Photoacoustic measurement simulation method, photoacoustic measurement method and photoacoustic measurement device

Abstract

The invention provides a simulation method for photoacoustic measurement, and a photoacoustic measurement method and device. The simulation method comprises the following steps: acquiring system parameters of photoacoustic measurement equipment and physical parameters of a to-be-measured object; establishing a dual-temperature model to obtain the lattice temperature T1 (z, t) of the to-be-measured object; obtaining the lattice temperature gradient of the material at any position z; establishing a partial differential equation based on the temperature gradient and the local physical parameters of the material at any position z; solving the partial differential equation to obtain displacement u (z, t); derivation is carried out on the displacement u (z, t) in the thickness direction to obtain strain eta (z, t), and then a simulation signal with the reflectivity changing along with time is obtained through calculation. According to the technical scheme provided by the invention, the to-be-tested object of the multi-layer film is used as a whole for modeling, so that the boundary between the film layers does not need to be specially processed in the model, the modeling process is simplified, the calculation efficiency is improved, the simulation signal can be obtained with high precision, and the method is more universal. According to the photoacoustic measurement method based on the simulation method, the film thickness measurement value can be accurately obtained.

Description

Technical Field

[0001] The present disclosure relates to the field of optical measurement technology, and in particular to a photoacoustic measurement simulation method, a photoacoustic measurement method and a device. Background Art

[0002] In the process of manufacturing semiconductor devices, it is necessary to form one or more material layers with thickness ranging from a few nanometers to a few microns on the substrate to achieve different functional designs. The realization of the above process is called coating. For the coating process, the film thickness is a critical dimension. Process deviation or other possible system factors will affect the film thickness obtained after the coating process, and then affect the overall performance of the semiconductor device. Therefore, after the coating process, it is necessary to measure the film thickness at selected points to verify the stability of the coating process and ensure the yield of semiconductor device manufacturing.

[0003] It is understandable that in the coating process, the film layer formed can be either a dielectric film layer or a metal film layer. Compared with dielectric film layers, metal film layers have stronger absorption of light. When measuring thicker metal film layers ("thicker" here means that the thickness of the metal film layer is greater than the material absorption depth, that is, opaque film layers or translucent film layers) based on the traditional ellipsometry principle, the measurement result of the film thickness will be inaccurate due to the absorption of light by the metal material. Photoacoustic film thickness measurement is based on the principle of photoacoustic effect. By irradiating the sample surface with a short pulse laser, the sample absorbs photons to produce thermoelastic deformation and induces sound wave transmission. The film thickness signal is obtained by detecting the time difference of the echo signal arriving at the surface film layer; since the generated sound wave signal can penetrate multiple layers of transparent or opaque film layers, it can be used to accurately measure the film thickness of the metal film layer.

[0004] However, in the actual measurement process, when there are multiple film layers in the object to be measured, the echo signals corresponding to different film layers may be aliased, making it difficult to detect and distinguish the echo signals returned by each film layer. It is necessary to further establish a theoretical simulation model to obtain the simulation signal, and to obtain the accurate film thickness by fitting the simulation signal with the measured signal. In the process of establishing the theoretical simulation model, the commonly used method is to model each film layer of the object to be measured one by one, and it is necessary to clarify the boundary conditions between each adjacent film layer. The modeling is difficult, time-consuming, and not universal, so that the film thickness measurement of a single independent object to be measured requires a lot of manpower, material resources and time costs; in addition, in the process of fitting the simulation signal with the measured signal, it is easy to fall into the local optimal solution, which affects the accuracy and repeatability of the film thickness measurement, making the film thickness measurement of multi-layer film objects still a major problem. Summary of the invention

[0005] In response to the problems in the prior art, the purpose of the present invention is to provide a simulation method, a photoacoustic measurement method and a device for photoacoustic measurement, which can provide a simpler and more universal physical model, quickly and accurately establish a photoacoustic physical model of the object to be measured, and improve the accuracy and efficiency of obtaining simulation signals. On this basis, the film thickness parameters can be quickly and accurately obtained by adopting a genetic algorithm.

[0006] Specifically, the first aspect of the present disclosure provides a simulation method for photoacoustic measurement, which may include the following steps:

[0007] Obtaining system parameters of the photoacoustic measurement device and physical parameters corresponding to the object to be measured, where the object to be measured includes several layers of thin films;

[0008] A dual-temperature model is established, and the system parameters and physical parameters are substituted into the dual-temperature model to obtain the lattice temperature T of the material at any position z in the film thickness direction of the object to be measured at time t under the corresponding parameter conditions. l (z, t);

[0009] For lattice temperature T l (z, t) is derived in the direction of the film thickness to obtain the lattice temperature gradient of the material at any position z of the object to be measured;

[0010] Based on the local physical parameters of the material at any position z and the lattice temperature gradient at any position z, a partial differential equation for the displacement u(z,t) of the material at any position z at time t is established;

[0011] Obtain initial conditions and boundary conditions, and solve the partial differential equation based on the initial conditions and boundary conditions to obtain the displacement u(z,t) of the material at any position z at time t;

[0012] The displacement u(z, t) of the material at any position z at time t is derived in the direction of the film thickness to obtain the strain η(z, t) of the material at any position z at time t;

[0013] Based on the local physical parameters of the material at any position z and the strain η(z, t) of the material at any position z at time t, a simulation signal δR(t) is established to characterize the change of the reflectivity of the object to be measured with time during the measurement process.

[0014] In a possible implementation of the first aspect, the partial differential equation in the aforementioned steps is expressed as follows:

[0015]

[0016] Among them, ρ(z) is the density of the material at any position z, v(z) is the speed of sound propagating in the material at any position z, α(z) is the thermal expansion coefficient of the material at any position z, E(z) is the Young's modulus of the material at any position z, and γ(z) is the Poisson's ratio of the material at any position z.

[0017] In a possible implementation of the first aspect, the obtaining of initial conditions and boundary conditions in the aforementioned step includes:

[0018] The displacement u(z, 0) of the material at any position z at the initial time t=0 is taken as the initial condition, and the initial condition satisfies the following formula:

[0019] u(z,0)=0;

[0020] According to the local physical parameters of the material at z = 0 on the surface of the surface film of the object to be measured and the lattice temperature T of the material at z = 0 on the surface of the surface film of the object to be measured at time t l (0, t), establish boundary conditions, and the boundary conditions satisfy the following formula:

[0021]

[0022] Among them, B 0 is the bulk modulus of the material at z = 0 on the surface of the surface film, α 0 is the thermal expansion coefficient of the material at z = 0 on the surface of the surface film, ρ 0 is the density of the material at z = 0 on the surface of the surface film, v 0 It is the sound velocity of the material propagating at z=0 on the surface of the surface film.

[0023] In a possible implementation of the first aspect, the simulation signal δR(t) characterizing the change of the reflectivity of the object to be measured over time during the measurement process is established in the above steps, and satisfies the following formula:

[0024]

[0025] Among them, f(z) is the sensitivity function, which is expressed as follows:

[0026]

[0027] In the above formula, f 0 satisfy:

[0028] In the above formula, ψ satisfies:

[0029] Where n is the material refractive index, κ is the material extinction coefficient, λ is the pump light wavelength, ζ is the pump light absorption depth, c is the speed of light, and ω is the pump light angular frequency.

[0030] In a possible implementation of the first aspect, the system parameters include at least one or more combinations of wavelength, power, pulse width, and spot size on the surface of the object to be measured of the pump light and the probe light;

[0031] The physical parameters include at least one or more combinations of the thickness, density, specific heat capacity, Young's modulus, thermal conductivity, refractive index, thermal expansion coefficient, propagation speed of sound, bulk modulus, and Poisson's ratio of each thin film in the object to be measured.

