens output power and the detection signal when the particle measuring device of the present invention measures a reference sample. [Diagram 5] 1 is a flow chart showing a procedure for obtaining a normalized signal of an evaluation sample. [Figure 6A] The experimental results are shown in which each standard sample was measured with each device for three types of output power including the standard power, and the relationship between the size of the standard particle and the normalized signal was plotted. [Figure 6B] FIG. 6B is a magnified view of the experimental results of FIG. 6A. [Figure 7A] Among the results of applying the polynomial size conversion model of the present invention, the results of a model of degree 1 are shown. [Figure 7B] Among the results of applying the size conversion model using polynomials according to the present invention, the results of a model of degree 2 are shown. [Figure 7C]Among the results of applying the polynomial size conversion model of the present invention, the results of a model of degree 3 are shown. [Figure 7D] Among the results of applying the polynomial size conversion model of the present invention, the results of a model of degree 4 are shown. [Figure 7E] Among the results of applying the polynomial size conversion model of the present invention, the results of a model of degree 5 are shown. [Figure 7F] Among the results of applying the polynomial size conversion model of the present invention, the results of a model of degree 6 are shown. [Figure 8] 13 is an experimental result showing the relationship between the order and RMS error of the size conversion model using a polynomial according to the present invention. [Figure 9A] The results of applying the size conversion model using the exponential function of the present invention are shown in the first-order lag model. [Figure 9B] The results of applying the size conversion model using the exponential function of the present invention are shown in the second-order lag model. [Figure 9C] The results of applying the size conversion model using the exponential function of the present invention are shown in the Gaussian distribution model. [Figure 10] 1 is an experimental result showing the relationship between the exponential function-based size conversion model of the present invention and the RMS error of the converted particle size. [Figure 11A] 1 shows the RMS error of particle size measured by the conventional technique and the present invention. [Figure 11B] This shows a comparison result between the relative error of the measured size obtained by the size conversion model for 0.107 μm (the smallest size shown in FIG. 6A) in the conventional technology and the present invention. [Figure 12A] 13 is an experimental result showing the relationship between d0 / λ value and parameters of the size conversion model. [Figure 12B] This is a numerical table showing the appropriate range of d0 / λ values taking into consideration the case where the range of particle sizes to be measured is changed by selecting the numerical aperture of the objective lens based on experimental results. [Figure 13] 13 is a diagram showing an example of the configuration of a particle measuring device according to embodiment 7. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] <Background of the invention> FIG. 1 is a schematic diagram showing the relationship between defocus and detection signal in Patent Document 1 and Patent Document 2. If the optical axis direction of the objective lens is z, the light spot diameter of the particle to be measured at the z position is determined by the wavelength of the light source, the numerical aperture of the objective lens, and the amount of defocus. The amount of reflected light from the particle is approximated according to the area ratio of the light spot diameter and the particle, and the detection signal increases or decreases. The left side of FIG. 1 is a schematic diagram of a state in which the particle to be measured is defocused from the focal position of the objective lens. In this case, the size of the particle is relatively small compared to the light spot diameter, and the amount of reflected light received through the objective lens and the detection signal converted from the reflected light to an electrical signal are relatively small. On the other hand, the right side of FIG. 1 is a schematic diagram of a state in which the particle to be measured is at the focal position of the objective lens. In this case, the size of the particle is maximum compared to the light spot diameter, and the amount of reflected light received through the objective lens and the detection signal are maximum. Figure 17 of Patent Document 1 discloses that when the size (diameter) of the target particle is approximately three times or less the minimum light spot diameter at the focus, the particle size and the maximum detection signal obtained at the focus position are uniquely determined, and that by acquiring this correspondence data in advance, it is possible to determine the particle size from the measured maximum detection signal.

[0014] FIG. 2A shows the results of a simulation in which the relationship between particle size and maximum detection signal was calculated using the interference detection optical system described in Patent Document 1 and Patent Document 2. Here, the simulation was performed using a method that combines Mie scattering and Fraunhofer diffraction. The wavelength of the light source is 785 nm, the numerical aperture of the objective lens is 0.45, the refractive index of the particles is 1.58 corresponding to commercially available polystyrene beads, and the refractive index of the solvent is 1.333 corresponding to pure water. Assuming that the particle size is d, as can be seen in the figure, in the region of d<0.1 μm, the maximum detection signal corresponds to Rayleigh scattering and is proportional to the cube of d, and in the region of d>0.3 μm, the maximum detection signal corresponds to Mie scattering and is proportional to the first power of d. The linearity of the particle size and maximum detection signal in the region of d>0.3 μm is consistent with FIG. 17 of Patent Document 1.

