Gap measurement control system, gap measurement system, calibration method and measurement method

Abstract

The invention provides a gap measurement control system, a gap measurement system, a calibration method and a measurement method, and the system comprises a spectrum correction module which is configured to calculate the reflectivity of an interference spectrum based on a background spectrum and a reference spectrum which are obtained in advance, and carry out the normalization processing of the reflectivity of the interference spectrum; the parameter optimization module is configured to optimize the thickness and the dielectric constant of the reflecting film layer of the pattern forming device based on the normalized interference spectrum reflectivity to obtain the optimized thickness and the optimized dielectric constant of the reflecting film layer; and the optical path difference analysis module is configured to obtain a simulation interference spectrum based on the optimized thickness of the reflecting film layer and the optimized dielectric constant, perform optical path difference calculation on an interference spectrum corresponding to the obtained sample to be measured based on the simulation interference spectrum, and obtain gap measurement data.

Description

Technical Field

[0001] The present disclosure relates to the technical field of gap measurement, and in particular to a gap measurement control system, a gap measurement system, a calibration method and a measurement method. Background Art

[0002] At present, the main calculation methods for white light interferometry gap measurement mainly include: peak detection method, Fourier transform and cross-correlation calculation. Among them, the main disadvantages of the peak detection method are low resolution and low accuracy. The resolution of Fourier transform white light interferometry measurement is improved compared with peak detection, and it also avoids the introduction of measurement errors during peak detection, but it is difficult to take into account both detection efficiency and detection accuracy at the same time. The resolution of the cross-correlation calculation method depends on the scanning resolution of the simulated spectrum, so it has extremely high detection accuracy, but as the resolution increases, the calculation efficiency decreases.

[0003] The gap measurement device with nanometer-level measurement accuracy inevitably has measurement errors, but there is no mature method to calibrate the measurement errors of the gap measurement device. At the same time, the thickness and dielectric constant of the reflective film layer of the pattern forming device used cannot be accurately measured. Therefore, there is a large error between the interference spectrum obtained by simulating the theoretical thickness and dielectric constant of the reflective film layer and the actual interference spectrum, which ultimately reduces the accuracy of gap detection. Summary of the invention

[0004] In view of this, the first aspect of the embodiment of the present disclosure provides a gap measurement control system, including: a spectral correction module, configured to calculate the interference spectrum reflectance based on a pre-acquired background spectrum and a reference spectrum, and normalize the interference spectrum reflectance; a parameter optimization module, configured to optimize the reflection film layer thickness and the dielectric constant of the pattern forming device based on the normalized interference spectrum reflectance, and obtain an optimized reflection film layer thickness and an optimized dielectric constant; an optical path difference analysis module, configured to simulate the optimized reflection film layer thickness and the optimized dielectric constant to obtain a simulated interference spectrum, perform optical path difference calculation on the interference spectrum corresponding to the obtained sample to be measured based on the simulated interference spectrum, and obtain gap measurement data.

[0005] According to an embodiment of the present disclosure, it also includes: a gap calibration module, which is configured to calculate the simulated interference spectrum reflectivity corresponding to the air standard samples of different gaps, calculate the correction coefficient based on the normalized interference spectrum reflectivity corresponding to the air standard samples and the simulated interference spectrum reflectivity, and calibrate the gap measurement system based on the correction coefficient.

[0006] According to an embodiment of the present disclosure, the spectral correction module calculates the interference spectrum reflectance based on the pre-acquired reference spectrum and background spectrum, including: using a rigorous coupled wave analysis method to calculate the reflectance of the reference spectrum; calculating the interference spectrum reflectance based on the reference spectrum and reflectance, the background spectrum and the interference spectrum.

[0007] According to an embodiment of the present disclosure, a parameter optimization module optimizes the thickness and dielectric constant of a reflective film layer of a pattern forming device based on the normalized interference spectrum reflectivity to obtain an optimized reflective film layer thickness and an optimized dielectric constant, including: initializing the reflective film layer thickness and the dielectric constant; using a rigorous coupled wave analysis method to calculate a reflectivity model library based on the initialized reflective film layer thickness and the initialized dielectric constant, wherein the reflectivity model library includes simulated interference spectrum reflectivities corresponding to different gaps; calculating the fitness of a particle population based on the normalized interference spectrum reflectivity and the simulated interference spectrum reflectivity with the highest correlation with the interference spectrum reflectivity; updating the reflective film layer thickness and the dielectric constant, and repeatedly calculating the particle population fitness until the particle population fitness meets a preset condition; and using the reflective film layer thickness and the dielectric constant corresponding to the particle population fitness that meets the preset condition as the optimized reflective film layer thickness and the optimized dielectric constant.

[0008] According to an embodiment of the present disclosure, based on the normalized interference spectrum reflectance and the simulated interference spectrum reflectance with the highest correlation with the interference spectrum reflectance, the particle population fitness is calculated, including:

[0009]

[0010] Calculate the particle population fitness Fitness1, where: is the simulated interference spectrum reflectance with the highest correlation with the interference spectrum reflectance, is the normalized interference spectrum reflectance of the sample to be tested, and λ is the wavelength.

[0011] According to an embodiment of the present disclosure, the air standard includes a first base layer, a first reflective film layer, a gap, a second reflective film layer and a second base layer stacked in sequence; the gap calibration module calculates the simulated interference spectrum reflectance corresponding to the air standard with different gaps, and calculates the correction coefficient based on the normalized interference spectrum reflectance corresponding to the air standard and the simulated interference spectrum reflectance, including: using a rigorous coupled wave analysis method to calculate the simulated interference spectrum reflectance corresponding to the air standard with different gaps; using a particle swarm algorithm to optimize the gap value, the thickness of the reflective film layer and the dielectric constant of the pattern forming device based on the normalized interference spectrum reflectance corresponding to the air standard to obtain a simulated gap value, and calculating the correction coefficient of the gap measurement system by comparing the relationship between the gap value in the air standard and the simulated gap value.

[0012] According to an embodiment of the present disclosure, the gap value, the thickness of the reflective film layer and the dielectric constant of the pattern forming device are optimized based on the normalized interference spectrum reflectance corresponding to the air standard sample to obtain a simulated gap value, and the correction coefficient of the gap measurement system is calculated by comparing the relationship between the gap value in the air standard sample and the simulated gap value, including: calculating the root mean square error between the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps; when the root mean square error is less than a set threshold or the number of iterations of the particle swarm algorithm reaches a preset number, calculating the correction coefficient based on the relationship between the gap value of the air standard sample and the simulated gap value in the gap measurement data.