[0032] The simulation method disclosed in the first aspect above models the multilayer film object to be measured as a whole, so there is no need to specially process the boundaries of different film layers in the model, which simplifies the modeling process, improves the calculation efficiency, and can obtain the simulation signal of the object to be measured with high precision. In addition, for the multilayer film object to be measured that has echo aliasing during measurement, the above photoacoustic measurement simulation method can also accurately obtain the corresponding echo aliasing simulation signal.

[0033] A second aspect of the present disclosure provides a photoacoustic measurement method, comprising the following steps:

[0034] Using a photoacoustic measuring device to measure photoacoustic signals of the object to be measured, so as to obtain a measured reflectivity change signal of the object to be measured;

[0035] Determine the value ranges of several physical parameters of the object to be measured, the physical parameters including the film thickness of the object to be measured, and generate several different physical parameter combinations by randomly selecting values ​​within the value range of each physical parameter;

[0036] According to the simulation method of photoacoustic measurement provided in the first aspect, a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each physical parameter combination is obtained respectively, and a first error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each physical parameter combination and the measured reflectivity change signal is obtained respectively;

[0037] Based on several first error values, a genetic algorithm is used to iterate the physical parameter combination until the second error value between the simulated signal δR(t) of the reflectivity change over time corresponding to the iterated physical parameter combination and the measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, and the second error value less than the preset threshold or equal to the minimum extreme value is used as the optimized error value, and the physical parameter combination corresponding to the optimized error value is used as the output result of the photoacoustic measurement, and the output result includes the thickness of each layer of the film.

[0038] In a possible implementation of the second aspect, based on a plurality of first error values, a genetic algorithm is used to iterate the physical parameter combination until a second error value between a simulated signal δR(t) of a reflectivity change over time corresponding to the iterated physical parameter combination and a measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, the process includes the following steps:

[0039] Step 1, comparing the first error value with the deviation threshold, discarding the physical parameter combinations corresponding to the first error value being greater than the deviation threshold, and retaining the remaining physical parameter combinations;

[0040] Step 2, performing parameter exchange operation and / or parameter mutation operation on the remaining physical parameter combinations to generate a plurality of next-generation physical parameter combinations, where the next-generation physical parameter combinations are different from the remaining physical parameter combinations;

[0041] Step 3, according to the simulation method of photoacoustic measurement provided in the first aspect, obtain a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each sub-generation physical parameter combination, and respectively obtain a second error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each sub-generation physical parameter combination and the measured reflectivity change signal;

[0042] Step 4: If the second error value is less than a preset threshold or reaches a minimum value, the iteration ends;

[0043] If the second error value is not less than the preset threshold and the minimum value is not obtained, the second error value is compared with the deviation threshold, the physical parameter combination corresponding to the second error value greater than the deviation threshold is discarded, and the remaining physical parameter combinations are retained. Steps 2-4 are repeated until the second error value is less than the preset threshold or the minimum extreme value is obtained, and the iteration ends.

[0044] For the photoacoustic measurement method disclosed in the second aspect, a simulation signal is obtained based on the simulation method of photoacoustic measurement provided in the first aspect, and genetic iteration is performed on the physical parameter combination, which can adapt to the change of the initial value and avoid falling into the local optimal solution, thereby improving the accuracy and repeatability of the film thickness measurement; the physical parameters obtained by fitting include not only the thickness of each film layer of the object to be measured, but also other physical parameters of each film layer of the object to be measured except the thickness. These other physical parameters except the thickness can be used to evaluate the coating uniformity of the object to be measured, so as to further monitor the production process of the object to be measured.

[0045] A third aspect of the present disclosure provides another photoacoustic measurement method, comprising the following steps:

[0046] Using a photoacoustic measuring device to measure photoacoustic signals of the object to be measured, so as to obtain a measured reflectivity change signal of the object to be measured;

[0047] Acquire several physical parameter combinations of the object to be measured, wherein each physical parameter combination includes a film thickness, and only the film thickness is the same in any two physical parameter combinations;

[0048] According to the simulation method of photoacoustic measurement provided in the first aspect, a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each physical parameter combination is obtained, and a first error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each physical parameter combination and the measured reflectivity change signal is obtained respectively;

[0049] Based on a number of first error values, a genetic algorithm is used to iterate the physical parameter combination until a second error value between a simulated signal δR(t) of a reflectivity change over time corresponding to the iterated physical parameter combination and a measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, and the second error value less than the preset threshold or equal to the minimum extreme value is used as an optimized error value, and physical parameters other than the film thickness are extracted from the physical parameter combination corresponding to the optimized error value as fixed parameters;

[0050] Keep the parameters fixed, only float the value of the film thickness, and construct several new physical parameter combinations;

[0051] According to the simulation method of photoacoustic measurement provided in the first aspect, a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each new physical parameter combination is obtained respectively, and a database of the simulation signal δR(t) of the change of reflectivity over time is constructed;

[0052] The library matching method is used to determine in the database a simulated signal δR(t) of the reflectivity change over time that matches the measured reflectivity change signal, and a combination of physical parameters corresponding to the matched simulated signal δR(t) of the reflectivity change over time is used as the output result of the photoacoustic measurement, and the output result includes the thickness of each layer of the film.

[0053] In a possible implementation of the third aspect, based on a plurality of first error values, a genetic algorithm is used to iterate the physical parameter combination until a second error value between a simulated signal δR(t) of a reflectivity change over time corresponding to the iterated physical parameter combination and a measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, the process includes the following steps:

[0054] Step 1, comparing the first error difference with the deviation threshold, discarding the physical parameter combinations whose first error values ​​are greater than the deviation threshold, and retaining the remaining physical parameter combinations;

[0055] Step 2, performing parameter exchange operation and / or parameter mutation operation on the remaining physical parameter combinations to generate several next-generation physical parameter combinations, wherein the next-generation physical parameter combinations are different from the remaining physical parameter combinations, and the film thickness in the next-generation physical parameter combinations is the same as the film thickness in the remaining physical parameter combinations;

[0056] Step 3, according to the simulation method of photoacoustic measurement provided in the first aspect, obtain a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each sub-generation physical parameter combination, and respectively obtain a second error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each sub-generation physical parameter combination and the measured reflectivity change signal;

[0057] Step 4: If the second error value is less than a preset threshold or reaches a minimum value, the iteration ends;

[0058] If the second error value is not less than the preset threshold and the minimum value is not obtained, the second error value is compared with the deviation threshold, the physical parameter combinations corresponding to the second error value greater than the deviation threshold are discarded, and the remaining physical parameter combinations are retained. Steps 2-4 are repeated until the second error value is less than the preset threshold or the minimum extreme value is obtained, and the iteration ends.

[0059] For the photoacoustic measurement method disclosed in the third aspect, on the basis of the photoacoustic measurement method disclosed in the second aspect, the value of the film thickness is first fixed, and then the genetic algorithm is used to iteratively fit the other physical parameters of each film layer except the thickness; after determining the other physical parameters of each film layer except the thickness, a corresponding simulation signal database can be established according to different film layer thickness combinations, and then the film layer thickness combination corresponding to the simulation signal δR(t) of the reflectivity change over time that is closest to the actual reflectivity change signal is selected through the library matching method. The database matching method has less calculation amount, greatly reduces the time required for calculating the film thickness, further improves the measurement speed, optimizes the practical application effect of the photoacoustic measurement method provided by the present disclosure, and improves the accuracy and repeatability of film thickness measurement.