[0015] In order to avoid misunderstandings about these particle size dependencies, we will add an explanation. In general, it is known that the energy intensity of scattered light in Rayleigh scattering is proportional to the sixth power of the particle size d. The magnitude of the electrical signal obtained by photoelectrically converting reflected light with a photodetector is also proportional to the sixth power of d. The optical systems described in Patent Document 1, Patent Document 2, and the present invention use homodyne interference, which causes the reflected light and reference light to interfere with each other and amplify the light. In this case, the "electric field amplitude" of the reflected light is converted into an electrical signal, not the "energy" of the reflected light, so the maximum detection signal is proportional to the third power of d. By using such an optical system, the change in the magnitude of the detection signal due to the particle size is gentler than in the method of photoelectrically converting the "energy" of the reflected light, and as a result, it is advantageous to widen the dynamic range of measurable particle sizes. When a semiconductor laser is used as the light source, it is possible to reduce laser noise caused mainly by return light by superimposing a high frequency on the driving current using the technology described in Patent Document 3.

[0016] When actually measuring a sample containing particles such as protein aggregates, the obtained interference signal contains components due to background scattering. The background scattering referred to in this invention is the sum of (factor 1) Rayleigh scattering from molecules such as protein molecules and surfactants in the sample, and (factor 2) stray light of the optical system including reflected light from the sample container and laser noise. If the magnitude of the interference signal from the particle to be measured is smaller than the background scattering, the size of the particle cannot be measured. Therefore, background scattering provides a lower limit for the measurement size of particles in the techniques described in Patent Documents 1 and 2, including this invention.

[0017] FIG. 2B shows the simulation results of FIG. 2A with background scattering added. Here, the case where the protein concentration in the sample is high at about 100 mg / mL, that is, the case where the background scattering is mainly determined by (factor 1), is shown. The background scattering level (magnitude of the interference signal) is assumed to be equal to the interference signal of a particle with a size of 0.25 μm. The lower limit of the measurement size for this sample is 0.25 μm, and as can be seen in the figure, the interference signal of measurable particles is mainly Mie scattering, so the relationship between particle size and interference signal can be considered linear. This shows the case where the linear relationship described in FIG. 17 of Patent Document 1 is appropriate.

[0018] Figure 2C shows the case where the background scattering level is equal to the interference signal of a particle with a size of 0.10 μm. This corresponds to the case where the concentration of protein molecules in the sample is low, or where a diluted sample is measured by diluting it by about 1000 times to investigate the aggregate size distribution of the sample shown in Figure 2B in detail. In this case, the background scattering is mainly determined by (factor 2). As can be seen in the figure, the interference signal of a measurable particle includes Rayleigh scattering in addition to Mie scattering, so the relationship between particle size and interference signal is nonlinear.

[0019] The lower limit of the particle size that can be measured by the particle measuring device of the present invention is determined by the magnitude of background scattering, which is determined by factors that depend on the sample (factor 1) and on the implementation of the device (factor 2). The magnitude of background scattering due to (factor 2) can be quantified by providing a lower limit of detection size that is independent of protein concentration, etc., and measuring, for example, a reference sample obtained by diluting a commercially available standard polystyrene bead suspension with pure water for clean room use. The magnitude of background scattering measured at this time is a value specific to the device. In addition, in a particle measuring device in which background scattering due to (factor 2) has been reduced by improving the implementation of the device, the relationship between particle size and interference signal becomes nonlinear, so a size conversion model that describes a new relationship between particle size and interference signal instead of the linear relationship described in Figure 17 of Patent Document 1 is required. In this case, if there is a size conversion model that describes the relationship between particle size and interference signal with sufficient accuracy for a reference sample with sufficiently small background scattering (no Rayleigh scattering of protein molecules), it is possible to accurately determine the particle size from the interference signal within the measurable size range, even for samples whose background scattering is mainly determined by (factor 1), as shown in Figures 2B and 2C.

[0020] In light of the problem to be solved by the present invention, it should be noted that, hereinafter, unless otherwise specified, background scattering refers to background scattering measured by a reference sample, i.e., background scattering due to (factor 2).

[0021] In conventional techniques such as Patent Documents 1 and 2, the relationship between particle size and detection signal is assumed to be linear. In contrast, the present invention detects a region ranging from Mie scattering to Rayleigh scattering as shown in FIG. 2A. Therefore, the relationship between particle size and detection signal is nonlinear with the boundary being near d=0.2 to 0.3 μm. The present invention provides a technique that can accurately detect particle size even in such a nonlinear correspondence relationship between particle size and detection signal.

[0022] In the following description of the present invention, the explanation will be made in a unified coordinate system in which the optical axis direction is the z-axis. For the sake of simplicity, the maximum detection signal obtained when the particle size is at the focal position of the objective lens will be simply referred to as the detection signal, and the signal obtained by suppressing the instrumental difference will be referred to as the normalized signal.

[0023] <First embodiment: Regarding standardized signals> Here, we describe a normalized signal that suppresses the differences between multiple devices. The normalized signal S is defined as follows: s is the detection signal.

[0024]

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[0025] s0 is a reference signal that represents the detection sensitivity of the device, and is defined as follows: α is a specific sensitivity coefficient that represents the light utilization efficiency of the optical system and the characteristics of the photodetector, η is a correction coefficient due to the light emission power of the light source and temperature conditions, r is the Fresnel amplitude reflectance of the particle to be measured, and R0 is the Fresnel amplitude reflectance of the reference particle used when calibrating the device. s0 can be calculated arithmetically from the refractive indexes of the particle and medium using r and R0. In Equations 3 and 4, n o is the refractive index of the particle to be measured, n s is the refractive index of the particle to be measured, N o is the refractive index of the particles in the reference sample, N s is the refractive index of the solvent of the reference sample.