[0013] According to an embodiment of the present disclosure, calculating the root mean square error between the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps includes:

[0014]

[0015] Calculate the root mean square error Fitness1, where r op is the simulated interference spectrum reflectance corresponding to the air standard sample, is the normalized interference spectrum reflectance corresponding to the air standard sample, and λ is the wavelength.

[0016] According to an embodiment of the present disclosure, the optical path difference analysis module calculates the optical path difference of the acquired interference spectrum based on the simulated interference spectrum, including: training a machine learning model based on the simulated interference spectrum, calculating the optical path difference of the interference spectrum corresponding to the sample to be tested based on the trained machine learning model, and obtaining gap measurement data.

[0017] According to an embodiment of the present disclosure, the spectrum correction module is further configured to: denoise and normalize the interference spectrum.

[0018] A second aspect of the embodiments of the present disclosure provides a gap measurement system, including: a light source, a pattern forming device, a wafer stage, a workpiece stage, a spectrometer and a control system; the control system adopts the above-mentioned gap measurement control system; the wafer stage is configured to carry a sample to be measured, and the workpiece stage is configured to adjust the position of the wafer stage; the light source is configured to generate incident light, and the incident light is irradiated on the sample to be measured through the pattern forming device, generating an interference spectrum between the pattern forming device and the sample to be measured; the spectrometer is configured to collect the interference spectrum; the control system is configured to obtain gap measurement data based on the interference spectrum.

[0019] The third aspect of the disclosed embodiment provides a calibration method for calibrating the above-mentioned gap measurement system, including: controlling the spectrometer to collect the background spectrum and the interference spectrum corresponding to the air standard sample through the control system, calculating the interference spectrum reflectance corresponding to the air standard sample based on the background spectrum and the interference spectrum corresponding to the air standard sample, and normalizing the interference spectrum reflectance corresponding to the air standard sample; using a rigorous coupled wave analysis method to calculate the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps; using a particle swarm algorithm to optimize the gap value of the air standard sample, the thickness of the reflective film layer and the dielectric constant of the pattern forming device based on the normalized interference spectrum reflectance corresponding to the air standard sample to obtain a simulated gap value, and calculating the correction coefficient of the gap measurement system by comparing the relationship between the gap value of the air standard sample and the simulated gap value; and correcting the gap measurement data based on the correction coefficient.

[0020] A fourth aspect of an embodiment of the present disclosure provides a gap measurement method, which performs gap measurement based on the above-mentioned gap measurement system, including: controlling a spectrometer through a control system to collect a background spectrum and a reference spectrum corresponding to a sample to be measured, calculating an interference spectrum reflectance corresponding to the sample to be measured based on the background spectrum and the reference spectrum corresponding to the sample to be measured, and normalizing the interference spectrum reflectance corresponding to the sample to be measured; optimizing a reflection film layer thickness and a dielectric constant of a pattern forming device based on the normalized interference spectrum reflectance corresponding to the sample to be measured, and obtaining an optimized reflection film layer thickness and an optimized dielectric constant; after the workpiece stage moves to a range of gap measurement, controlling a spectrometer through a control system to collect an interference spectrum generated between the pattern forming device and the sample to be measured; simulating and generating a simulated interference spectrum based on the optimized reflection film layer thickness and the optimized dielectric constant through a control system, training a machine learning model based on the simulated interference spectrum, and calculating an optical path difference on the interference spectrum corresponding to the sample to be measured based on the trained machine learning model to obtain gap measurement data.

[0021] The gap measurement control system, gap measurement system, calibration method and measurement method provided by the embodiments of the present disclosure have at least the following technical effects:

[0022] The strict coupled wave analysis method is used to optimize the calculation of the thickness and dielectric constant of the reflective film layer of the pattern forming device, which solves the thickness analysis error under small gaps caused by inaccurate reflective film layer parameters, thereby improving the accuracy of gap measurement. The use of interference spectrum optical path difference calculation based on machine learning model can solve the problem of low gap measurement efficiency caused by thickness scanning, and improve the detection efficiency and real-time feedback performance of gap measurement. Different air gap standard samples are prepared by optical connection method, and then the correction coefficient is calculated based on the simulated spectral reflectivity and actual spectral reflectivity corresponding to different air gap standard samples to correct the gap measurement data, which solves the fixed analysis error caused by nonlinearity that may exist in interference spectrum measurement under small gaps, and improves the accuracy of spectral analysis under small gaps. In general, the gap measurement system, gap measurement method and calibration method provided by the embodiments of the present disclosure can take into account both detection efficiency and detection accuracy, and realize high-precision and high-efficiency gap measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0024] Figure 1 The structure diagram of a gap measurement control system according to an embodiment of the present disclosure is schematically shown.

[0025] Figure 2 The structure diagram of a gap measurement control system according to another embodiment of the present disclosure is schematically shown.

[0026] Figure 3 The structure diagram of the gap measurement system according to the embodiment of the present disclosure is schematically shown.

[0027] Figure 4 The film layer structure diagram of the pattern forming device according to an embodiment of the present disclosure is schematically shown.

[0028] Figure 5 The structure of an air gap standard sample (referred to as air standard sample) according to an embodiment of the present disclosure is schematically shown.

[0029] Figure 6 A flow chart of a calibration algorithm according to an embodiment of the present disclosure is schematically shown.

[0030] Figure 7 The figure schematically shows a flow chart for optimizing the dielectric constant and the thickness of the reflective film layer of the pattern forming device according to an embodiment of the present disclosure.

[0031] Figure 8 The figure schematically shows a training and calculation flow chart of a machine learning model according to an embodiment of the present disclosure.

[0032] Fig. 9 The diagram schematically shows the collected original spectrum when the gap is 9.6 μm according to an embodiment of the present disclosure.

[0033] Fig.10 The diagram schematically shows a spectrum diagram of the collected original spectrum after passing through the spectrum correction module when the gap is 9.6 μm according to an embodiment of the present disclosure.

[0034] Fig.11 The diagram schematically shows a comparison of the measured spectrum and the simulated spectrum before the Cr layer thickness is optimized according to an embodiment of the present disclosure.

[0035] Fig.12 The diagram schematically shows a comparison of the measured spectrum and the simulated spectrum before the Cr layer thickness is optimized according to an embodiment of the present disclosure.

[0036] Fig.13 The diagram schematically shows the variation of intensity with frequency after the interference spectrum according to an embodiment of the present disclosure is converted into the frequency domain.

