Structure measurement method and device of integrated circuit device, equipment and storage medium

Abstract

The invention discloses a structure measurement method and device of an integrated circuit device, equipment and a storage medium. The method comprises the following steps: acquiring an initial measurement spectral signal of a to-be-measured sample in a preset wavelength range; dividing the preset wavelength range into a plurality of wavelength sections based on a preset mode; analyzing the spectrum change frequency of each wavelength band, and determining the sampling frequency corresponding to each wavelength band; resampling the initial measurement spectral signal of each wavelength band according to the sampling frequency to obtain a final measurement spectral signal; and performing fitting analysis on the final measurement spectral signal to obtain structural parameters of the sample to be measured. According to the invention, the wavelength sampling frequency is adaptively adjusted according to the frequency change distribution trend of the initially measured spectral signal, so that the finally collected spectral signal can be better fitted, and the measurement result is more accurate.

Description

Technical Field

[0001] The present application relates to the field of optical measurement technology, and in particular to a structure measurement method, device, equipment and storage medium for integrated circuit devices. Background Art

[0002] To ensure consistency and yield in the large-scale integrated circuit (IC) manufacturing process, it is necessary to quickly and accurately measure the three-dimensional structural morphology parameters of devices in key process steps. Currently, the industry widely uses optical critical dimension (OCD) measurement technology. Its basic technical principle is to collect the spectral information of the zero-order diffraction light reflected from the measured sample, combine it with theoretical models, and perform fitting analysis on the measured spectral information to obtain the sample's three-dimensional morphology parameters.

[0003] To collect the spectral signal of the zero-order diffraction light of the sample under test, a spectrometer is typically used to obtain light intensity at different wavelengths. Spectrometers uniformly sample wavelengths, resulting in uniformly sampled spectral signals. When fitting the spectral signal using theoretical calculation models, a fixed sampling frequency is typically set to uniformly sample the measurement wavelength range, or the original spectrometer wavelength sampling points are used to perform fitting analysis at these wavelengths to obtain measurement results. However, for certain semiconductor device structures, such as logic and DRAM devices, the zero-order diffraction light signal exhibits inconsistent characteristics at different wavelengths, varying dramatically in some wavelength ranges and more gradually in others. Another example is the zero-order diffraction light signal of a 3D NAND structure, which exhibits distinct oscillations across the entire wavelength range. For these unique devices, traditional fitting analysis using uniform wavelength sampling results in low theoretical model sensitivity due to low sampling frequencies, making it difficult to effectively extract the characteristics of the measured spectral signal, resulting in inaccurate measurement results and poor repeatability. Furthermore, higher sampling frequencies increase the computational complexity and computation time of the theoretical model, lengthening the fitting analysis time and reducing overall measurement efficiency. Summary of the Invention

[0004] In view of this, the present application provides a structure measurement method, apparatus, device and storage medium for an integrated circuit device to solve the problem of inaccurate circuit device structure measurement results caused by an unreasonable sampling method.

[0005] To solve the above technical problems, a technical solution adopted in the present application is: to provide a structural measurement method for an integrated circuit device, which includes: obtaining an initial measurement spectral signal of a sample to be measured within a preset wavelength range; dividing the preset wavelength range into multiple wavelength bands based on a preset method; analyzing the spectral change frequency of each wavelength band to determine the sampling frequency corresponding to each wavelength band; resampling the initial measurement spectral signal of each wavelength band according to the sampling frequency to obtain a final measurement spectral signal; and performing fitting analysis on the final measurement spectral signal to obtain the structural parameters of the sample to be measured.

[0006] As a further improvement of the present application, the preset wavelength range is divided into multiple wavelength segments based on a preset method, including: performing discrete wavelet transform analysis on the initial measured spectral signal to obtain the frequency change distribution of the spectral change frequency in the preset wavelength range; and dividing the preset wavelength range into multiple wavelength segments based on the frequency change distribution.

[0007] As a further improvement of this application, the discrete wavelet transform analysis process is expressed as: ; in, represents the frequency change distribution, Indicates the The initial measured spectrum signal corresponding to the wavelength point is Indicates that the wavelet function is at the displacement position The value at Indicates the total number of wavelength points of the initial measured spectrum signal.

[0008] As a further improvement of the present application, the preset wavelength range is divided into multiple wavelength segments based on the frequency change distribution, including: performing gradient calculation on the frequency change distribution to obtain the gradient value of each wavelength point; calculating the mean and standard deviation of all gradient values based on the gradient value, and setting a gradient threshold based on the mean and standard deviation; and dividing the preset wavelength range into multiple wavelength segments based on the gradient threshold.