[0026]

number

[0027]

number

[0028]

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[0029] 3 is a flow chart showing the simplified calibration procedure of the device provided by the present invention. In the sensitivity calibration procedure to suppress the difference between multiple devices, the detection signal is measured using a reference sample. Specifically, the following steps can be performed.

[0030] In step S301, a reference sample is prepared. For example, a commercially available standard polystyrene bead suspension is diluted with pure water for clean room use to obtain a particle density of 10 7 The suspension can be adjusted to about 1000 particles / mL. The particle size is, for example, 1 μm. To ensure accuracy, it is desirable to measure the size of the particles contained in the suspension in advance using a scanning electron microscope. In this case, N o = 1.58, N s R0 can be calculated using a known refractive index, such as r = 1.333. Since the measurement target is a reference sample, r = R0.

[0031] In step S302, the device to be calibrated is set to standard conditions. The light source is made to emit light at a predetermined standard light emission power, such as 1 mW, and the environmental temperature is kept at a predetermined standard environmental temperature, such as 25° C. The correction coefficient at this time can be defined as η=1.

[0032] In step S303, a reference sample is measured using an apparatus set under standard conditions.

[0033] In step S304, the measured detection signal s indicates the inherent sensitivity coefficient of the light utilization efficiency of the optical system of the device and the photoelectric conversion characteristics of the detector. When the particle size contained in the reference sample is φ, α=s / φ is held as the magnitude of the detection signal per 1 μm. α is a constant inherent to the device and is saved in a device-dependent parameter file or the like for use.

[0034] Figure 4 shows the experimental results showing the relationship between the objective lens output power and the detection signal when a reference sample is measured by the particle measuring device of the present invention described later. As can be seen from the figure, there is a proportional relationship between the objective lens output power and the detection signal. This shows that characteristics based on the basic equation of optical interference have been obtained. Therefore, the correction coefficient η due to the light source emission power and temperature conditions in equation 2 can be written as follows:

[0035]

number

[0036] P0 is the output power under standard conditions, P is the output power during measurement, T is the temperature, η T (T) is the temperature correction coefficient that depends on the change in the emission spectrum of the semiconductor laser depending on the temperature. In the device used, the sensitivity change is about 0.5% per 1°C at room temperature of 25°C. η T (T) can be considered as being determined according to the quantum well structure of the semiconductor laser used as the light source. Therefore, it can be treated as a population-specific characteristic determined by the model number or lot number of the selected semiconductor laser component, rather than being device-specific.

[0037] Fig. 5 is a flow chart showing the procedure for obtaining a normalized signal of an evaluation sample. The procedure for obtaining a normalized signal of the present invention for an evaluation sample such as a protein aggregate of a biopharmaceutical prepared by a user will be described with reference to Fig. 5. This flow chart can be implemented, for example, by a controller or computer attached to the measurement device.

[0038] In step S501, the correction coefficient η is calculated according to Equation 5 from the output power P specified by the user and the output value T of the temperature monitor mounted near the semiconductor laser, which is the light source. At this time, if the difference between the refractive index of the particle to be measured and the refractive index of the solvent is large, the detection signal will be large, so it is better to reduce the output power of the objective lens in consideration of the size measurement dynamic range and resolution. Conversely, if the difference in refractive index is small, it is preferable to set the output power to a large value. In an actual measurement device, the measurement device determines the appropriate output power setting value for representative measurement targets, such as protein aggregates in biopharmaceuticals, commercially available antibodies, virus vectors, and coronavirus vaccines, and the user can select the conditions appropriately according to the measurement target, thereby improving convenience.

[0039] In step S502, the Fresnel amplitude reflectance of the particle to be measured is calculated according to Equation 3 from the refractive indexes of the particle and medium contained in the evaluation sample.

[0040] In step S503, the reference signal s0 is calculated according to Equation 2.

[0041] In step S504, the light source and various motorized stages within the apparatus are appropriately controlled to prepare for measurement.

[0042] In step S505, according to the method described in Patent Document 2 or the method described later, the detection signals obtained while scanning the light spot within the evaluation sample are acquired to obtain three-dimensional image data, and individual particles are identified based on this, and then the maximum detection signal s at the focus of each individual particle is obtained.

[0043] In step S506, the normalized signal S of each particle is calculated according to Equation 1.

[0044] <First embodiment: Summary> The obtained normalized signal S is in accordance with the above-mentioned sensitivity coefficient α, and can be said to directly reflect the relationship shown in the simplified form in FIG. 17 of Patent Document 1, that the detection signal is proportional to the particle size. According to the technology disclosed in Patent Document 1, in order to obtain the normalized signal S, it is necessary to obtain the above-mentioned correspondence relationship data while changing the output power for various reference particle sizes individually for multiple devices. In contrast, according to the present embodiment, this calibration process can be realized in a single measurement process for a reference sample under the above-mentioned standard device conditions, so that the process can be significantly simplified.