[0060] A fourth aspect of the present disclosure provides a photoacoustic measurement device, comprising:

[0061] A measuring module, used to perform photoacoustic signal measurement on the object to be measured to obtain a measured reflectivity change signal of the object to be measured;

[0062] A simulation module, used to obtain a simulation signal δR(t) of the change of reflectivity over time according to the simulation method of photoacoustic measurement provided in the first aspect;

[0063] A calculation module is used to obtain the output result of the photoacoustic measurement according to the photoacoustic measurement method provided by the second aspect or the third aspect, wherein the output result includes the thickness of each layer of the film.

[0064] In summary, compared with the prior art, the present disclosure has the following beneficial effects:

[0065] Through the technical solution provided by the present disclosure, in the theoretical modeling and simulation stage, it is not necessary to model layer by layer according to the film layer distribution of the object to be measured, which has the advantages of simplified modeling process, low modeling complexity and strong modeling universality; selecting a genetic algorithm in the stage of fitting the simulation signal and the measured signal can avoid falling into the local optimal solution and improve the fitting accuracy; in the photoacoustic measurement results, in addition to providing accurate film thickness information, it can also provide other physical parameters of each film layer except the thickness, which is helpful for evaluating the uniformity of the coating; in addition, when obtaining the film thickness measurement value, the value of the film thickness can be fixed first, and other physical parameters except the film thickness can be obtained by fitting the genetic algorithm, and then on this basis, a database of simulation signals corresponding to different film thickness combinations can be constructed, and then the film thickness measurement value can be quickly obtained by library matching, which greatly reduces the time required for calculating the film thickness. The technical solution provided by the present disclosure can effectively reduce the complexity of the simulation and fitting process in the photoacoustic measurement, improve the accuracy and repeatability of the film thickness parameter acquisition, save the time required for the film thickness parameter acquisition, and has a popularizable value. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Other features, objects and advantages of the present disclosure will become more apparent from a reading of the detailed description of non-limiting embodiments made with reference to the following accompanying drawings.

[0067] Figure 1 According to the prior art, a schematic diagram of the principle of photoacoustic film thickness measurement of an object to be measured is provided.

[0068] Figure 2 According to the prior art, a schematic diagram of an acoustic wave echo propagating along the film thickness direction in a single-layer film object to be tested is provided.

[0069] Figure 3 According to the prior art, a schematic diagram of an acoustic wave echo propagating along the film thickness direction in a multi-layer film to be tested is provided.

[0070] Figure 4 According to an embodiment of the present disclosure, a schematic flow chart of a simulation method for photoacoustic measurement is provided.

[0071] Figure 5 According to a specific embodiment of the present disclosure, a schematic diagram is provided showing how the lattice temperature at a certain position z in the film thickness direction changes with time.

[0072] Figure 6According to a specific embodiment of the present disclosure, a schematic diagram of the variation of strain at a certain moment with position z is provided.

[0073] Figure 7 According to a specific embodiment of the present disclosure, a schematic diagram of a simulation signal δR(t) showing the change of reflectivity over time is provided.

[0074] Figure 8 According to a specific embodiment of the present disclosure, a schematic flow chart of a photoacoustic measurement method is provided.

[0075] Fig. 9 According to a specific embodiment of the present disclosure, a schematic diagram of a measured reflectivity change signal over time is provided.

[0076] Fig.10 According to a specific embodiment of the present disclosure, a flow chart of iterating a combination of physical parameters using a genetic algorithm is provided.

[0077] Fig.11 According to a specific embodiment of the present disclosure, a schematic flow chart of another photoacoustic measurement method is provided.

[0078] Fig.12 According to a specific embodiment of the present disclosure, a schematic diagram of the structure of a database of a simulation signal δR(t) of reflectivity variation over time is provided.

[0079] Fig.13 According to a specific embodiment of the present disclosure, a schematic structural diagram of another photoacoustic measurement device is provided. DETAILED DESCRIPTION

[0080] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in the present disclosure. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in the present disclosure can also be modified or changed in various ways according to different viewpoints and application systems without departing from the spirit of the present disclosure. It should be noted that the embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0081] The following is a detailed description of the embodiments of the present disclosure with reference to the accompanying drawings so that those skilled in the art can easily implement the present disclosure. The present disclosure can be embodied in many different forms and is not limited to the embodiments described herein.

[0082] In the representations of the present disclosure, the reference terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" and the like mean that the specific features, structures, materials, or characteristics represented in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. Moreover, the specific features, structures, materials, or characteristics represented may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples represented in the present disclosure and the features of different embodiments or examples, unless they are mutually contradictory.

[0083] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the representation of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0084] In order to clearly describe the present disclosure, components not related to the description are omitted, and the same reference numerals are given to the same or similar components throughout the specification.

[0085] Throughout the specification, when a device is said to be "connected" to another device, this includes not only the case of "direct connection" but also the case of "indirect connection" by placing other elements therebetween. In addition, when a device is said to "include" a certain component, unless otherwise stated, it does not exclude other components, but means that other components may be included.

[0086] When a device is said to be "on" another device, it may be directly on the other device, but there may also be other devices between it. In contrast, when a device is said to be "directly" on another device, there are no other devices between it.

[0087] Although the terms first, second, etc. are used to represent various elements in some examples, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, the first interface and the second interface, etc. are represented. Moreover, as used in this article, the singular forms "one", "one" and "the" are intended to also include plural forms, unless there is an opposite indication in the context. It should be further understood that the terms "comprising" and "including" indicate the existence of features, steps, operations, elements, components, projects, kinds, and / or groups, but do not exclude the existence, occurrence or addition of one or more other features, steps, operations, elements, components, projects, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Therefore, "A, B or C" or "A, B and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C". Only when the combination of elements, functions, steps or operations is inherently mutually exclusive in some way, will there be an exception to this definition.

[0088] The technical terms used herein are only used to refer to specific embodiments and are not intended to limit the present disclosure. The singular form used herein also includes the plural form unless the sentence clearly indicates the contrary meaning. The meaning of "including" used in the specification is to specify specific characteristics, regions, integers, steps, operations, elements and / or components, and does not exclude the existence or addition of other characteristics, regions, integers, steps, operations, elements and / or components.

[0089] Although not defined differently, all terms, including technical and scientific terms used herein, have the same meaning as those generally understood by those skilled in the art to which the present disclosure belongs. Terms defined in commonly used dictionaries are additionally interpreted as having meanings consistent with the content of relevant technical literature and current disclosures, and unless defined, shall not be overly interpreted as ideal or very formal meanings.

[0090] According to the relevant explanations and descriptions in the prior art, it can be understood that for a coating structure including a metal film layer, a photoacoustic film thickness measurement scheme can be used to measure the film thickness. The implementation of the photoacoustic film thickness measurement scheme will first be briefly described below:

[0091] Specifically, Figure 1 FIG. 1 shows a schematic diagram of the principle of photoacoustic film thickness measurement of an object to be measured. Figure 1 As shown, the pump light 101 is used as an excitation light beam to irradiate the surface of the object to be measured 100, so that the object to be measured 100 absorbs photons and generates thermoelastic deformation, that is, Figure 1As shown in 102, this thermoelastic deformation 102 will form a propagating sound wave on the surface and inside of the sample: when the sound wave propagating along the film thickness direction propagates to the interface of the film layer for the first time, a first echo signal will be generated. When the first echo signal returns to the surface of the object to be tested 100, the reflectivity of the surface of the object to be tested 100 will change. Figure 1 The detection module 103 can detect the reflectivity change of the reflected detection light 103b of the incident detection light 103a. The first echo signal rebounds on the surface of the object to be tested 100, and after rebounding, it continues to propagate along the film thickness direction to the junction of the film layer to generate a second echo signal. The second echo signal returns to the surface of the object to be tested 100, which will also cause the reflectivity to change. The time difference between the two reflectivity changes obtained by detection can be used to obtain the corresponding surface film thickness, that is:

[0092]

[0093] Where d is the thickness of the surface film, Δt is the time difference between two changes in reflectivity, and v is the propagation speed of the sound wave in the surface film. Correspondingly, Figure 2 A schematic diagram of an acoustic wave echo propagating along the film thickness direction in a single-layer film to be tested is shown, and those skilled in the art can directly obtain the film thickness intuitively according to the above method.