[0009] As a further improvement of the present application, the spectral change frequency of each wavelength band is analyzed to determine the sampling frequency corresponding to each wavelength band, including: confirming the maximum value of the spectral change frequency in each wavelength band; multiplying each maximum value by a preset proportional factor to obtain the sampling frequency corresponding to each wavelength band.

[0010] As a further improvement of the present application, the initial measured spectral signal of each wavelength band is resampled according to the sampling frequency to obtain the final measured spectral signal, including: confirming the sampling point of each wavelength band according to the sampling frequency; sampling and interpolating the initial measured spectral signal according to the sampling point to obtain the final measured spectral signal.

[0011] As a further improvement of the present application, a fitting analysis is performed on the final measured spectral signal to obtain the structural parameters of the sample to be tested, including: constructing a three-dimensional structural physical model of the sample to be tested, the three-dimensional structural physical model including multiple parameter combinations; using electromagnetic simulation technology to construct a theoretical spectral calculation model of the sample to be tested, and setting the wavelength of the theoretical spectral calculation model to a preset wavelength range; using the theoretical spectral calculation model to solve the three-dimensional structural physical model to obtain theoretical spectral signals corresponding to all parameter combinations within the preset wavelength range; comparing the final measured spectral signal with each theoretical spectral signal to confirm the closest target theoretical spectral signal; and outputting the parameter combination corresponding to the target theoretical spectral signal as the structural parameter of the sample to be tested.

[0012] To solve the above technical problems, another technical solution adopted in the present application is: to provide a structural measurement device for an integrated circuit device, which includes: an acquisition module for acquiring an initial measurement spectral signal of a sample to be measured within a preset wavelength range; a wavelength division module for dividing the preset wavelength range into multiple wavelength bands based on a preset method; a frequency analysis module for analyzing the spectral change frequency of each wavelength band and determining the sampling frequency corresponding to each wavelength band; a resampling module for resampling the initial measurement spectral signal of each wavelength band according to the sampling frequency to obtain a final measurement spectral signal; and a fitting module for performing fitting analysis on the final measurement spectral signal to obtain the structural parameters of the sample to be measured.

[0013] To solve the above technical problems, another technical solution adopted in this application is: providing a computer device, which includes a processor and a memory coupled to the processor, wherein program instructions are stored in the memory, and when the program instructions are executed by the processor, the processor executes the steps of the structural measurement method of an integrated circuit device as described in any one of the above items.

[0014] In order to solve the above technical problems, another technical solution adopted by the present application is: providing a storage medium storing program instructions capable of implementing any of the above-mentioned structural measurement methods for integrated circuit devices.

[0015] The beneficial effects of the present application are as follows: the structural measurement method of the integrated circuit device of the present application divides the initial measurement spectral signal into multiple wavelength bands, analyzes the frequency change distribution of each wavelength band, sets the sampling frequency of each wavelength band, and then resamples each wavelength band according to the sampling frequency to obtain a new measurement spectral signal. Finally, the new measurement spectral signal is used for fitting analysis to obtain the structural parameters of the sample to be measured. It can analyze the distribution trend of the change frequency of the spectral signal with the wavelength, and then determine the appropriate wavelength sampling frequency according to the change frequency of the spectral signal. It can realize high-frequency sampling of the range with high spectral oscillation frequency and low-frequency sampling of the range with low spectral oscillation frequency. The wavelength sampling frequency is adaptively adjusted according to the specific characteristics of the measured spectral signal, so that the fitting analysis can better extract the spectral characteristics, and improve the accuracy of the measurement results without increasing the total number of samples and the amount of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 1 is a flow chart of a method for measuring the structure of an integrated circuit device according to an embodiment of the present invention; Figure 2 It is a schematic diagram of the structure of a periodic structure in an integrated circuit device; Figure 3 2 is a schematic diagram of the functional modules of the structure measurement device of the integrated circuit device according to an embodiment of the present invention; Figure 4 is a schematic structural diagram of a computer device according to an embodiment of the present invention; Figure 5 It is a schematic structural diagram of a storage medium according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0018] The terms "first," "second," and "third" in this application are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features identified. Therefore, features identified as "first," "second," or "third" may explicitly or implicitly include at least one of such features. In the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined. All directional designations in the embodiments of this application (such as up, down, left, right, front, back, etc.) are intended only to illustrate the relative positional relationships and movement of components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional designations will also change accordingly. Furthermore, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to such process, method, product, or apparatus.