[0045] <Embodiment 2: Results of measurement experiments of normalized signals using multiple devices> In order to demonstrate that the nonlinear size conversion model provided by the present invention can be applied to multiple devices, four devices were prepared. Each device shared the same type of semiconductor laser as the light source and objective lens, with a wavelength of 785 nm and a numerical aperture of 0.45, respectively. In addition, each device was prepared with two types of optical system bases, two types of scanning mirrors for the light spot, two types of stages for driving the optical components and sample stage, and two types of adjustment of the origin of the optical path length of the reference light and the signal light. The basic configuration and main components of the device will be described later.

[0046] As a reference sample for measuring the particle size dependence of the normalized signal, a commercially available standard polystyrene bead suspension was diluted with pure water for clean room use to obtain a particle density of 10 7 Several samples were prepared with the concentration adjusted to 100 / mL. The size of the polystyrene particles contained in each standard sample was measured using a scanning electron microscope. The particle sizes prepared were 0.107 μm, 0.160 μm, 0.216 μm, 0.551 μm, 0.995 μm, and 1.510 μm.

[0047] Figure 6A shows the experimental results of measuring each standard sample with each device for three types of output power including the standard power, and plotting the relationship between the size of the standard particle and the normalized signal. As can be seen from the figure, the normalized signal provided by the present invention has almost no variation for four devices and three types of output power conditions, and can be measured as a value determined only by the particle size.

[0048] Figure 6B is an enlarged view of the experimental results of Figure 6A. When the particle size was the smallest at 0.107 μm, the effects of laser noise and Brownian motion of the particles were greatest, but the standard deviation of the normalized signal was 15%. For a particle size measurement device, it is desirable to keep the standard deviation below 10%.

[0049] <Third embodiment: Nonlinear size conversion model applicable to multiple devices with a lower limit on measurement size (1) In the case of polynomials> In the third embodiment of the present invention, a polynomial model will be described as a size conversion model for finding particle size from the measurement results of normalized signals using the multiple devices shown in the second embodiment.

[0050] In the present invention, a polynomial model is provided as a nonlinear model using the normalized signal S and introducing a lower limit d0 (d0>0) of the measurement size. d0 is the particle size at which the interference signal is nearly equal to the background scattering. In addition, since the size conversion model shown here is not device-specific, it has an advantage over the technology described in Patent Document 1 that it can be commonly used for products of the same model (same model numbers for semiconductor laser and objective lens).

[0051] If the particle size obtained from the normalized signal is d, the size conversion model is defined as follows: N is the maximum order of the polynomial model, c n is the coefficient multiplied with the term of order n. In equation 6, when the normalized signal S>0 and the right-hand side is positive, the particle size d becomes larger than the lower limit of the measurement size d0. Since it may be easier to understand if you move d0 to the right-hand side of equation 6, we present equation 6' as a supplementary equation.

[0052]

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[0053] Below, we will discuss the results of applying polynomials of degree N = 1 to 6. Here, we apply the size conversion model of Equation 6 to the results of Figure 6A, and obtain the parameters (unknowns) d0 and c n Multivariate optimization was performed using the Subplex method to minimize the error.

[0054] FIG. 7A shows the results of a model with degree 1 among the results of application of the polynomial size conversion model of the present invention. The parameters are d0 and c1, and the number of parameters is 2. A specific example of this model is shown in Equation 7A described below. In the figure, each plot shows the experimental results, and the straight lines show the model results. As can be seen from the figure, the error becomes large when the particle size is 0.2 μm or less and 1 μm or more. If this error can be tolerated, this model is a first-order linear formula, and is therefore very suitable for implementation in hardware such as FPGA.

[0055] FIG. 7B shows the results of a model with degree 2 among the results of applying the size conversion model using a polynomial of the present invention. The parameters are d0, c1, and c2, and the number of parameters is 3. A specific example of this model is shown in Equation 7B, which will be described later. In the figure, each plot shows the experimental results, and the curve shows the model results. As can be seen from the figure, the error between the plots and the curve is smaller than in the case of degree 1. If the remaining error is acceptable, this model is a second-order polynomial, and is therefore suitable for implementation in hardware such as FPGA.

[0056] FIG. 7C shows the results of a model with order 3 among the results of application of the size conversion model by polynomial of the present invention. The parameters are d0, c1, c2, and c3, and the number of parameters is 4. This model is specifically shown as Equation 7C described later. In the figure, each plot shows the experimental results, and the curve shows the model results. As can be seen from the figure, the error between the plot and the curve, especially when the particle size is 1 μm, is significantly smaller than in the case of order 2. If the residual error is acceptable, this model is a third-order polynomial, so it is suitable for implementation in hardware such as FPGA.

[0057] FIG. 7D shows the results of a model with degree 4 among the results of applying the size conversion model by polynomial of the present invention. The parameters are d0, c1, c2, c3, and c4, and the number of parameters is 5. A specific example of this model is Equation 7D described later. In the figure, each plot shows the experimental results, and the curve shows the model results. As shown in the figure, although a large improvement in error is not visible compared to the case of degree 3, the numerical error has decreased. If the remaining error and the increase in calculation time due to the increase in the number of parameters can be tolerated, this model is a fourth-order polynomial, so it is a relatively suitable model for implementation in hardware such as FPGA.