[0094] For multi-layer film objects to be tested, the situation becomes more complicated: when the sound wave propagating along the film thickness direction first propagates to the junction of the first film layer and the second film layer, part of the sound wave signal is reflected to form the above-mentioned first echo signal, and the other part of the sound wave signal continues to propagate along the film thickness direction toward the inside of the multi-layer film object to be tested; when it propagates to the junction of the second film layer and the third film layer, part of the sound wave signal is also reflected to form an echo signal, and the other part continues to propagate into the inside of the object to be tested... As the number of film layers increases, this makes it very easy for the echo signal returning to the sample surface to be aliased. Correspondingly, Figure 3 A schematic diagram of an acoustic wave echo propagating along the film thickness direction in a multi-layer film to be tested is shown. Figure 3 As shown in the figure, it can be seen that the echo signals of different film layers are prone to aliasing. It is difficult to distinguish the echo signals returned by each film layer only through the measured signal of the change in surface reflectivity, and thus it is impossible to determine the thickness of each film layer.

[0095] It is understandable that, based on the prior art and the aforementioned related explanations, it can be seen that the difficulty in measuring the film thickness of a multi-layer film object to be tested is mainly due to the aliasing of echo signals corresponding to different film layers; and the solutions provided by the prior art have the difficulty in establishing a simulation model, and it is impossible to obtain a simulation signal with aliasing of the echo signals of the object to be tested, and the fitting is prone to fall into the pain point of a local optimal solution. The present disclosure provides a technical solution, which provides targeted solutions to the two pain points of establishing a simulation model and fitting of simulation signals with measured signals, simplifies the difficulty of simulation modeling, improves the universality of simulation modeling and the accuracy of data fitting, and enables efficient and accurate measurement of the film thickness of a multi-layer film object to be tested. The following will explain and illustrate the specific implementation of simulation model establishment and data fitting respectively:

[0096] It can be understood that the establishment of the simulation model is an important part that is basic and difficult to obtain in the film thickness measurement of the multi-layer film to be measured. In some embodiments provided in the present disclosure, Figure 4 A schematic diagram of the process flow of a simulation method for photoacoustic measurement is provided. Figure 4 As shown, the following steps may be specifically included:

[0097] Step 401: Obtain the system parameters of the photoacoustic measurement device and the physical parameters corresponding to the object to be measured. The object to be measured includes several layers of thin films. It can be understood that the object to be measured includes a multi-layer film object to be measured and a single-layer film object to be measured, that is, the technical solution provided by the present disclosure is intended to obtain the thickness of each film layer in the multi-layer film object to be measured. The relevant technical solution can also be applied to the film thickness measurement of the single-layer film object to be measured, which will not be elaborated here.

[0098] Step 402: Establish a dual-temperature model, substitute system parameters and physical parameters into the dual-temperature model to obtain the lattice temperature T of the material at any position z in the film thickness direction of the object to be tested at time t under the corresponding parameter conditions. l (z, t).

[0099] Step 403: Lattice temperature T l (z, t) is derived in the direction of the film thickness to obtain the lattice temperature gradient of the material at any position z of the object to be measured.

[0100] Step 404: Based on the local physical parameters of the material at any position z and the lattice temperature gradient at any position z, a partial differential equation of the displacement u(z, t) of the material at any position z at time t is established.

[0101] Step 405: Obtain initial conditions and boundary conditions, and solve the partial differential equation based on the initial conditions and boundary conditions to obtain the displacement u(z, t) of the material at any position z at time t.

[0102] Step 406: Derivative the displacement u(z, t) of the material at any position z at time t in the film thickness direction to obtain the strain η(z, t) of the material at any position z at time t.

[0103] Step 407: Based on the local physical parameters of the material at any position z and the strain η(z, t) of the material at any position z at time t, a simulation signal δR(t) is established to characterize the change of the reflectivity of the object to be measured with time during the measurement process.

[0104] It can be seen that in the above embodiment, based on the dual-temperature model, the lattice temperature of the object to be tested at any position z in the thickness direction of the film is first obtained, and then the lattice temperature gradient is obtained. Then, a partial differential equation is established according to the lattice temperature gradient and the local physical parameters of the material at any position z, and the partial differential equation is solved to obtain the displacement at position z that changes with time, and then the displacement is derived in the thickness direction to obtain the strain, and finally the simulation signal δR(t) of the reflectivity at position z that changes with time is established according to the strain. Through the above scheme provided by the present disclosure, there is no need to model each film layer in the multilayer film object to be tested one by one, but directly take the entire object to be tested as a whole to obtain the simulation signal of the reflectivity change, which simplifies the modeling process of obtaining the simulation signal, saves modeling time, reduces the difficulty and complexity of modeling, and improves the modeling accuracy. For the multilayer film object to be tested that has echo aliasing during measurement, the above photoacoustic measurement simulation method can also accurately obtain the corresponding simulation signal of echo aliasing. The following will be further explained by the specific implementation of the above steps 401 to 406:

[0105] In the above step 401, the system parameters may include at least one or more combinations of the wavelength, power, pulse width of the pump light and the probe light, and the spot size on the surface of the object to be measured. In a preferred embodiment of the present disclosure, the system parameters include all of the above parameters; the physical parameters may include at least one or more combinations of the thickness, density, specific heat capacity, Young's modulus, thermal conductivity, refractive index, thermal expansion coefficient, propagation speed of sound, bulk modulus, and Poisson's ratio of each thin film in the object to be measured. In a preferred embodiment of the present disclosure, the physical parameters also include all of the above parameters. It can be understood that the technical solution provided by the present disclosure introduces more physical parameters other than thickness related to the film layer, which can more accurately calculate the reflection and transmission of sound waves between film layers of different materials, so that a more accurate simulation signal of reflectivity changing with time can be obtained.

[0106] In the specific implementation of step 401, the initial value of the thickness of each layer of the film is the nominal thickness value of each film layer, and the initial values ​​of other physical parameters of each film layer except the thickness are all empirical values. In the process of establishing the simulation model, the value range of each physical parameter can be predetermined, and random values ​​can be taken within the value range to obtain multiple physical parameter combinations, at least one physical parameter in any two physical parameter combinations is different, and each physical parameter combination contains multiple or all parameter types.

[0107] It is understandable that the principle of photoacoustic measurement is that the excitation light beam irradiates the film layer of the object to be measured, which will cause the free electrons in the film layer to absorb a large amount of energy, and the electron temperature will rise sharply; then the energy is transferred from the electrons to the lattice, causing the lattice temperature to rise; the different lattice temperature rise rates at different positions in the thickness direction of the film produce a temperature gradient, which in turn induces stress and strain to generate the propagation of sound waves. Therefore, in the simulation process, it is necessary to obtain in advance the lattice temperature T of the material at any position z in the thickness direction of the film under given parameter conditions. l In a specific implementation of step 402, a dual-temperature model is used to obtain the lattice temperature T of the material at any position z in the thickness direction of the film at time t. l (z, t), specifically, the relevant mathematical expressions are as follows:

[0108]

[0109]

[0110] Among them, T e is the electron temperature; T l is the lattice temperature; C e is the specific heat of electrons; C l is the lattice specific heat capacity; G is the electron lattice thermal conduction coupling coefficient; Q(z, t) is the pump light heat absorbed by the material at any position z in the film thickness direction at time t; k l is the lattice thermal conductivity; k e is the electronic thermal conductivity; t is the time. Furthermore, the pump light source generally uses an ultrashort pulse femtosecond laser, so the corresponding pump light heat Q(z, t) absorbed by the material at any position z in the film thickness direction at time t can be expressed as:

[0111]

[0112] Among them, r and z are the cylindrical coordinate positions established in the film thickness direction; r s 、z s are the dimensions of the laser in cylindrical coordinates; t pis the laser pulse width; J 0 is the peak power of the laser; R is the surface refractive index of the material; L is the film thickness; for Gaussian distributed pump light, β=4ln2.