[0019] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0020] Figure 1 FIG. 1 is a flow chart of a method for measuring the structure of an integrated circuit device according to an embodiment of the present invention. It should be noted that the method of the present invention is not limited to the method of measuring the structure of an integrated circuit device according to an embodiment of the present invention. Figure 1 The process sequence shown is limited. Figure 1 As shown, the structure measurement method of the integrated circuit device includes the following steps: Step S1: obtaining an initial measurement spectrum signal of a sample to be measured within a preset wavelength range.

[0021] Specifically, the OCD measuring device is used to measure the sample to be measured to obtain the initial measurement spectrum signal of the sample to be measured. ,in Represents the measured values at different wavelengths. The measured values can be in various forms such as reflectivity, ellipsometric parameters, Mueller matrix, etc. It should be noted that the initial measured spectral signal is uniformly sampled at a constant sampling frequency, and the preset wavelength range can be pre-set as needed.

[0022] Step S2: Divide the preset wavelength range into multiple wavelength segments based on a preset method.

[0023] Specifically, after obtaining the initial measured spectral signal, in order to better analyze the frequency change distribution of different wavelength bands, in this embodiment, the preset wavelength range is divided into multiple wavelength bands. The division of the wavelength bands can be achieved in a variety of ways. For example: equal interval division: by equally dividing the entire wavelength range into K segments, each of the same length; division based on frequency threshold: dividing the wavelength bands using a static frequency threshold obtained in advance, or setting a dynamic threshold based on the spectral change frequency value obtained by wavelet transform (such as the gradient, absolute value or local extreme value of the frequency change distribution) to determine the segmentation boundary; clustering algorithm division: using a clustering algorithm (such as K-means, DBSCAN) to group wavelength points of similar frequency into the same segment.

[0024] Furthermore, in order to better divide the wavelength bands so that each wavelength band can reflect the spectral characteristics of the wavelength band, S2 specifically includes: 1. Perform discrete wavelet transform analysis on the initial measured spectral signal to obtain the frequency change distribution of the spectral change frequency in the preset wavelength range.

[0025] Specifically, the discrete wavelet transform analysis process is expressed as: ; in, represents the frequency change distribution, Indicates the The initial measured spectrum signal corresponding to the wavelength point is Indicates that the wavelet function is at the displacement position The value at Indicates the total number of wavelength points of the initial measured spectrum signal.

[0026] It should be noted that It represents a wavelet function, which has many forms. You can choose the appropriate wavelet function according to the specific signal type. For example, the commonly used Haar wavelet is specifically defined as follows: .

[0027] 2. Divide the preset wavelength range into multiple wavelength segments based on the frequency change distribution.

[0028] Specifically, after obtaining the distribution of spectral frequency changes within a preset wavelength range, the preset wavelength range is divided into multiple wavelength bands based on the frequency change distribution, so that wavelength points with similar frequency change characteristics are distributed in the same wavelength band, which is convenient for setting the corresponding sampling frequency for each wavelength band.

[0029] Furthermore, the step of dividing the preset wavelength range into a plurality of wavelength segments based on the frequency change distribution specifically includes: 2.1. Perform gradient calculation on the frequency change distribution to obtain the gradient value at each wavelength point.

[0030] Specifically, in this implementation, the central difference method is used to calculate the gradient value of each wavelength point, and the calculation formula is expressed as: ; in, represents the gradient value, Indicates the It should be noted that before calculating the gradient value, the data is smoothed, which can be achieved by performing Gaussian filtering or moving average on the frequency change distribution.

[0031] 2.2. Calculate the mean and standard deviation of all gradient values based on the gradient value, and set the gradient threshold based on the mean and standard deviation.

[0032] Specifically, this embodiment adopts a dynamic threshold setting method to set the gradient threshold. The calculation formula of the mean and standard deviation is as follows: ; ; in, represents the mean, represents the standard deviation, Indicates the number of wavelength points.

[0033] The calculation formula of the gradient threshold is expressed as: ; in, represents the gradient threshold, Indicates the preset adjustment coefficient, The larger the value, the more conservative the segmentation. In this embodiment, different The best fitting accuracy and calculation time are selected under the value For spectra with large noise (such as 3D NAND structure), you can increase value to reduce mis-segmentation.

[0034] 2.3. Divide the preset wavelength range into multiple wavelength segments based on the gradient threshold.