[0058] FIG. 7E shows the results of a model with degree 5 among the results of applying the size conversion model by polynomial of the present invention. The parameters are d0, c1, c2, c3, c4, and c5, and the number of parameters is 6. A specific example of this model is Equation 7E described later. In the figure, each plot shows the experimental results, and the curve shows the model results. As shown in the figure, although a large improvement in error is not visible compared to the case of degree 4, the numerical error has decreased. If the remaining error and the increase in calculation time due to the increase in the number of parameters can be tolerated, this model is a 5th-order polynomial, so it is a relatively suitable model for implementation in hardware such as FPGA.

[0059] FIG. 7F shows the results of a model with degree 6 among the results of applying the size conversion model by polynomial of the present invention. The parameters are d0, c1, c2, c3, c4, c5, and c6, and the number of parameters is 7. A specific example of this model is Equation 7F described later. In the figure, each plot shows the experimental results, and the curve shows the model results. As shown in the figure, although a large improvement in error is not visible compared to the case of degree 5, the numerical error has decreased. If the remaining error and the increase in calculation time due to the increase in the number of parameters can be tolerated, this model is a polynomial of degree 6, so it is a relatively suitable model for implementation in hardware such as FPGA.

[0060]

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[0061] FIG. 8 shows the experimental results showing the relationship between the order and RMS error of the size conversion model by the polynomial of the present invention. FIG. 8 shows the RMS (Root Mean Square) error when converting from the normalized signal to the particle size for the results shown in FIG. 7A to FIG. 7F. As can be seen from the figure, the RMS error decreases as the order of the polynomial increases. The range of the RMS error is from a maximum of about 0.07 μm to a minimum of about 0.01 μm. As the order of the polynomial increases, the calculation time increases when processed by a CPU, and the circuit scale and power consumption increase when implemented in hardware such as an FPGA. When using the technology disclosed in the present invention, one can select one that meets the specifications appropriately, taking into account the error (= size measurement accuracy) and the calculation time or circuit scale.

[0062] The above has been exemplified with respect to polynomial models of degree 1 to 6. In the present invention, as shown in Equation 6, a polynomial model of degree 7 or higher can also be used in the same manner to evaluate the RMS error of the particle size converted from the normalized signal based on the model equation, thereby making it possible to select a model suited to the circuit scale and precision specifications.

[0063] <Fourth embodiment: Nonlinear size conversion model applicable to multiple devices with lower limit of measurement size (2) In the case of exponential function> In the fourth embodiment of the present invention, an exponential function model will be described as a size conversion model for determining particle size from the measurement results of normalized signals using the multiple devices shown in the second embodiment.

[0064] In the present invention, an exponential function model is provided as a nonlinear model using a normalized signal S and introducing a lower limit d0 (d0>0) of the measurement size. d0 is the particle size at which the interference signal is almost equal to the background scattering. In addition, the size conversion model shown here is not specific to the device, and has the advantage over the technology described in Patent Document 1 that it can be commonly used for products of the same model (same model numbers for semiconductor laser and objective lens). At the same time, the following model has a relatively small number of parameters, 3, and is characterized in that the physical meaning of each parameter is easy to grasp compared to the above-mentioned polynomial model. In this regard, for example, when a second-generation device is designed to achieve high resolution by changing the wavelength of the light source or the numerical aperture of the objective lens compared to the first generation, the size conversion model is easy to manage.

[0065] Taking into consideration that the intensity distribution of the light spot is approximated by a Gaussian distribution, that the reflected light from the target particle is interference-amplified by a homodyne optical circuit (described later) and converted into a detection signal as an electrical signal equivalent to an electric field amplitude proportional to the 1 / 2 power of the light intensity, and that the reflected light from particles equal to or larger than the light spot size is saturated due to the size effect, three size conversion models are presented below. These are the basic first-order lag model and its advanced second-order lag model and Gaussian distribution model. To derive each parameter, a multivariate optimization process was performed using the Subplex method based on the results in Fig. 6A to minimize the error.

[0066] (1) First-order lag model To aid in understanding, a model expressing the normalized signal S obtained when a particle size d is given is shown in Equation 8. d0 (>0) is the particle size at which the interference signal is nearly equal to the background scattering, D (>0) is the light spot size constant expressing the saturation of the normalized signal due to the size of the light spot, and A (>0) is a constant expressing the magnitude of the saturation signal. Since these parameters each have a physical meaning, for example, when developing a new second-generation device with a light spot size of 1 / 2, if D in the above equation becomes close to 1 / 2, it can be interpreted that the prototype device has been assembled correctly. The inverse function of Equation 8 is used to convert from the normalized signal S to the size of the measured particle. Specifically, it is expressed as Equation 8' below. The form obtained by transferring d0 to the right-hand side is expressed as Equation 8'' below.