[0113] Based on the above mathematical expressions and given system parameters and physical parameters, the electron temperature T of the material at any position z in the thickness direction of the film can be obtained. e and the lattice temperature T l Changes over time, where T l (z, t) represents the lattice temperature of the material at any position z in the thickness direction of the film at time t during the propagation of the sound wave. For example, Figure 5 That is, it shows a schematic diagram of the change of lattice temperature at a certain position z in the film thickness direction over time. It can be seen that the lattice temperature of the material at any position z in the film thickness direction rises rapidly to a peak value in a very short time after receiving the excitation light, and then the lattice temperature gradually decreases as time goes by.

[0114] Different from the prior art, which requires modeling each film layer separately and clarifying the boundary conditions between layers, the technical solution provided by the present disclosure treats the multilayer film to be tested as a whole, and considers the local physical parameters of the material at any position z in the film thickness direction and the lattice temperature gradient at any position z of the multilayer film to be tested, and obtains the displacement u(z,t) of the material at any position z in the film thickness direction at time t by establishing a partial differential equation. Specifically, the expression of the partial differential equation can be as follows:

[0115]

[0116] Where ρ(z) is the density of the material at any position z, F z is the force on the material at any position z. It is understandable that the temperature gradient will produce strains of different magnitudes at different positions. The difference in the magnitude of this strain will generate forces between materials at different positions. The relationship between this force and strain will be transmitted in the form of sound waves. z The expression can be as follows:

[0117]

[0118] Where ρ(z) is the density of the material at any position z, v(z) is the speed of sound propagating through the material at any position z, α(z) is the thermal expansion coefficient of the material at any position z, E(z) is the Young's modulus of the material at any position z, and γ(z) is the Poisson's ratio of the material at any position z. is the lattice temperature gradient, that is, the lattice temperature T lThe derivative of (z, t) in the film thickness direction. Therefore, based on the local physical parameters of the material at any position z and the lattice temperature gradient at any position z, a partial differential equation for the displacement u(z, t) of the material at any position z at time t is established.

[0119] The traditional film thickness simulation modeling method needs to use the transfer matrix to calculate and process each film layer. In the process of partial differential equation modeling, it is necessary to clarify the boundary conditions between layers. The modeling conditions are complex and only applicable to objects to be tested of uniform materials. In the above scheme provided by the present disclosure, it is not difficult to see based on the specific establishment of the above partial differential equation that by introducing more physical parameters, the multilayer film object to be tested is modeled as a whole. Therefore, there is no need to specially process the boundaries of different film layers in the model, which simplifies the modeling process, improves the calculation efficiency, and can obtain the simulation signal of the object to be tested with high precision. The solution of the above partial differential equation will be further explained below:

[0120] It can be understood that boundary conditions and initial conditions are required to solve any partial differential equation. The steps of obtaining the initial conditions and boundary conditions in the above steps include:

[0121] The displacement u(z, 0) of the material at any position z at the initial time t=0 is taken as the initial condition, and the initial condition satisfies the following formula:

[0122] u(z,0)=0;

[0123] As for the boundary conditions, since the strain on the surface of the surface film of the object to be measured is completely caused by the change of lattice temperature, it can be calculated based on the local physical parameters of the material at z = 0 on the surface of the surface film of the object to be measured and the lattice temperature T of the material at z = 0 on the surface of the surface film of the object to be measured at time t. l (0, t), establish boundary conditions, and the boundary conditions satisfy the following formula:

[0124]

[0125] Among them, B 0 is the bulk modulus of the material at z = 0 on the surface of the surface film, α 0 is the thermal expansion coefficient of the material at z = 0 on the surface of the surface film, ρ 0 is the density of the material at z = 0 on the surface of the surface film, v 0 It is the sound velocity of the material propagating at z=0 on the surface of the surface film.

[0126] Based on the above initial conditions and boundary conditions, the above partial differential equation can be solved to obtain the displacement u(z, t) of the material at any position z at time t. Further, by differentiating the displacement u(z, t) in the film thickness direction, the strain η(z, t) of the material at any position z at time t can be obtained, that is:

[0127]

[0128] For example, Figure 6 A schematic diagram showing the variation of strain with position z at a certain moment t.

[0129] In the above step 407, in the process of establishing the simulation signal δR(t) representing the change of the reflectivity of the object to be measured with time during the measurement process, the following formula can be used:

[0130]

[0131] Among them, f(z) is the sensitivity function, which characterizes the sensitivity of reflectivity to strain over time, and its expression is as follows:

[0132]

[0133] In the above formula, f 0 satisfy:

[0134] In the above formula, ψ satisfies:

[0135] Where n is the material refractive index, κ is the material extinction coefficient, λ is the pump light wavelength, ζ is the pump light absorption depth, c is the speed of light, and ω is the pump light angular frequency.

[0136] It can be seen that the above sensitivity function is related to the physical parameters of the object to be measured, and the simulation signal δR(t) of the change of reflectivity over time can be obtained through the physical parameters of the object to be measured and the strain of the material at any position z at time t. Figure 7 That is, it is a schematic diagram showing the simulated signal δR(t) of the change of the reflectivity of the object to be measured with time during the measurement process.

[0137] Based on the relevant description of the above embodiments, the technical solution provided by the present disclosure can achieve high-precision simulation of the reflectivity change signal curve compared with the prior art, and at the same time, there is no need to simulate each film layer in the multi-layer film object to be tested one by one and consider the boundary conditions between the film layers. It can be flexibly applied to various types of multi-layer film objects to be tested, with low difficulty, strong universality, and saving modeling time. For multi-layer film objects to be tested that have echo aliasing during measurement, the above photoacoustic measurement simulation method can also accurately obtain the corresponding echo aliasing simulation signal.

[0138] In some embodiments of the present disclosure, a photoacoustic measurement method is also provided, which can apply the simulation method provided in the above embodiments to perform photoacoustic measurement of the film thickness of the object to be measured. Specifically, Figure 8 A schematic diagram of the process of a photoacoustic measurement method is provided, such as Figure 8 As shown, the photoacoustic measurement method may specifically include the following steps:

[0139] Step 801: Use a photoacoustic measuring device to measure the photoacoustic signal of the object to be measured to obtain the measured reflectivity change signal of the object to be measured. It is understandable that the photoacoustic signal measurement of the object to be measured can refer to the scheme of the prior art, and those skilled in the art can also make adaptive adjustments to the specific implementation steps according to actual needs, which is not limited here. Specifically, Fig. 9 A schematic diagram of the measured reflectivity change signal is shown.

[0140] Step 802: Determine the value ranges of several physical parameters of the object to be measured, the physical parameters including the film thickness of the object to be measured, and generate several different physical parameter combinations by randomly selecting values ​​within the value range of each physical parameter.

[0141] Step 803: According to the simulation method of photoacoustic measurement provided in the aforementioned embodiment, respectively obtain the simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each physical parameter combination, and respectively obtain the first error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each physical parameter combination and the measured reflectivity change signal.