[0037] Fig.14 The diagram schematically shows a visualization diagram of principal component analysis after the interference spectrum according to an embodiment of the present disclosure is converted into the frequency domain.

[0038] Fig.15 The diagram schematically shows the final gap value diagram obtained by spectral analysis using the SVR model according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present disclosure.

[0040] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0041] In the present disclosure, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or can communicate with each other; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0042] In the description of the present disclosure, it is necessary to understand that the terms "longitudinal", "length", "circumferential", "front", "rear", "left", "right", "top", "bottom", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the subsystem or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present disclosure.

[0043] Throughout the drawings, the same elements are represented by the same or similar reference numerals. Conventional structures or configurations will be omitted when they may cause confusion in the understanding of the present disclosure. The shapes, sizes, and positional relationships of the components in the drawings do not reflect the actual size, proportion, and actual positional relationship. In addition, in the claims, any reference symbol between brackets shall not be construed as a limitation to the claims.

[0044] Similarly, in order to simplify the present disclosure and help understand one or more of the various disclosed aspects, in the above description of the exemplary embodiments of the present disclosure, the various features of the present disclosure are sometimes grouped together into a single embodiment, figure, or description thereof. The description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0045] 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 the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the feature. In the description of the present disclosure, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0046] The gap measurement control system, gap measurement system, calibration method and measurement method provided by the embodiments of the present disclosure will be explained in detail below with reference to specific drawings.

[0047] Figure 1 The structural block diagram of a gap measurement control system according to an embodiment of the present disclosure is schematically shown.

[0048] like Figure 1 As shown, the gap measurement control system of this embodiment may include: a spectrum correction module, a parameter optimization module and an optical path difference analysis module.

[0049] The spectrum correction module is configured to calculate the interference spectrum reflectance based on the pre-acquired background spectrum and reference spectrum, and perform normalization processing on the interference spectrum reflectance.

[0050] The parameter optimization module is configured to optimize the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the normalized interference spectrum reflectivity to obtain an optimized thickness of the reflective film layer and an optimized dielectric constant.

[0051] The optical path difference analysis module is configured to obtain a simulated interference spectrum based on the optimized reflective film thickness and the optimized dielectric constant simulation, calculate the optical path difference of the interference spectrum corresponding to the obtained sample to be tested based on the simulated interference spectrum, and obtain gap measurement data.

[0052] Figure 2 The structural block diagram of a gap measurement control system according to another embodiment of the present disclosure is schematically shown.

[0053] like Figure 2 As shown, the gap measurement control system of this embodiment includes, in addition to a spectral correction module, a parameter optimization module and an optical path difference analysis module, further including: a gap calibration module, configured to calculate the simulated interference spectrum reflectance corresponding to air standards of different gaps, calculate a correction coefficient based on the normalized interference spectrum reflectance corresponding to the air standards and the simulated interference spectrum reflectance, and calibrate the gap measurement system based on the correction coefficient.

[0054] It can be understood that the spectrum correction module, parameter optimization module and optical path difference analysis module in this embodiment are Figure 1 The functions of the spectral correction module, parameter optimization module and optical path difference analysis module shown are similar or identical and will not be described in detail here.

[0055] Based on the above embodiment, the spectral correction module calculates the interference spectrum reflectance based on the pre-acquired reference spectrum and background spectrum, which may include: using a rigorous coupled wave analysis method to calculate the reflectance of the reference spectrum; calculating the interference spectrum reflectance based on the reference spectrum and reflectance, the background spectrum and the interference spectrum.

[0056] On the basis of the above-mentioned embodiment, the parameter optimization module optimizes the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the normalized interference spectrum reflectivity to obtain the optimized reflective film layer thickness and the optimized dielectric constant, including: initializing the reflective film layer thickness and the dielectric constant; using a rigorous coupled wave analysis method to calculate a reflectivity model library according to the initialized reflective film layer thickness and the initialized dielectric constant, wherein the reflectivity model library includes simulated interference spectrum reflectivities corresponding to different gaps; calculating the fitness of the particle population based on the normalized interference spectrum reflectivity and the simulated interference spectrum reflectivity with the highest correlation with the interference spectrum reflectivity; updating the reflective film layer thickness and the dielectric constant, and repeatedly calculating the particle population fitness until the particle population fitness meets the preset conditions; and using the reflective film layer thickness and the dielectric constant corresponding to the particle population fitness that meets the preset conditions as the optimized reflective film layer thickness and the optimized dielectric constant.

[0057] It should be noted that different gaps refer to different gaps between the pattern forming device and the wafer. In the parameter optimization module, the two reflectivities, the interference spectrum reflectivity after normalization and the simulated interference spectrum reflectivity with the highest correlation with the interference spectrum reflectivity, correspond to the same pattern forming device and the sample to be tested.

[0058] On the basis of the above embodiment, the air standard includes a first substrate layer, a first reflective film layer, a gap, a second reflective film layer and a second substrate layer stacked in sequence; the gap calibration module calculates the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps, and calculates the correction coefficient based on the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance, including: using a rigorous coupled wave analysis method to calculate the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps; using a particle swarm algorithm to optimize the gap value, the thickness of the reflective film layer and the dielectric constant of the pattern forming device based on the normalized interference spectrum reflectance corresponding to the air standard sample to obtain a simulated gap value (i.e., simulated air thickness), and calculating the correction coefficient of the gap measurement system by comparing the relationship between the gap value in the air standard sample and the simulated gap value.

[0059] Based on the above embodiment, the optical path difference analysis module calculates the optical path difference of the acquired interference spectrum based on the simulated interference spectrum, which may include: training a machine learning model based on the simulated interference spectrum, calculating the optical path difference of the interference spectrum corresponding to the sample to be tested based on the trained machine learning model, and obtaining gap measurement data.

[0060] It should be noted that further possible implementation details of the spectrum correction module, parameter optimization module, optical path difference analysis module and gap calibration module will be described in detail later when introducing the gap measurement system.

[0061] Figure 3 The structure diagram of the gap measurement system according to the embodiment of the present disclosure is schematically shown.

[0062] like Figure 3 As shown, the gap measurement system of this embodiment includes: a light source 1, a wafer stage 5, a workpiece stage 6, a spectrometer 7 and a control system 8.

[0063] The light source 1 is configured to generate incident light. In a specific example, the light source 1 may be a white light source, generating white light as the incident light. The incident light is irradiated onto the sample 4 through the pattern forming device 2, generating an interference spectrum between the pattern forming device 2 and the sample 4.