[0035] Specifically, by traversing all wavelength points, it is confirmed whether the wavelength point exceeds the gradient threshold. If so, the wavelength point is marked as a boundary point. After all boundary points are found, the preset wavelength range is divided into multiple wavelength segments according to the boundary points.

[0036] Furthermore, to avoid segmenting wavelengths that are too short, this embodiment can also set a minimum wavelength length and merge boundary points whose adjacent spacing is less than the minimum wavelength length. For example, assuming the minimum wavelength length is 10 nm, if the initial segment boundary points are [450 nm, 455 nm, 460 nm, 600 nm, 605 nm], they are merged into [450 nm, 460 nm, 600 nm].

[0037] Furthermore, this embodiment may also extend the wavelength of a preset distance (eg, ±5 nm) before and after the region with high spectral oscillation frequency, to ensure that the region with high spectral oscillation frequency is fully covered.

[0038] Step S3: Analyze the spectrum change frequency of each wavelength band and determine the sampling frequency corresponding to each wavelength band.

[0039] Specifically, after dividing into multiple wavelength bands, the sampling frequency corresponding to each wavelength band is calculated in combination with the spectrum change frequency of each wavelength band.

[0040] The step S3 specifically includes: 1. Confirm the maximum value of the spectrum change frequency in each wavelength band.

[0041] 2. Multiply each maximum value by the preset scaling factor to obtain the sampling frequency corresponding to each wavelength band.

[0042] Among them, the preset scale factor is a preset constant. The value of the preset scale factor depends on the spectral signal characteristics and the final spectral fitting effect. The larger the value of the preset scale factor, the denser the sampling. It can be set in advance through multiple experiments and based on the final fitting results obtained from the experiments.

[0043] Specifically, after dividing into multiple wavelength bands, the spectrum change frequency distribution in each wavelength band is calculated separately. The maximum value , K represents the number of wavelength bands, and then the maximum value of the spectrum change frequency in each wavelength band is multiplied by the preset proportional factor to obtain the sampling frequency in the wavelength band, which is expressed as .

[0044] Step S4: resampling the initial measured spectrum signal of each wavelength band according to the sampling frequency to obtain a final measured spectrum signal.

[0045] Specifically, when obtaining the sampling frequency Finally, sampling is performed on the initial measurement spectrum signal corresponding to each wavelength band according to the sampling frequency corresponding to the wavelength band to obtain the final measurement spectrum signal.

[0046] Furthermore, step S4 specifically includes: 1. Confirm the sampling points of each wavelength band according to the sampling frequency.

[0047] Specifically, after obtaining the sampling frequency corresponding to each wavelength band, the number of sampling points in the wavelength band is determined according to the sampling frequency, and then the position of the sampling point is determined according to the number of sampling points and the length of the wavelength band.

[0048] 2. Sample and interpolate the initial measured spectrum signal according to the sampling points to obtain the final measured spectrum signal.

[0049] Specifically, after the position of each sampling point is confirmed, the spectrum signal of each sampling point is collected in the initial measurement spectrum signal, thereby obtaining the final measurement spectrum signal.

[0050] Step S5: Perform fitting analysis on the final measured spectral signal to obtain the structural parameters of the sample to be measured.

[0051] Specifically, after obtaining the final measurement spectrum signal, the final measurement spectrum signal is fitted and analyzed using the optical critical dimension (OCD) measurement technology, thereby obtaining the structural parameters of the three-dimensional structure of the sample to be measured.

[0052] Furthermore, step S5 specifically includes: 1. Construct a three-dimensional structural physical model of the sample to be tested, which includes multiple parameter combinations.

[0053] Specifically, a three-dimensional structural physical model corresponding to the sample to be tested is established, such as Figure 2 As shown, Figure 2 (a) represents a common device in an integrated circuit. Figure 2 (b) is its cross-sectional view, and the dotted box represents a single periodic unit. For each periodic unit, it includes structural parameters such as top width TCD, bottom width BCD, height Ht, and period Pitch. These structural parameters are used to characterize the three-dimensional structural physical model of the device.

[0054] 2. Use electromagnetic simulation technology to construct a theoretical spectrum calculation model of the sample to be tested, and set the wavelength of the theoretical spectrum calculation model to a preset wavelength range.

[0055] It should be noted that this electromagnetic simulation technology includes Rigorous Coupled Wave Analysis (RCWA) and Finite Difference Time Domain (FDTD). The theoretical spectrum calculation model constructed through electromagnetic simulation technology is used to calculate the theoretical spectrum signal under each structural parameter.