[0142] Step 804: Based on a number of first error values, a genetic algorithm is used to iterate the physical parameter combination until the second error value between the simulated signal δR(t) of the reflectivity change over time corresponding to the iterated physical parameter combination and the measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, and the second error value less than the preset threshold or equal to the minimum extreme value is used as the optimized error value, and the physical parameter combination corresponding to the optimized error value is used as the output result of the photoacoustic measurement, and the output result includes the thickness of each layer of the film. Among them, the second error value obtaining the minimum extreme value refers to the minimum error value that cannot be further reduced through iteration, and the specific implementation of the genetic algorithm will be described in detail later.

[0143] It is understandable that in the prior art, in the process of fitting the measured signal of the multilayer film object to be measured with the simulated signal, most of the nonlinear least squares are used to search for the optimal solution, and there is a high probability that the solution process will fall into the local optimal solution, which will affect the accuracy and repeatability of the film thickness measurement. The present disclosure uses a genetic algorithm as a fitting method, which can adapt to the change of the initial value and avoid falling into the local optimal solution, thereby improving the accuracy and repeatability of the film thickness measurement. The specific implementation of the above steps 801 to 804 will be further explained below:

[0144] In the above step 802, in the process of obtaining the simulation signal, it is necessary to obtain in advance the initial value and value range of the physical parameters of each film layer in the object to be measured, wherein the initial value of the film thickness can be a nominal value, and the initial values ​​of the other physical parameters can be empirical values. The exemplary value range of each physical parameter can be ±20% of the initial value. Those skilled in the art can also select other suitable value ranges according to actual needs, which are not limited here. Multiple physical parameter combinations are obtained by randomly selecting values ​​in the value range, and the simulation signal δR(t) of the reflectivity change over time corresponding to each physical parameter combination is obtained according to the simulation method of the above-mentioned photoacoustic measurement.

[0145] In the above step 804, Fig.10 According to an embodiment of the present disclosure, a flow chart of iterating a physical parameter combination using a genetic algorithm based on a plurality of first error values ​​until a second error value between a simulated signal δR(t) of a reflectivity change over time corresponding to the iterated physical parameter combination and a measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained is shown, as shown in FIG. Fig.10 As shown, it may specifically include:

[0146] Step 1001: Compare the first error value with the deviation threshold, discard the physical parameter combination corresponding to the first error value greater than the deviation threshold, and retain the remaining physical parameter combinations. The first error value between the simulated signal δR(t) of the reflectivity change over time and the measured reflectivity change signal includes one of the standard deviation of the measured signal and the simulated signal, the mean square error of the measured signal and the simulated signal, and the root mean square of the measured signal and the simulated signal, which are not limited here.

[0147] It is understandable that in the above step 1001, the setting of the deviation threshold will affect the genetic iteration speed and fitting accuracy. Those skilled in the art can select a suitable deviation threshold according to actual conditions, which will not be elaborated here.

[0148] Step 1002: Perform parameter exchange operation and / or parameter mutation operation on the remaining physical parameter combinations to generate several next-generation physical parameter combinations. The next-generation physical parameter combinations are different from the remaining physical parameter combinations. In the above step 1002, the parameter exchange operation refers to the exchange of the values ​​of each physical parameter between different physical parameter combinations with a certain probability (exemplarily, such as 1%); the parameter mutation operation refers to the change of the value of each physical parameter in any physical parameter combination with a certain probability (exemplarily, such as 1%).

[0149] Step 1003: According to the simulation method of photoacoustic measurement provided in the aforementioned embodiment, obtain the simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each next-generation physical parameter combination, and obtain the second error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each next-generation physical parameter combination and the measured reflectivity change signal.

[0150] Step 1004: If the second error value is less than a preset threshold or reaches a minimum value, the iteration ends;

[0151] If the second error value is not less than the preset threshold and has not reached the minimum value, compare the second error value with the deviation threshold, discard the physical parameter combination corresponding to the second error value greater than the deviation threshold, retain the remaining physical parameter combinations, and repeat the above steps 1002 to 1004 until the second error value is less than the preset threshold or reaches the minimum extreme value, and the iteration ends.

[0152] It can be understood that, through the above steps 801 to 804, the final output result obtained is a combination of physical parameters after iterative fitting, which includes not only the thickness of each film layer of the object to be tested, but also other physical parameters of each film layer of the object to be tested except the thickness. These other physical parameters except the thickness can be used to evaluate the coating uniformity of the object to be tested, so as to further monitor the production process level of the object to be tested, and have promotional value.

[0153] However, it is worth noting that although the genetic algorithm can achieve accurate fitting between the simulated signal and the measured signal, each fitting requires a complete genetic iteration process, which takes a relatively long time. Fig.11 According to some embodiments of the present disclosure, another photoacoustic measurement method is provided. Figure 8 The photoacoustic measurement method provided by Fig.11The provided photoacoustic measurement method only needs to perform genetic iteration on other physical parameters except thickness. In the subsequent process of obtaining film thickness, a database can be established based on the genetic iteration results, and the measured signal can be directly matched to the library, which greatly saves the time spent on subsequent film thickness acquisition. Fig.11 As shown, the photoacoustic measurement method may include the following steps:

[0154] Step 1101: Use a photoacoustic measurement device to measure photoacoustic signals on the object to be measured to obtain a measured reflectivity change signal of the object to be measured.

[0155] Step 1102: Obtain several physical parameter combinations of the object to be tested, wherein each physical parameter combination includes the film thickness, and only the film thickness value is the same in any two physical parameter combinations. Exemplarily, in this step, the initial value of the film thickness can be a nominal value, and the initial values ​​of the other physical parameters can be empirical values. The value range of each physical parameter other than the thickness can be ±20% of the initial value. Those skilled in the art can also select other appropriate value ranges according to actual needs, which are not limited here.

[0156] Step 1103: According to the simulation method of photoacoustic measurement provided in the aforementioned embodiment, obtain the simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each physical parameter combination, and obtain the first error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each physical parameter combination and the measured reflectivity change signal.

[0157] Step 1104: Based on a number of first error values, a genetic algorithm is used to iterate the physical parameter combination until the second error value between the simulated signal δR(t) of the reflectivity change over time corresponding to the iterated physical parameter combination and the measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, and the second error value less than the preset threshold or equal to the minimum extreme value is used as the optimized error value, and the physical parameters other than the film thickness are extracted from the physical parameter combination corresponding to the optimized error value as fixed parameters. The specific implementation of step 1104 can refer to the aforementioned steps 1001 to 1004, including:

[0158] Step 1201: refer to the aforementioned step 1001, which will not be described in detail here;

[0159] Step 1202: Perform parameter exchange operations and / or parameter mutation operations on the remaining physical parameter combinations to generate several next-generation physical parameter combinations. The next-generation physical parameter combination is different from the remaining physical parameter combinations, and the film thickness in the next-generation physical parameter combination is the same as the film thickness in the remaining physical parameter combinations. In the above step 1202, the parameter exchange operation refers to the exchange of the values ​​of each physical parameter other than thickness between different physical parameter combinations with a certain probability (exemplarily, such as 1%); the parameter mutation operation refers to the change of the value of each physical parameter other than thickness in any physical parameter combination with a certain probability (exemplarily, such as 1%);

[0160] Step 1203: refer to the aforementioned step 1003, which will not be described in detail here;

[0161] Step 1204: If the second error value is less than a preset threshold or reaches a minimum value, the iteration ends;

[0162] If the second error value is not less than the preset threshold and the minimum value is not obtained, the second error value is compared with the deviation threshold, the physical parameter combinations corresponding to the second error value greater than the deviation threshold are discarded, and the remaining physical parameter combinations are retained. The above steps 1202 to 1204 are repeated until the second error value is less than the preset threshold or the minimum extreme value is obtained, and the iteration ends.