[0064] The wafer stage 5 is configured to carry the sample 4 to be tested, and the workpiece stage 6 is configured to adjust the position of the wafer stage 5, thereby adjusting the position of the sample 4 to be tested. The sample 4 to be tested can move or rotate in the horizontal direction and the vertical direction.

[0065] The spectrometer 7 is configured to collect the interference spectrum generated by the incident light between the pattern forming device 2 and the sample to be measured 4 and to collect the interference spectrum corresponding to the air standard sample.

[0066] Control system 8 adopts Figure 1 or Figure 2 The control system shown is configured to use a spectral correction module and a gap calibration module to calibrate the gap measurement system based on the interference spectrum corresponding to the air standard sample; use the spectral correction module and the parameter optimization module to obtain the optimized reflection film layer thickness and dielectric constant, and further obtain the optimized simulated interference spectrum; train the machine learning model based on the optimized simulated interference spectrum, and calculate the optical path difference of the interference spectrum corresponding to the sample to be measured based on the trained machine learning model to obtain gap measurement data.

[0067] Based on the above embodiments, continue to refer to Figure 3 The gap measurement system may further include: a suction cup 3, configured to mount the pattern forming device 2, so that the pattern forming device 2 is placed above the sample to be measured 4. It should be understood that the structure for mounting the pattern forming device 2 is not limited to the suction cup 3, and it is sufficient to be able to stably place the pattern forming device 2 above the sample to be measured 4. The sample to be measured 4 may be, for example, a wafer.

[0068] On the basis of the above embodiment, the spectrometer 7 is further configured to collect a reference spectrum and a background spectrum.

[0069] Before the gap measurement officially begins, the gap measurement system can be calibrated. By measuring the gap value in the air standard sample through the gap measurement system, the simulated interference spectrum of the air standard sample can be corrected to eliminate the fixed deviation of the gap measurement system and improve the measurement accuracy.

[0070] The calibration process includes: initialization, which may include background spectrum acquisition and reference spectrum acquisition. For example, before the air standard is installed, the control system 8 controls the spectrometer 7 to collect background light and save it in the control system 8. After installing any pattern forming device and any sample 4 to be tested, the control system 8 turns on the light source, controls the worktable 6 to move upward to a preset position, controls the spectrometer 7 to collect a reference spectrum, and saves it in the control system 8. The preset position may be a position where the distance between the pattern forming device 2 and the sample 4 to be tested is 250 μm. The preset position may be set specifically according to the actual scenario. Usually, at the preset position, the pattern forming device is in contact with the sample 4 to be tested, such as a gap between the two that is less than or equal to 0.5 mm.

[0071] After initialization, the pattern forming device 2 and the sample to be tested 4 are uninstalled, and an air standard sample (air gap standard sample) can be installed to correct the gap measurement data using the gap calibration module. The control system 8 turns on the light source and controls the spectrometer 7 to collect the interference spectrum corresponding to the air standard sample.

[0072] Calculating the interference spectrum reflectance of the air standard sample, including using a rigorous coupled wave analysis method to calculate the reflectance of a reference spectrum corresponding to the air standard sample; calculating the interference spectrum reflectance corresponding to the air standard sample according to the interference spectrum, background spectrum, reference spectrum and reference spectrum reflectance corresponding to the air standard sample, and normalizing the interference spectrum reflectance corresponding to the air standard sample.

[0073] In a possible implementation of the embodiment of the present disclosure, the formula for calculating the interference spectrum reflectance corresponding to the air standard sample is:

[0074] (1)

[0075] Among them, R ref1 is the reference spectrum corresponding to the air standard, R s1 is the interference spectrum corresponding to the air standard sample collected by spectrometer 7, D is the background spectrum, r ref1 is the reflectance of the reference spectrum corresponding to the air standard, which is calculated using the rigorous coupled wave analysis method, r s1 is the interference spectrum reflectance of the air standard.

[0076] The normalization formula is as follows:

[0077] (2)

[0078] in, is the normalized interference spectrum reflectance of the air standard sample, r s1 is the interference spectrum reflectance of the air standard sample, u1 and σ1 are the mean and variance of the interference spectrum reflectance of the air standard sample, respectively.

[0079] On the basis of the above embodiment, the air standard includes a first base layer, a first reflective film layer, a gap, a second reflective film layer and a second base layer stacked in sequence; the gap calibration module calculates the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps, and calculates the correction coefficient based on the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance, including: using a rigorous coupled wave analysis method to calculate the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps; using a particle swarm algorithm to optimize the gap value, the thickness of the reflective film layer and the dielectric constant of the pattern forming device based on the normalized interference spectrum reflectance corresponding to the air standard sample to obtain a simulated gap value, and calculating the correction coefficient of the gap measurement system by comparing the relationship between the gap value in the air standard sample and the simulated gap value.

[0080] Furthermore, based on the normalized interference spectrum reflectivity corresponding to the air standard sample, the gap value, the thickness of the reflective film layer of the pattern forming device and the dielectric constant are optimized to obtain the simulated air thickness, and by comparing the relationship between the gap value in the air standard sample and the simulated gap value, the correction coefficient of the gap measurement system is calculated, including: calculating the root mean square error between the normalized interference spectrum reflectivity corresponding to the air standard sample and the simulated interference spectrum reflectivity corresponding to the air standard samples with different gaps; when the root mean square error is less than a set threshold or the number of iterations of the particle swarm algorithm reaches a preset number, the correction coefficient is calculated based on the relationship between the gap value of the air standard sample and the simulated gap value in the gap measurement data.

[0081] On the basis of the above embodiment, the parameter optimization module optimizes the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the normalized interference spectrum reflectivity to obtain the optimized thickness and dielectric constant of the reflective film layer, including:

[0082] Initialize the thickness and dielectric constant of the reflective film layer; use a rigorous coupled wave analysis method to calculate the reflectivity model library according to the initialized thickness of the reflective film layer and the initialized dielectric constant, wherein the reflectivity model library includes simulated interference spectrum reflectivities corresponding to different gaps; calculate the fitness of the particle population based on the normalized interference spectrum reflectivity and the simulated interference spectrum reflectivity; update the thickness of the reflective film layer and the dielectric constant, and repeat the operation of calculating the fitness of the particle population until the fitness of the particle population meets the preset conditions; use the thickness of the reflective film layer and the dielectric constant corresponding to the fitness of the particle population that meets the preset conditions as the optimized thickness of the reflective film layer and the optimized dielectric constant.