[0056] 3. Use the theoretical spectral calculation model to solve the three-dimensional structural physical model and obtain the theoretical spectral signals corresponding to all parameter combinations within the preset wavelength range.

[0057] Specifically, the wavelength of the theoretical spectrum calculation model is set to a preset wavelength range, and then the theoretical spectrum calculation model is used to perform spectral calculation on each parameter combination in the three-dimensional structure physical model to obtain the corresponding theoretical spectrum, thereby constructing a theoretical spectrum library corresponding to the sample to be tested.

[0058] 4. Compare the final measured spectrum signal with each theoretical spectrum signal to confirm the closest target theoretical spectrum signal.

[0059] 5. The parameter combination corresponding to the target theoretical spectral signal is used as the structural parameter of the sample to be tested and output.

[0060] Specifically, each theoretical spectrum signal in the theoretical spectrum library is traversed to find the target theoretical spectrum signal that is closest to the final measured spectrum. Then, the structural parameters corresponding to the target theoretical spectrum signal are queried, and the structural parameters and the three-dimensional structure data of the sample to be measured are queried, and the structural parameters are output as the final measurement results.

[0061] The structural measurement method of the integrated circuit device of this embodiment divides the initial measurement spectral signal into multiple wavelength bands, analyzes the frequency change distribution of each wavelength band, sets the sampling frequency of each wavelength band, and resamples each wavelength band according to the sampling frequency to obtain a new measurement spectral signal. Finally, the new measurement spectral signal is used to perform fitting analysis to obtain the structural parameters of the sample to be measured. It can analyze the distribution trend of the change frequency of the spectral signal with the wavelength, and then determine the appropriate wavelength sampling frequency according to the change frequency of the spectral signal. It can achieve high-frequency sampling of the range with high spectral oscillation frequency and low-frequency sampling of the range with low spectral oscillation frequency. The wavelength sampling frequency is adaptively adjusted according to the specific characteristics of the measured spectral signal, so that the fitting analysis can better extract the spectral characteristics, thereby improving the accuracy of the measurement results without increasing the total number of samples and the amount of calculation.

[0062] Figure 3 FIG. 1 is a schematic diagram of the functional modules of the structure measurement device of the integrated circuit device according to an embodiment of the present invention. Figure 3 As shown, the structure measurement device 20 of the integrated circuit device includes: an acquisition module 21, a wavelength division module 22, a frequency analysis module 23, a resampling module 24 and a fitting module 25.

[0063] An acquisition module 21 is used to obtain an initial measurement spectrum signal of a sample to be tested within a preset wavelength range; The wavelength division module 22 is used to divide the preset wavelength range into multiple wavelength segments based on a preset method; The frequency analysis module 23 is used to analyze the spectrum change frequency of each wavelength band and determine the sampling frequency corresponding to each wavelength band; A resampling module 24 is configured to resample the initial measured spectrum signal of each wavelength band according to the sampling frequency to obtain a final measured spectrum signal; The fitting module 25 is used to perform fitting analysis on the final measured spectral signal to obtain the structural parameters of the sample to be measured.

[0064] Optionally, the wavelength division module 22 performs an operation of dividing the preset wavelength range into multiple wavelength bands based on a preset method, specifically including: performing discrete wavelet transform analysis on the initial measured spectral signal to obtain the frequency change distribution of the spectral change frequency in the preset wavelength range; dividing the preset wavelength range into multiple wavelength bands based on the frequency change distribution.

[0065] Alternatively, the discrete wavelet transform analysis process is expressed as: ; in, represents the frequency change distribution, Indicates the The initial measured spectrum signal corresponding to the wavelength point is Indicates that the wavelet function is at the displacement position The value at Indicates the total number of wavelength points of the initial measured spectrum signal.

[0066] Optionally, the wavelength division module 22 performs an operation of dividing the preset wavelength range into multiple wavelength bands based on the frequency change distribution, specifically including: performing gradient calculation on the frequency change distribution to obtain the gradient value of each wavelength point; calculating the mean and standard deviation of all gradient values based on the gradient value, and setting a gradient threshold based on the mean and standard deviation; and dividing the preset wavelength range into multiple wavelength bands based on the gradient threshold.