[0067]

number

[0068] FIG. 9A shows the results of applying the size conversion model based on the exponential function of the present invention, using a first-order lag model. In the figure, each plot shows the experimental results under various conditions for the four devices mentioned above, and the curves show the results of the size conversion model. As can be seen from the figure, the size conversion model and the experimental results match well. This is due to the effect of the introduction of the normalized signal provided by the present invention and the lower limit of the measurement size that models the effect of Rayleigh scattering. Since this model is a transcendental function formula, the circuit scale and power consumption will be large when implemented in hardware such as FPGA, but the extension of calculation time is small when processed by a general CPU with a built-in numerical calculation processor.

[0069] (2) Second-order lag model To aid understanding, the model expressing the normalized signal S obtained when particle size d is given is shown in Equation 9 below. d0 (>0) is the lower limit of measurement size due to the effects of Rayleigh scattering, D (>0) is the light spot size constant expressing the saturation of the normalized signal due to the size of the light spot, and A (>0) is a constant expressing the magnitude of the saturation signal. When converting from the normalized signal S to the size of the measured particle, the inverse function of Equation 9 is used. Specifically, this is expressed as Equation 9' below. When d0 is transferred to the right-hand side, it becomes Equation 9'' below.

[0070]

number

[0071] FIG. 9B shows the results of applying the size conversion model based on the exponential function of the present invention, using a second-order lag model. In the figure, each plot shows the experimental results under various conditions for the four devices mentioned above, and the curve shows the results of the size conversion model. As can be seen from the figure, the size conversion model and the experimental results are in good agreement. Comparing FIG. 9A with the curve representing the model, it can be seen that the rising region where the particle size is 0.2 μm or less changes smoothly. This is a characteristic suitable for a device with a high S / N ratio with reduced laser noise. At the same time, it can be seen that the saturation effect of the normalized signal in the region where the particle size is 1 μm or more is large. This is a characteristic suitable for detecting large particles. Since this model is a transcendental function, the circuit scale and power consumption will be large when implemented in hardware such as an FPGA, but the calculation time will not be extended much when processed by a general CPU with a built-in numerical calculation processor.

[0072] (3) Gaussian distribution model To aid understanding, a model expressing the normalized signal S obtained when particle size d is given is shown in Equation 10. d0 (>0) is the lower limit of measurement size due to the effects of Rayleigh scattering, D (>0) is the light spot size constant expressing the saturation of the normalized signal due to the size of the light spot, and A (>0) is a constant expressing the magnitude of the saturation signal. To convert from the normalized signal S to the size of the measured particle, the inverse function of Equation 10 is used. Specifically, it is shown in Equation 10' below. The form obtained by transferring d0 to the right-hand side is shown in Equation 10'' below.

[0073]

number

[0074] FIG. 9C shows the results of applying the size conversion model based on the exponential function of the present invention, using a Gaussian distribution model. In the figure, each plot shows the experimental results under various conditions for the four devices mentioned above, and the curves show the results of the size conversion model. As can be seen from the figure, the size conversion model and the experimental results are almost identical. Compared with FIG. 9A and FIG. 9B, the error is larger overall. In addition, the rising region where the particle size is 0.2 μm or less has a smoother change, which is a characteristic suitable for a device with a high S / N ratio with reduced laser noise. At the same time, it can be seen that the saturation effect of the normalized signal in the region where the particle size is 1 μm or more is even greater. This is a characteristic suitable for detecting large particles. Since this model is a transcendental function formula, the circuit scale and power consumption will be large when implemented in hardware such as an FPGA, but the calculation time will not be extended much when processed by a general CPU with a built-in numerical calculation processor.

[0075] Fig. 10 shows the experimental results showing the relationship between the size conversion model based on the exponential function formula of the present invention and the RMS error of the converted particle size, and is a summary of the results shown in Figs. 9A to 9C. As can be seen from the figure, the RMS errors of the first-order lag model and the second-order lag model are almost equal at about 0.02 μm, while the Gaussian distribution model has a slightly larger RMS error of about 0.055 μm. When using the technology disclosed in this invention, one can select the one that meets the specifications appropriately, taking into consideration the RMS error shown here (= measurement accuracy) and the above-mentioned rise region and saturation characteristics.

[0076] Above, three size conversion models based on exponential function formulas have been exemplified. The present invention is not limited to these, and size conversion models combined with higher-order exponential function formulas and the polynomial model shown above can also be applied. In such cases, a model suited to the amount of calculation and accuracy specifications can be appropriately used by evaluating the RMS error of the particle size converted from the normalized signal based on the model formula in the same procedure as shown here.

[0077] <Fifth embodiment: Comparison of size measurement accuracy between the present invention and the prior art> In the fifth embodiment of the present invention, the improvement of size measurement accuracy according to the present invention is summarized. Here, as a conventional size conversion model, a model in which the normalized signal is proportional to the particle size is used based on the results illustrated in FIG. 17 of Patent Document 1. The model formula is as follows. d represents the particle size, S represents the normalized signal, and c1 represents the proportionality coefficient. Compared with Formula 7A, the difference from the present invention is that there is no lower limit d0 of the measurement size that represents the characteristic change in the Rayleigh scattering region.