[0083] Using the gap calibration module, air standard and parameter optimization module to calibrate the gap measurement system can improve the measurement accuracy. When the measurement accuracy is not high, the gap can be measured using only the spectrum correction module, parameter optimization module and optical path difference analysis module. In addition, when optimizing the thickness and dielectric constant of the reflective film layer of the pattern forming device, the parameter optimization module uses the interference spectrum between the collected sample to be measured and the pattern forming device used with it.

[0084] Figure 4 The diagram schematically shows a film layer structure consisting of a pattern forming device and a sample to be tested according to an embodiment of the present disclosure.

[0085] like Figure 4 As shown, the film layer structures are respectively the sample 1-1 to be tested, the gap 1-2, the reflective film layer 1-3 and the base layer 1-4 from bottom to top. In the optical path difference analysis module of the control system 8, the spectral database with different accuracy and detection range is mainly generated by the film layer structure with different gap values. The accuracy of the spectral database determines the detection resolution and accuracy of the system. When the film layer structure has a large gap, the step distance of the gap value can be, for example, 50nm, that is, every 50nm corresponds to a spectrum, so the resolution can be, for example, 50nm, and the corresponding accuracy is low; when the gap is small, the step distance of the air gap can be, for example, 1nm, that is, every 1nm corresponds to a spectrum, so the resolution can be, for example, 1nm, and the corresponding accuracy is high.

[0086] Figure 5 The membrane layer structure diagram of the air standard according to the embodiment of the present disclosure is schematically shown.

[0087] like Figure 5 As shown, the film layer structure of the air standard sample is, from top to bottom, the bottom first base layer 2-1, the first reflection film layer 2-2 (for example, Si reflection film layer), the gap 2-3, the second reflection film layer 2-4 (for example, Cr reflection film layer) and the second base layer 2-5. The gap measurement system is calibrated by the air standard sample.

[0088] Figure 6 A flow chart of a calibration algorithm according to an embodiment of the present disclosure is schematically shown.

[0089] like Figure 6 As shown, in a possible implementation of the embodiment of the present disclosure, first, initialize the particle group parameters, including the population number N1 and the particle speed v1. Initialize the gap value t1, the thickness t2 of the first reflective film layer 2-2, the dielectric constant n1 and ε1, the thickness t3 of the second reflective film layer (such as the Cr layer), the dielectric constant n2 and ε2, wherein n1, ε1, n2 and ε2 are functions of the wavelength. The wavelength range can be, for example, 450nm to 850nm.

[0090] Next, according to the initialized thickness and dielectric constant of the reflective film layer, the reflectivity model library D varying with the optical path difference is simulated using the rigorous coupled-wave analysis method s , where the reflectivity model library D s is a set of reflectivity databases composed of the simulated interference spectral reflectivities corresponding to multiple different gap values.

[0091] Next, calculate the particle fitness. The root mean square error between the normalized interference spectral reflectivity corresponding to the air standard sample and the simulated interference spectral reflectivity corresponding to the air standard sample with different gaps is used as the evaluation index of the particle fitness. The particle fitness can be calculated according to:

[0092] (3)

[0093] where Fitness1 is the particle fitness, r op is the simulated interference spectral reflectivity, is the normalized interference spectral reflectivity of the air standard sample, and λ is the wavelength.

[0094] Update the gap value, the thickness and dielectric constant of the reflective film layer, and repeat to calculate the particle fitness using formula (3) until the particle fitness meets the preset conditions or the number of iterative updates reaches the set threshold.

[0095] The formula for updating the population is:

[0096] (4)

[0097] where c1 and c2 are acceleration factors, r1 and r2 are random numbers, and r 1,2 ϵ[0,1], v1 is the particle velocity, the subscript pbest is the global optimal position, the subscript gbest is the optimal position of the current population, and η is the inertia factor, and its update method is:

[0098] (5)

[0099] where It is the maximum number of iterations, it is the current number of iterations, η ini is the initial inertia weight, and η end is the final inertia weight.

[0100] The particle fitness meeting the preset conditions can be that the set particle fitness is less than a certain set threshold (Fitness1 < F) or the number of iterations reaches the maximum number of iterations (it = It), and this set threshold can be selected according to actual needs. For example, it can be 0.1.

[0101] Next, the simulated gap value is output after reaching the termination condition. By comparing the relationship between the gap value in the actual air standard sample and the simulated gap value, the correction coefficient of the gap measurement system is calculated, and finally the calibration of the gap measurement system is realized.

[0102] By comparing the relationship between the gap value in the actual air standard sample and the simulated gap value, the correction coefficient of the gap measurement system is calculated, and finally the calibration of the gap measurement system is achieved.

[0103] It should be noted that if the particle fitness does not meet the preset conditions, the parameters of the first reflective film layer 2-2, the gap 2-3, and the second reflective film layer 2-4 can be updated, the particle speed and weight can be updated, and the rigorous coupled wave analysis method can be re-used to simulate the reflectivity model library that changes with the optical path difference and then perform iterative calculations until the particle fitness meets the preset conditions.

[0104] After completing the calibration of the gap measurement system, the gap measurement system is used to measure the gap between the pattern forming device and the sample to be tested 4. Initialization, initialization may include background spectrum acquisition and reference spectrum acquisition. Specifically, before the pattern forming device 2 and the sample to be tested 4 are installed, the control system 8 controls the spectrometer 7 to collect the background spectrum and save it in the control system 8. After any pattern forming device 2 and any sample to be tested 4 are installed, the control system 8 turns on the light source, controls the workpiece stage 6 to move upward to a preset position, controls the spectrometer 7 to collect the reference spectrum, and saves it in the control system 8. The preset position can be the distance between the pattern forming device 2 and the sample to be tested 4, for example, it can be 250 μm, which is specifically set according to the actual scene. Usually, at the preset position, the pattern forming device and the sample to be tested 4 are in contact, such as the gap between the two is less than or equal to 0.5 mm.

[0105] After initialization, the formal pattern forming device 2 and the sample to be tested 4 are installed to measure the gap value between the two. When the workpiece stage 6 moves to the range of the gap measurement, the control system 8 receives the interference spectrum transmitted by the spectrometer 7. The particle swarm algorithm is used to optimize the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the reflectivity of the interference spectrum to obtain the optimized thickness and dielectric constant of the reflective film layer. The rigorous coupled wave analysis method is used to obtain the simulated interference spectrum based on the accurate thickness and dielectric constant of the reflective film layer after optimization.