[0163] Step 1105: Keep the fixed parameters, only float the value of the film thickness, and construct several new physical parameter combinations. Among them, only the value of the film thickness is different in any two new physical parameter combinations. Exemplarily, the value range of the film thickness in this step is ±20% of the initial value. Those skilled in the art can also select other suitable value ranges according to actual needs, which is not limited here.

[0164] Step 1106: According to the simulation method of photoacoustic measurement provided in the aforementioned embodiment, obtain the simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each new physical parameter combination, and construct a database of the simulation signal δR(t) of the change of reflectivity over time.

[0165] Step 1107: Using the library matching method, determine in the database the simulated signal δR(t) of the reflectivity change over time that matches the measured reflectivity change signal, and use the physical parameter combination corresponding to the matched simulated signal δR(t) of the reflectivity change over time as the output result of the photoacoustic measurement, and the output result includes the thickness of each layer of the film.

[0166] It can be understood that, based on the aforementioned steps 1101 to 1107, the value of the film thickness parameter is fixed in the genetic iteration stage, and only the other physical parameters of each film layer except the thickness are iteratively fitted; after the other physical parameters of each film layer except the thickness are determined, the corresponding simulation signal database can be established according to different film layer thickness combinations. Specifically, Fig.12 The schematic diagram of the structure of a simulated reflectivity change signal database is shown as an example. Different film layer thickness combinations have different simulated signals δR(t) showing the reflectivity change over time. In the subsequent process of obtaining the film thickness, it is only necessary to compare the measured reflectivity change signal with the database, and select the closest simulation signal. The corresponding film layer thickness combination is the required film thickness measurement value.

[0167] Compared with the solution provided in the aforementioned embodiment, the above-mentioned photoacoustic measurement method only needs to use a genetic algorithm for fitting during the initial measurement to obtain other physical parameters of each film layer except the thickness. On this basis, a database of simulation signals corresponding to different film thickness combinations is constructed, and then the film thickness measurement value can be quickly obtained through library matching. Compared with directly determining the film layer thickness through fitting, the database matching method has less calculation amount, greatly reduces the time required for calculating the film thickness, further improves the measurement speed, further optimizes the practical application effect of the photoacoustic measurement method provided by the present disclosure, and improves the accuracy and repeatability of film thickness measurement.

[0168] In each embodiment provided in the present disclosure, the step numbers are only for the convenience of description and do not limit the specific implementation order of each step.

[0169] In some embodiments of the present disclosure, Fig.13 A schematic diagram of the structure of a photoacoustic measurement device is disclosed, which is used to implement the photoacoustic measurement method provided in the above embodiment. Fig.13 As shown, the photoacoustic measurement device may specifically include:

[0170] The measuring module 1301 is used to perform photoacoustic signal measurement on the object to be measured to obtain a measured reflectivity change signal of the object to be measured.

[0171] The simulation module 1302 is used to obtain a simulation signal δR(t) of the change of reflectivity over time according to the simulation method of photoacoustic measurement provided in the first aspect.

[0172] The calculation module 1303 is used to calculate the Figure 8 As shown or mentioned above Fig.11 The photoacoustic measurement method shown in the figure obtains the output result of the photoacoustic measurement, and the output result includes the thickness of each film layer.

[0173] It is worth noting that although the technical solution provided in the present disclosure is intended to improve the accuracy and convenience of obtaining the film thickness of a multi-layer film object to be tested, the relevant technical solution can also be applied to obtaining the film thickness of a single-layer film object to be tested, and is not limited here.

[0174] In summary, through the technical solution provided by the present disclosure, in the theoretical modeling and simulation stage, there is no need to model layer by layer according to the film layer distribution of the object to be measured, which has the advantages of simplified modeling process, high modeling accuracy, low complexity and strong universality; selecting a genetic algorithm in the stage of fitting the simulation signal and the measured signal can avoid falling into the local optimal solution and improve the fitting accuracy; in the photoacoustic measurement results, in addition to providing accurate film thickness information, it can also provide other physical parameters of each film layer except the thickness, which is helpful for evaluating the uniformity of the coating; in addition, when obtaining the film thickness measurement value, the value of the film thickness can be fixed first, and other physical parameters except the film thickness can be obtained by fitting the genetic algorithm, and then on this basis, a database of simulation signals corresponding to different film thickness combinations can be constructed, and then the film thickness measurement value can be quickly obtained by library matching, which greatly reduces the time required for calculating the film thickness. The technical solution provided by the present disclosure can effectively reduce the complexity of the simulation and fitting process in the photoacoustic measurement, improve the accuracy and repeatability of the film thickness parameter acquisition, save the time required for the film thickness parameter acquisition, and has a popularizable value.

[0175] In addition, the technical solutions of the embodiments of the present disclosure are applicable to both the film thickness measurement of a multi-layer film object to be measured and the film thickness measurement of a single-layer film object to be measured.

[0176] The above content is a further detailed description of the present disclosure in combination with specific preferred implementation modes, and it cannot be determined that the specific implementation of the present disclosure is limited to these descriptions. For ordinary technicians in the technical field to which the present disclosure belongs, several simple deductions or substitutions can be made without departing from the concept of the present disclosure, which should be regarded as falling within the scope of protection of the present disclosure.

Claims

1. A simulation method for photoacoustic measurement, It is characterized in that The steps include: Acquiring system parameters of a photoacoustic measurement device and physical parameters corresponding to an object to be measured, wherein the object to be measured includes several layers of thin films; Establish a dual-temperature model, substitute the system parameters and the physical parameters into the dual-temperature model to obtain the lattice temperature T of the material at any position z in the film thickness direction of the object to be measured at time t under the corresponding parameter conditions l (z,t); The lattice temperature T l (z, t) is derived in the thickness direction of the film to obtain the lattice temperature gradient of the material at the arbitrary position z of the object to be measured; Based on the local physical parameters of the material at the arbitrary position z and the lattice temperature gradient at the arbitrary position z, a partial differential equation of the displacement u(z,t) of the material at the arbitrary position z at time t is established; Obtaining initial conditions and boundary conditions, and solving the partial differential equation based on the initial conditions and the boundary conditions to obtain a displacement u(z,t) of the material at the arbitrary position z at time t; Derivative the displacement u(z, t) of the material at the arbitrary position z at the time t in the thickness direction of the film to obtain the strain η(z, t) of the material at the arbitrary position z at the time t; Based on the local physical parameters of the material at the arbitrary position z and the strain η(z, t) of the material at the arbitrary position z at time t, a simulation signal δR(t) is established to characterize the change of the reflectivity of the object to be measured with time during the measurement process.

2. The method for simulating photoacoustic measurement according to claim 1, It is characterized in that The partial differential equation is expressed as follows: Wherein, ρ(z) is the density of the material at the arbitrary position z, v(z) is the speed of sound propagating through the material at the arbitrary position z, α(z) is the coefficient of thermal expansion of the material at the arbitrary position z, E(z) is the Young's modulus of the material at the arbitrary position z, and γ(z) is the Poisson's ratio of the material at the arbitrary position z.