[0078]

number

[0079] FIG. 11A shows the RMS error of particle size measured by the conventional technology and the present invention. The horizontal axis of the figure is the number of parameters, where the conventional technology has a parameter number of 1, the polynomial model has a parameter number of order + 1, and the exponential function model has a parameter number of 3. As can be seen from the figure, the RMS error is about 0.07 μm or less for each model, which is a reasonable result for the measurement accuracy of particle size in the submicron region. The first-order polynomial (parameter number = 2) of the present invention has an RMS error that is almost the same as that of the conventional technology. It can be seen that the effect of the present invention is more noticeable in the polynomial model of second or higher order and the exponential function model, and the RMS error is improved to a minimum of about 0.01 μm.

[0080] FIG. 11B shows the results of comparing the relative error of the measured size obtained by the size conversion model for 0.107 μm (the minimum size shown in FIG. 6A) between the conventional technology and the present invention. As mentioned above, one of the main purposes of the present invention is to deal with the particle size in the Rayleigh scattering region and the characteristic change of the detection signal. As can be seen from the figure, the size measurement error is about 67% in the case of the conventional technology. On the other hand, it can be seen that the error is greatly improved to about 34% or less in the size conversion model of the present invention. It can be seen that a polynomial model (order ≧3) with 4 or more parameters and an exponential function model with a first-order lag system and a second-order lag system are suitable for reducing the size measurement error of a particle of about 0.1 μm to 10% or less. The results shown here are based on the wavelength (=0.785 μm) and objective lens (numerical aperture = 0.45) of the four devices prepared. When using the technology disclosed in this invention, one can select one that matches the specifications appropriately, taking into consideration the evaluation method of the size conversion model shown here.

[0081] <Embodiments 1 to 5: Supplementary information on proofreading work> In the above embodiment, d0 is fixed depending on the model of the particle measuring device, and there is no need to consider the difference in d0 between devices. A device whose background scattering measured using a reference sample is out of a predetermined range indicates that the device implementation is abnormal due to stray light, laser noise, etc., so the device can be shipped after appropriate measures such as readjustment of the optical system are taken. In addition, it is also possible to simplify the calibration work by applying the same size conversion model to devices whose background scattering is within a predetermined range.

[0082] <Sixth embodiment: Appropriate range of the measurement size lower limit d0 in the present invention> In the sixth embodiment of the present invention, the appropriate numerical range of the measurement size lower limit d0, which is a parameter that indicates the characteristic change of the detection signal in the Rayleigh scattering region disclosed in the above embodiments, is described. As is well known, in Rayleigh scattering and Mie scattering, the scattering characteristics are determined by the value obtained by dividing the particle size by the wavelength. Here, the appropriate numerical range of d0 / λ (λ is the wavelength of the light source) is described, taking into consideration the selection of the light source wavelength of the device.

[0083] Figure 12A shows the experimental results showing the relationship between d0 / λ values and the parameters of the size conversion model. The wavelength of the light source of the four devices prepared is 0.785 μm, and the numerical aperture of the objective lens is 0.45. As can be seen in the figure, d0 / λ ranged from 0.01 to 0.14. Figure 12B is a numerical table showing the appropriate range of d0 / λ values when the range of particle sizes to be measured is changed by selecting the numerical aperture of the objective lens based on the experimental results. The experimental conditions shown in the figure are as above.

[0084] The minimum value of d0 / λ is determined mainly by Rayleigh scattering, and it is appropriate to set the minimum value at 0.01 as shown in the figure.

[0085] The maximum value of d0 / λ may be considered to increase or decrease in proportion to the light spot size. It is known that the light spot size is proportional to 1 / numerical aperture. When using the technology of the present invention to measure the particle size distribution of large sizes (approximately 1 to 30 μm), the numerical aperture of the objective lens should be selected to be about 0.1. In this case, the light spot size is 4.5 times that of the experimental conditions, and the maximum value of d0 / λ is 0.63. On the other hand, when using the technology of the present invention to measure the particle size distribution of small sizes (approximately 0.03 to 1 μm), the numerical aperture of the objective lens should be selected to be about 0.95. In this case, the light spot size is 0.47 times that of the experimental conditions, and the maximum value of d0 / λ is 0.07.

[0086] As described above, in the size conversion model provided by the present invention, when the parameter d0 indicating the lower limit of the measurement size is taken as λ, and the wavelength of the light source is taken as λ, the appropriate numerical range of d0 / λ is 0.01 to 0.63.

[0087] <Embodiment 7: Particle measuring device> 13 is a diagram showing an example of the configuration of a particle measuring device according to the seventh embodiment of the present invention. Laser light emitted from a light source 100, whose light emission state is controlled by a laser driver 101 that controls high frequency superposition and emission power, is converted into parallel light by a collimating lens 102, and after the polarization direction is adjusted by a λ / 2 plate 103 whose optical axis is set at about 22.5 degrees with respect to the horizontal direction, the light is separated by a polarizing beam splitter 104 into a signal light and a reference light.