[0106] Correcting the interference spectrum of the sample to be tested includes calculating the reference spectrum reflectance corresponding to the sample to be tested by a strict coupled wave analysis method; calculating the interference spectrum reflectance corresponding to the sample to be tested based on the interference spectrum, background spectrum, reference spectrum and reference spectrum reflectance, and normalizing the interference spectrum reflectance corresponding to the sample to be tested.

[0107] In a possible implementation of the embodiment of the present disclosure, the formula for calculating the interference spectrum reflectance corresponding to the sample to be tested is:

[0108] (6)

[0109] Among them, R ref2 is the reference spectrum corresponding to the sample 4 to be tested, R s2 is the interference spectrum corresponding to the sample 4 to be tested collected by the spectrometer 7, D is the background spectrum, r ref2 is the reference spectral reflectance corresponding to the sample 4 to be tested, which is calculated using the rigorous coupled wave analysis method, r s2 is the interference spectrum reflectivity corresponding to the sample 4 to be tested.

[0110] The normalization formula is as follows:

[0111] (7)

[0112] in, is the normalized interference spectrum reflectance of the sample 4 to be tested, r s2 is the interference spectrum reflectance corresponding to the sample 4 to be tested, u2 and σ2 are the mean and variance of the interference spectrum reflectance of the sample 4 to be tested, respectively.

[0113] On the basis of the above embodiment, a particle swarm algorithm is used to optimize the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the interference spectrum reflectivity corresponding to the sample to be tested, to obtain the optimized thickness and dielectric constant of the reflective film layer, and further to obtain the optimized accurate simulated interference spectrum, which may include:

[0114] Initialize the gap value, the thickness of the reflective film layer and the dielectric constant. Use a rigorous coupled wave analysis method to calculate the reflectivity model library according to the initialized gap value, the thickness of the reflective film layer and the dielectric constant, wherein the reflectivity model library includes simulated interference spectrum reflectivities corresponding to different gap values. Calculate the fitness of the particle population based on the normalized interference spectrum reflectivity corresponding to the sample to be tested and the simulated spectrum reflectivity with the highest correlation with the interference spectrum reflectivity. Update the thickness of the reflective film layer and the dielectric constant, and repeat the operation of calculating the fitness of the particle population until the fitness of the particle population meets the preset conditions. The thickness of the reflective film layer and the dielectric constant corresponding to the fitness of the particle population that meets the preset conditions are used as the optimized thickness of the reflective film layer and the optimized dielectric constant.

[0115] Figure 7 The figure schematically shows a flow chart for optimizing the dielectric constant and the thickness of the reflective film layer of the pattern forming device according to an embodiment of the present disclosure.

[0116] like Figure 7As shown, in a possible implementation of the embodiment of the present disclosure, first, initialize the particle group parameters, including the population number N2 and the particle velocity v2. Initialize the reflective film layer thickness t4 and the dielectric constants n3 and ε3 of the reflective film layer, where n3 and ε3 are functions of the wavelength.

[0117] Next, according to the initialized reflective film thickness and dielectric constant, the rigorous coupled wave analysis method is used to simulate the reflectivity model library D that changes with the optical path difference. s , where the reflectivity model library D s It is a set of data consisting of the reflectance of the simulated interference reflection spectrum of multiple different gap values ​​corresponding to the sample to be tested.

[0118] Next, the fitness of the seed particle population can be calculated according to:

[0119] (8)

[0120] Calculate the particle population fitness Fitness2, where: is the simulated interference spectrum reflectance with the highest correlation with the interference spectrum reflectance, is the normalized interference spectrum reflectance of the sample to be tested, and λ is the wavelength.

[0121] Next, the thickness and dielectric constant of the reflective film layer are updated, and the operation of calculating the fitness of the particle population using formula (8) is repeated until the fitness of the particle population meets the preset conditions.

[0122] The formula for updating the population is:

[0123] (9)

[0124] Among them, c1 and c2 are acceleration factors, r1 and r2 are random numbers, and r 1,2 ϵ[0,1], ν is the particle velocity, the subscript pbest is the global optimal position, the subscript gbest is the current population optimal position, η is the inertia factor, and its update method is:

[0125] (10)

[0126] Among them, It is the maximum number of iterations, it is the current number of iterations, η ini is the initial inertia weight, η end is the final inertia weight.

[0127] Based on the above iterative update calculation, the optimized reflective film thickness t is finally output. op , the optimized dielectric constant n op and ε op , using the thickness of the reflective film t op, the optimized dielectric constant n op and ε op Re-substitute the rigorous coupled wave analysis algorithm to generate the reflectivity model library.

[0128] On the basis of the above embodiment, in order to improve the speed of gap measurement, model training based on machine learning algorithm is adopted. Therefore, the final analysis efficiency is related to the complexity of the model and has nothing to do with the size of the database itself.

[0129] Figure 8 The figure schematically shows a training and calculation flow chart of a machine learning model according to an embodiment of the present disclosure.

[0130] like Figure 8 As shown, the process of training a machine learning model based on simulated interference spectroscopy can be:

[0131] First, the simulated interference spectrum is normalized. The normalized calculation method can be

[0132] (11)

[0133] Among them, R p To simulate the interference spectrum, u3 and σ3 are the mean and variance of the simulated interference spectrum, respectively.

[0134] Then, feature extraction is performed: Fourier transform is performed on the simulated interference spectrum, the simulated interference spectrum is transferred to the frequency domain, and then principal component analysis is performed. The extracted principal components are trained using support vector machine regression (SVR) to obtain the final analytical model.

[0135] After the machine learning model is trained, the optical path difference calculation of the interference spectrum based on the trained machine learning model may include:

[0136] The collected interference spectrum is preprocessed. The preprocessing includes denoising and normalization. The noise is eliminated by wavelet threshold denoising. The normalization calculation method can be

[0137] (12)

[0138] Among them, R s is the interference spectrum, u4 and σ4 are the mean and variance of the interference spectrum respectively.

[0139] Then, feature extraction is performed: Fourier transform is performed on the interference spectrum, the interference spectrum is transferred to the frequency domain, and then principal component analysis is performed. The extracted principal components can explain 99.9% of the frequency domain signals. The extracted principal components are trained using support vector machine regression (SVR) to obtain the final analytical model.

[0140] Finally, the signal after principal component analysis is input into the optimized analytical model and the optical path difference is output.

[0141] In order to verify the accuracy of gap measurement, air standards with different gaps can be made for detection and calibration.