3. The photoacoustic measurement simulation method according to claim 1 or 2, It is characterized in that The obtaining of initial conditions and boundary conditions comprises: The displacement u(z, 0) of the material at the arbitrary position z at the initial time t=0 is taken as the initial condition, and the initial condition satisfies the following formula: u(z,0)=0; According to the local physical parameters of the material at z=0 on the surface of the surface film of the object to be measured and the lattice temperature T of the material at z=0 on the surface of the surface film of the object to be measured at time t l (0, t), establish boundary conditions, which satisfy the following formula: Among them, B 0 is the bulk modulus of the material at z = 0 on the surface of the surface film, α 0 is the thermal expansion coefficient of the material at z = 0 on the surface of the surface film, ρ 0 is the density of the material at z = 0 on the surface of the surface film, v 0 It is the sound velocity of the material propagating at z=0 on the surface of the surface film.

4. The photoacoustic measurement simulation method according to claim 1 or 2, It is characterized in that The simulation signal δR(t) representing the change of the reflectivity of the object to be measured over time during the measurement process satisfies the following formula: Among them, f(z) is the sensitivity function, which is expressed as follows: In the above formula, f 0 satisfy: In the above formula, ψ satisfies: Where n is the material refractive index, k is the material extinction coefficient, λ is the pump light wavelength, ζ is the pump light absorption depth, c is the speed of light, and ω is the pump light angular frequency.

5. The photoacoustic measurement simulation method according to claim 1 or 2, It is characterized in that The system parameters include at least one or more combinations of wavelength, power, pulse width of the pump light and the probe light and the spot size on the surface of the object to be measured; The physical parameters include at least one or more combinations of the thickness, density, specific heat capacity, Young's modulus, thermal conductivity, refractive index, thermal expansion coefficient, propagation speed of sound, bulk modulus, and Poisson's ratio of each thin film in the object to be measured.

6. A photoacoustic measurement method, It is characterized in that The steps include: Using a photoacoustic measuring device to measure photoacoustic signals of the object to be measured, so as to obtain a measured reflectivity change signal of the object to be measured; Determine the value ranges of several physical parameters of the object to be measured, the physical parameters including the film thickness of the object to be measured, and generate several different physical parameter combinations by randomly selecting values ​​within the value range of each physical parameter; According to the simulation method for photoacoustic measurement according to any one of claims 1 to 5, a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each physical parameter combination is obtained respectively, and a first error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each physical parameter combination and the measured reflectivity change signal is obtained respectively; Based on several of the first error values, a genetic algorithm is used to iterate the physical parameter combination until a second error value between a simulated signal δR(t) of the reflectivity change over time corresponding to the iterated physical parameter combination and the measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, and the second error value that is less than the preset threshold or equal to the minimum extreme value is used as an optimized error value, and the physical parameter combination corresponding to the optimized error value is used as an output result of the photoacoustic measurement, and the output result includes the thickness of each layer of the film.

7. The photoacoustic measurement method according to claim 6, It is characterized in that In the process of iterating the physical parameter combination based on the first error values ​​by using a genetic algorithm until a second error value between a simulated signal δR(t) of a reflectivity change over time corresponding to the iterated physical parameter combination and the measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, the following steps are included: Step 1, comparing the first error value with a deviation threshold, discarding the physical parameter combinations corresponding to the first error value being greater than the deviation threshold, and retaining the remaining physical parameter combinations; Step 2, performing a parameter exchange operation and / or a parameter mutation operation on the remaining physical parameter combinations to generate a plurality of next-generation physical parameter combinations, wherein the next-generation physical parameter combinations are different from the remaining physical parameter combinations; Step 3, according to the simulation method of photoacoustic measurement according to any one of claims 1 to 5, obtaining a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each of the second-generation physical parameter combinations, and respectively obtaining a second error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each of the second-generation physical parameter combinations and the measured reflectivity change signal; Step 4: If the second error value is less than a preset threshold or reaches a minimum value, the iteration ends; If the second error value is not less than the preset threshold and the minimum value is not obtained, the second error value is compared with the deviation threshold, the physical parameter combination corresponding to the second error value greater than the deviation threshold is discarded, and the remaining physical parameter combinations are retained. Steps 2-4 are repeated until the second error value is less than the preset threshold or the minimum extreme value is obtained, and the iteration ends.

8. A photoacoustic measurement method, It is characterized in that The steps include: Using a photoacoustic measuring device to measure photoacoustic signals of the object to be measured, so as to obtain a measured reflectivity change signal of the object to be measured; Acquire several physical parameter combinations of the object to be measured, wherein each of the physical parameter combinations includes a film thickness, and only the film thickness has the same value in any two of the physical parameter combinations; According to the simulation method for photoacoustic measurement according to any one of claims 1 to 5, a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each physical parameter combination is obtained, and a first error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each physical parameter combination and the measured reflectivity change signal is obtained respectively; Based on several first error values, the physical parameter combination is iterated by using a genetic algorithm until a second error value between a simulated signal δR(t) of a reflectivity change over time corresponding to the iterated physical parameter combination and the measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, the second error value less than the preset threshold or equal to the minimum extreme value is used as an optimized error value, and the physical parameters other than the film thickness are extracted from the physical parameter combination corresponding to the optimized error value as fixed parameters; The fixed parameters are maintained, only the value of the film thickness is changed, and several new physical parameter combinations are constructed; According to the simulation method for photoacoustic measurement according to any one of claims 1 to 5, a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each new combination of the physical parameters is obtained, and a database of the simulation signal δR(t) of the change of reflectivity over time is constructed; A library matching method is adopted to determine in the database a simulated signal δR(t) of the reflectivity change over time that matches the measured reflectivity change signal, and the physical parameter combination corresponding to the matched simulated signal δR(t) of the reflectivity change over time is used as the output result of the photoacoustic measurement, and the output result includes the thickness of each layer of the film.

9. The photoacoustic measurement method according to claim 8, It is characterized in that In the process of iterating the physical parameter combination based on the first error values ​​by using a genetic algorithm until a second error value between a simulated signal δR(t) of a reflectivity change over time corresponding to the iterated physical parameter combination and the measured reflectivity change signal is less than a preset threshold or a minimum extreme value is obtained, the following steps are included: Step 1, comparing the first error value with a deviation threshold, discarding the physical parameter combinations whose first error values ​​are greater than the deviation threshold, and retaining the remaining physical parameter combinations; Step 2, performing parameter exchange operation and / or parameter mutation operation on the remaining physical parameter combinations to generate several next-generation physical parameter combinations, wherein the next-generation physical parameter combinations are different from the remaining physical parameter combinations, and the film thickness in the next-generation physical parameter combinations is the same as the film thickness in the remaining physical parameter combinations; Step 3, according to the simulation method of photoacoustic measurement according to any one of claims 1 to 5, obtaining a simulation signal δR(t) of the change of reflectivity over time corresponding to the photoacoustic measurement based on each of the second-generation physical parameter combinations, and respectively obtaining a second error value between the simulation signal δR(t) of the change of reflectivity over time corresponding to each of the second-generation physical parameter combinations and the measured reflectivity change signal; Step 4: If the second error value is less than a preset threshold or reaches a minimum value, the iteration ends; If the second error value is not less than the preset threshold and the minimum value is not obtained, the second error value is compared with the deviation threshold, the physical parameter combinations corresponding to the second error value greater than the deviation threshold are discarded, and the remaining physical parameter combinations are retained. Steps 2-4 are repeated until the second error value is less than the preset threshold or the minimum extreme value is obtained, and the iteration ends.

10. A photoacoustic measurement device, It is characterized in that include: A measuring module, used to perform photoacoustic signal measurement on the object to be measured to obtain a measured reflectivity change signal of the object to be measured; A simulation module, used for obtaining a simulation signal δR(t) of the change of the reflectivity over time according to the simulation method for photoacoustic measurement according to any one of claims 1 to 5; A calculation module is used to obtain an output result of the photoacoustic measurement according to the photoacoustic measurement method according to any one of claims 6 to 9, wherein the output result includes the thickness of each thin film layer.

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