[0088] The reference light is converted to a circularly polarized state by the λ / 4 plate 105, reflected by the reference light mirror 106, and the polarization state is rotated by 90 degrees from the forward path by the λ / 4 plate 105, and reflected by the polarizing beam splitter 104. The signal light is deflected in its traveling direction by the XY-direction composite deflection element 107, converted to a circularly polarized state by the action of the built-in λ / 4 plate, and focused in the sample 204 held in the sample container 200 by the objective lens 108. The driving mechanism 109 that moves the sample in the Z-axis direction has the function of scanning the focal position of the signal light along the Z-axis direction (optical axis direction). The component of the signal light reflected from each particle contained in the sample 204 is deflected in the same direction as the forward path by the XY-direction composite deflection element 107, and is circular by the action of the built-in λ / 4 plate, and the polarization state is rotated by 90 degrees from the forward path, and passes through the polarizing beam splitter 104. Here, the sample container 200 holds a sample 204 in a well, and guides signal light into the sample through a transparent window 202. 203 is a resin member that forms the well of the sample container. The base plate 201 contacts the transparent window 202 to mechanically hold the sample container 200 and stabilize the temperature of the sample.

[0089] The signal light and the reference light are combined by the polarizing beam splitter 104 and guided to the detection optical system 112 , and are split by the half beam splitter 113 via the pinhole 111 into transmitted light and reflected light.

[0090] The reflected light passes through a λ / 4 plate 114, whose optical axis is set at approximately 45 degrees with respect to the horizontal direction, and is then focused by a focusing lens 115 and split into two by a polarizing beam splitter 116. The two beams are then photoelectrically converted by photodetectors 150 and 151, and differentially amplified by a current differential amplifier 152 to become a detection signal 123.

[0091] The transmitted light passes through a λ / 2 plate 118, whose optical axis is set at approximately 22.5 degrees with respect to the horizontal direction, and is then focused by a focusing lens 119 and split into two by a polarizing beam splitter 120. The two beams are then photoelectrically converted by photodetectors 153 and 154, and differentially amplified by a current differential amplifier 155 to become a detection signal 122.

[0092] The detection optical system 112 shown here constitutes a homodyne phase diversity method, and the real part component 122 and imaginary part component 123 of the detection signal are electrical signals corresponding to the real part and imaginary part of the electric field amplitude of the signal light reflected from an individual particle contained in the sample 204. The detection signal is calculated in the signal processing unit 124 as a numerical value obtained by calculating the square sum of these and then the square root.

[0093] The signal processing unit 124 synthesizes the time series data of the acquired detection signals to form three-dimensional image data in the XYZ directions of the sample, and separates / tracks the data of individual particles contained therein to calculate the maximum value of the detection signal obtained under the focusing conditions for each particle. The signal processing unit 124 further calculates the reference signal and the normalized signal according to the flows shown in Figures 3 and 5 and (Equation 1) to (Equation 5). Finally, the signal processing unit 124 calculates the particle size from the normalized signal using the size conversion model shown in the third and fourth embodiments of the present invention, and presents the results to the user after organizing them into a graph, a numerical table, or the like.

[0094] The implementation form of the signal processing unit 124 in the figure is an embedded microcomputer built into the device, or a computer that is placed outside the device and enables the exchange of necessary signals via an interface board, etc. If there are time or power constraints on the processing items of the signal processing unit 124, a dedicated processing circuit implemented by an FPGA or the like may be used as an auxiliary computing unit.

[0095] The memory unit 126 can store, for example, a measurement lower limit value d0 that is measured in advance for each individual particle measuring device. The signal processing unit 124 can calculate the particle size d by using the d0 stored in the memory unit 126 according to the method described in the above embodiment.

[0096] <Modifications of the present invention> The present invention is not limited to the above-described embodiment, and includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to those having all of the configurations described. In addition, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. In addition, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

[0097] In the above embodiments, the signal processing unit 124 can be built inside the particle measuring device, or the particle measuring device may acquire only data describing the results of measuring a sample, and the signal processing unit 124 may be arranged outside the particle measuring device to receive that data. In either case, the configuration of the particle measuring device according to the present invention is the same as that described in the above embodiments. [Explanation of symbols]

[0098] 100: Light source 101: Laser driver with high frequency superposition function 108: Objective lens 109: Sample container drive mechanism 112: Detection optical system 124: Signal processing unit 200: Sample container 201: Base plate 202: Transparent window 203: Resin member for forming a well

Claims

1. 1. A particle measurement device for measuring the size of particles contained in a liquid sample, comprising: A light source that emits light, a branching unit that branches the light from the light source into a signal light and a reference light; an irradiation unit that collects the signal light and irradiates the sample with the collected light; a detection unit for detecting an interference signal obtained by causing the reflected light from the particle to interfere with the reference light; a processor that measures the size of the particle using the interference signal; Equipped with The processing unit obtains a normalized signal S by dividing a maximum value of the interference signal detected by the detection unit by a reference value, The processing unit includes: The size of the particle is d, d0 is a lower limit of the particle size at which the interference signal is equal to or lower than the signal level of background scattering caused by the liquid; Then, the size of the particle is measured using a function that describes the relationship between S and (d-d0). A particle measuring device characterized by:

2. The function is configured to connect a portion of the interference signal caused by Mie scattering of the particle and a portion of the interference signal caused by Rayleigh scattering in a range equal to or greater than the lower limit in a plot of the interference signal and the size.