[0142] In summary, the gap measurement system provided by the embodiment of the present disclosure can work in a gap measurement state and a calibration state. When working in the gap measurement state, the collected interference spectrum is first spectrally corrected, and then the parameters of the pattern forming device are optimized based on the corrected interference spectrum, and finally the optical path difference is calculated using the optimized pattern forming device parameters to obtain dynamic gap measurement data. In the calibration state, the simulated interference spectrum corresponding to the air standard samples of different gaps is first corrected, and then the correction coefficient is calculated based on the corrected simulated interference spectrum to obtain the fixed deviation of the system.

[0143] Based on the above gap measurement system, an embodiment of the present disclosure further provides a calibration method for the gap measurement system, which may include:

[0144] The control system controls the spectrometer to collect the interference spectrum corresponding to the background spectrum and the air standard sample, calculates the interference spectrum reflectance corresponding to the air standard sample based on the background spectrum and the interference spectrum corresponding to the air standard sample, and normalizes the interference spectrum reflectance corresponding to the air standard sample.

[0145] The rigorous coupled wave analysis method is used to calculate the simulated interference spectrum reflectance corresponding to air standards with different gaps.

[0146] The particle swarm algorithm is used to optimize the gap value of the air standard sample, the thickness of the reflective film layer of the pattern forming device and the dielectric constant based on the normalized interference spectrum reflectivity corresponding to the air standard sample to obtain the simulated gap value. By comparing the relationship between the gap value of the air standard sample and the simulated gap value, the correction coefficient of the gap measurement system is calculated.

[0147] The gap measurement data is corrected based on the correction factor.

[0148] Based on the above gap measurement system, an embodiment of the present disclosure further provides a gap measurement method based on the gap measurement system, and the measurement method may include:

[0149] The control system controls the spectrometer to collect the background spectrum and the reference spectrum corresponding to the sample to be tested. Based on the background spectrum and the reference spectrum corresponding to the sample to be tested, the interference spectrum reflectance corresponding to the sample to be tested is calculated, and the interference spectrum reflectance corresponding to the sample to be tested is normalized.

[0150] The thickness and dielectric constant of the reflective film layer of the pattern forming device are optimized based on the normalized interference spectrum reflectivity corresponding to the sample to be tested, so as to obtain the optimized thickness and dielectric constant of the reflective film layer.

[0151] After the workpiece stage moves to within the travel range of the gap measurement, the control system controls the spectrometer to collect the interference spectrum generated between the pattern forming device and the sample to be measured.

[0152] A simulated interference spectrum is generated based on the optimized reflective film thickness and the optimized dielectric constant through the control system, a machine learning model is trained based on the simulated interference spectrum, and the optical path difference is calculated for the interference spectrum corresponding to the sample to be tested based on the trained machine learning model to obtain the gap measurement data.

[0153] It should be noted that the specific implementation details and technical effects of the gap measurement method and calibration method implementation examples are the same as the specific implementation details and technical effects of the gap measurement control system and gap measurement system implementation examples, and will not be repeated here.

[0154] In order to further verify the measurement control system, gap measurement system, calibration method and measurement method provided by the embodiments of the present disclosure, some data are provided below for support.

[0155] Fig. 9 The diagram schematically shows the collected original spectrum when the gap is 9.6 μm according to an embodiment of the present disclosure. Fig.10 The diagram schematically shows a spectrum diagram of the collected original spectrum after passing through the spectrum correction module when the gap is 9.6 μm according to an embodiment of the present disclosure.

[0156] like Fig. 9 and Fig.10 As shown in the figure, after the spectrum correction module, the consistency of the interference spectrum under micron gap is better, thus avoiding the poor stability and analysis error of the subsequent spectrum analysis.

[0157] Fig.11 The figure schematically shows a comparison diagram between the interference spectrum before the optimization of the Cr layer thickness according to an embodiment of the present disclosure and the simulated interference spectrum. Fig.12 The figure schematically shows a comparison diagram between the interference spectrum before the optimization of the Cr layer thickness according to an embodiment of the present disclosure and the simulated interference spectrum.

[0158] like Fig.11 and Fig.12 As shown in the figure, the contrast between the interference spectrum and the simulated interference spectrum before and after optimization is quite different. This is because the unoptimized model is used, and the model error will cause the analytical value to have an analytical error of 10nm-100nm. After optimization, the model is correct and the analytical value is accurate.

[0159] Fig.13The diagram schematically shows the variation of intensity with frequency after the interference spectrum according to an embodiment of the present disclosure is converted into the frequency domain.

[0160] like Fig.13 As shown, after the interference spectrum is converted into the frequency domain, the frequency characteristic peak position corresponds to the gap value, and the accuracy of feature extraction is improved.

[0161] Fig.14 The diagram schematically shows a visualization diagram of principal component analysis after the interference spectrum according to an embodiment of the present disclosure is converted into the frequency domain.

[0162] like Fig.14 As shown, the extracted frequency domain spectrum is subjected to principal component analysis, and the first three principal components are taken for visualization.

[0163] Fig.15 The diagram schematically shows the final gap value diagram obtained by spectral analysis using the SVR model according to an embodiment of the present disclosure.

[0164] like Fig.15 As shown in the figure, the features obtained by principal component analysis are input, and the R-square calculated by the model is close to 1, and the analytical value is accurate.

[0165] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present disclosure in detail. It should be understood that the above are only preferred embodiments of the present disclosure and the technical principles used. Those skilled in the art will understand that the present disclosure is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present disclosure. Therefore, although the present disclosure is described in more detail through the above embodiments, the present disclosure is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present disclosure, all of which belong to the protection scope of the present disclosure.

Claims

1. A gap measurement control system, comprising: The spectrum correction module is configured to calculate the interference spectrum reflectance based on the pre-acquired background spectrum and reference spectrum, and perform normalization processing on the interference spectrum reflectance; A parameter optimization module is configured to optimize the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the normalized interference spectrum reflectivity to obtain an optimized thickness and dielectric constant of the reflective film layer; The optical path difference analysis module is configured to obtain the simulated interference spectrum based on the optimized reflective film layer thickness and the optimized dielectric constant simulation, calculate the optical path difference of the interference spectrum corresponding to the obtained sample to be tested based on the simulated interference spectrum, and obtain gap measurement data.

2. The gap measurement control system according to claim 1, further comprising: The gap calibration module is configured to calculate the simulated interference spectrum reflectance corresponding to the air standard samples of different gaps, calculate the correction coefficient based on the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance, and correct the gap measurement data based on the correction coefficient.

3. The gap measurement control system according to claim 1 or 2, wherein the spectrum correction module calculates the interference spectrum reflectance based on the pre-acquired reference spectrum and background spectrum, comprising: Calculating the reflectivity of the reference spectrum using a rigorous coupled wave analysis method; The interference spectrum reflectance is calculated according to the reference spectrum and the reflectance, the background spectrum and the interference spectrum.

4. The gap measurement control system according to claim 1 or 2, wherein the parameter optimization module optimizes the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the normalized interference spectrum reflectivity to obtain the optimized thickness and dielectric constant of the reflective film layer, including: Initializing the thickness of the reflective film layer and the dielectric constant; A rigorous coupled wave analysis method is used to calculate a reflectivity model library according to an initialized reflective film layer thickness and an initialized dielectric constant, wherein the reflectivity model library includes simulated interference spectrum reflectivities corresponding to different gaps; Calculating the fitness of the particle population based on the normalized interference spectrum reflectance and the simulated interference spectrum reflectance with the highest correlation with the interference spectrum reflectance; Updating the thickness of the reflective film layer and the dielectric constant, and repeatedly calculating the fitness of the particle population until the fitness of the particle population meets a preset condition; The reflective film layer thickness and dielectric constant corresponding to the fitness of the particle population that meets the preset conditions are taken as the optimized reflective film layer thickness and the optimized dielectric constant.

5. The gap measurement control system according to claim 4, wherein the particle population fitness is calculated based on the normalized interference spectrum reflectivity and the simulated interference spectrum reflectivity with the highest correlation with the interference spectrum reflectivity, comprising: according to Calculate the particle population fitness Fitness2, where: is the simulated interference spectrum reflectivity with the highest correlation with the interference spectrum reflectivity, is the normalized interference spectrum reflectance of the sample to be tested, and λ is the wavelength.

6. The gap measurement control system according to claim 2, wherein the air standard sample comprises a first base layer, a first reflection film layer, a gap, a second reflection film layer and a second base layer stacked in sequence; The gap calibration module calculates the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps, and calculates the correction coefficient based on the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance, including: The rigorous coupled wave analysis method is used to calculate the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps; The particle swarm algorithm is used to optimize the gap value, the thickness of the reflective film layer of the pattern forming device and the dielectric constant based on the normalized interference spectrum reflectivity corresponding to the air standard sample to obtain the simulated gap value. By comparing the relationship between the gap value in the air standard sample and the simulated gap value, the correction coefficient of the gap measurement system is calculated.

7. The gap measurement control system according to claim 6, wherein the particle swarm algorithm is used to optimize the gap value, the thickness of the reflective film layer of the pattern forming device and the dielectric constant based on the normalized interference spectrum reflectivity corresponding to the air standard sample to obtain the simulated gap value, and the correction coefficient of the gap measurement system is calculated by comparing the relationship between the gap value in the air standard sample and the simulated gap value, including: Calculate the root mean square error between the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps; When the root mean square error is less than a set threshold or the number of iterations of the particle swarm algorithm reaches a preset number, the correction coefficient is calculated based on the relationship between the gap value of the air standard sample and the simulated gap value in the gap measurement data.

8. The gap measurement control system according to claim 7, wherein the calculating the root mean square error between the normalized interference spectrum reflectance corresponding to the air standard sample and the simulated interference spectrum reflectance corresponding to the air standard samples of different gaps comprises: according to Calculate the root mean square error Fitness1, where r op is the simulated interference spectrum reflectance corresponding to the air standard sample, is the normalized interference spectrum reflectance corresponding to the air standard sample, and λ is the wavelength.

9. The gap measurement control system according to claim 1 or 2, wherein the optical path difference analysis module calculates the optical path difference of the interference spectrum corresponding to the obtained sample to be measured based on the simulated interference spectrum, comprising: A machine learning model is trained based on the simulated interference spectrum, and an optical path difference is calculated for the interference spectrum corresponding to the sample to be tested based on the trained machine learning model to obtain the gap measurement data.

10. The gap measurement control system according to claim 1, wherein the spectrum correction module is further configured to: The interference spectrum is denoised and normalized.

11. A gap measurement system, comprising: Light source, pattern forming device, wafer stage, workpiece stage, spectrometer and control system; The control system adopts the gap measurement control system described in any one of claims 1 to 10; The wafer stage is configured to carry a sample to be tested, and the workpiece stage is configured to adjust the position of the wafer stage; The light source is configured to generate incident light, the incident light is irradiated onto the sample to be tested through the pattern forming device, and an interference spectrum is generated between the pattern forming device and the sample to be tested; The spectrometer is configured to collect the interference spectrum; The control system is configured to acquire gap measurement data based on the interference spectrum.

12. A calibration method for calibrating the gap measurement system according to claim 11, comprising: Controlling the spectrometer to collect the background spectrum and the interference spectrum corresponding to the air standard sample through the control system, calculating the interference spectrum reflectance corresponding to the air standard sample based on the background spectrum and the interference spectrum corresponding to the air standard sample, and normalizing the interference spectrum reflectance corresponding to the air standard sample; The rigorous coupled wave analysis method is used to calculate the simulated interference spectrum reflectance corresponding to the air standard samples with different gaps; Using a particle swarm algorithm, based on the normalized interference spectrum reflectivity corresponding to the air standard sample, the gap value of the air standard sample, the thickness of the reflective film layer of the pattern forming device, and the dielectric constant are optimized to obtain a simulated gap value, and by comparing the relationship between the gap value in the air standard sample and the simulated gap value, a correction coefficient of the gap measurement system is calculated; The gap measurement data is corrected based on the correction factor.

13. A gap measurement method, based on the gap measurement system of claim 11, comprising: Controlling the spectrometer to collect a background spectrum and a reference spectrum corresponding to the sample to be tested by a control system, calculating the interference spectrum reflectance corresponding to the sample to be tested based on the background spectrum and the reference spectrum corresponding to the sample to be tested, and normalizing the interference spectrum reflectance corresponding to the sample to be tested; Optimizing the thickness and dielectric constant of the reflective film layer of the pattern forming device based on the normalized interference spectrum reflectivity corresponding to the sample to be tested, to obtain an optimized thickness and dielectric constant of the reflective film layer; After the workpiece stage moves to within the travel range of the gap measurement, the control system controls the spectrometer to collect the interference spectrum generated between the pattern forming device and the sample to be measured; A simulated interference spectrum is generated based on the optimized reflective film layer thickness and the optimized dielectric constant through a control system, a machine learning model is trained based on the simulated interference spectrum, and the optical path difference of the interference spectrum corresponding to the sample to be tested is calculated based on the trained machine learning model to obtain gap measurement data.

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