[0067] Optionally, the frequency analysis module 23 performs an operation of analyzing the spectral change frequency of each wavelength band and determining the sampling frequency corresponding to each wavelength band, specifically including: confirming the maximum value of the spectral change frequency in each wavelength band; multiplying each maximum value by a preset proportional factor to obtain the sampling frequency corresponding to each wavelength band.

[0068] Optionally, the resampling module 24 performs an operation of resampling the initial measured spectral signal of each wavelength band according to the sampling frequency to obtain a final measured spectral signal, specifically including: confirming the sampling point of each wavelength band according to the sampling frequency; sampling and interpolating the initial measured spectral signal according to the sampling point to obtain a final measured spectral signal.

[0069] Optionally, the fitting module 25 performs a fitting analysis on the final measured spectral signal to obtain the structural parameters of the sample to be tested, specifically including: constructing a three-dimensional structural physical model of the sample to be tested, the three-dimensional structural physical model including multiple parameter combinations; using electromagnetic simulation technology to construct a theoretical spectral calculation model of the sample to be tested, and setting the wavelength of the theoretical spectral calculation model to a preset wavelength range; using the theoretical spectral calculation model to solve the three-dimensional structural physical model to obtain theoretical spectral signals corresponding to all parameter combinations within the preset wavelength range; comparing the final measured spectral signal with each theoretical spectral signal to confirm the closest target theoretical spectral signal; and outputting the parameter combination corresponding to the target theoretical spectral signal as the structural parameter of the sample to be tested.

[0070] For other details on the technical solutions for implementing each module in the structure measurement apparatus for integrated circuit devices in the above embodiment, reference may be made to the description of the structure measurement method for integrated circuit devices in the above embodiment, which will not be repeated here.

[0071] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similarities between the various embodiments can be referred to in conjunction with each other. For device embodiments, since they are generally similar to method embodiments, their description is relatively simple, and for relevant details, reference can be made to the description of the method embodiments.

[0072] See also Figure 4 , Figure 4 FIG. 1 is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Figure 4 As shown, the computer device 30 includes a processor 31 and a memory 32 coupled to the processor 31. The memory 32 stores program instructions. When the program instructions are executed by the processor 31, the processor 31 executes the steps of the structure measurement method of the integrated circuit device described in any of the above embodiments.

[0073] The processor 31 may also be referred to as a central processing unit (CPU). The processor 31 may be an integrated circuit chip with signal processing capabilities. The processor 31 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. The general-purpose processor may be a microprocessor or any conventional processor.

[0074] See Figure 5 , Figure 5Schematic diagram of the structure of the storage medium of an embodiment of the present invention. The storage medium of the embodiment of the present invention stores program instructions 41 that can implement the structural measurement method of the above-mentioned integrated circuit device, wherein the program instructions 41 can be stored in the above-mentioned storage medium in the form of a software product, including a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or a computer device such as a computer, server, mobile phone, or tablet.

[0075] In the several embodiments provided in this application, it should be understood that the disclosed computer devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0076] In addition, the functional units in the various embodiments of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of this application, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for measuring the structure of an integrated circuit device, characterized in that: It includes: Obtaining an initial measurement spectrum signal of the sample to be tested within a preset wavelength range; Dividing the preset wavelength range into a plurality of wavelength bands based on a preset method; Analyze the spectrum change frequency of each wavelength band and determine the sampling frequency corresponding to each wavelength band; Resampling the initial measured spectrum signal of each wavelength band according to the sampling frequency to obtain a final measured spectrum signal; The final measured spectral signal is subjected to fitting analysis to obtain the structural parameters of the sample to be measured.

2. The structure measurement method of an integrated circuit device according to claim 1, wherein: The dividing the preset wavelength range into a plurality of wavelength segments based on a preset method includes: Performing discrete wavelet transform analysis on the initial measured spectral signal to obtain a frequency change distribution of the spectral change frequency within the preset wavelength range; The preset wavelength range is divided into a plurality of wavelength segments based on the frequency change distribution.

3. The structure measurement method of an integrated circuit device according to claim 2, wherein: The process of discrete wavelet transform analysis is expressed as: ； in, represents the frequency change distribution, Indicates the The initial measured spectrum signal corresponding to the wavelength point is Indicates that the wavelet function is at the displacement position The value at Indicates the total number of wavelength points of the initial measured spectrum signal.

4. The structure measurement method of an integrated circuit device according to claim 2, wherein: The dividing the preset wavelength range into a plurality of wavelength segments based on the frequency change distribution includes: Performing gradient calculation on the frequency change distribution to obtain a gradient value at each wavelength point; Calculating a mean and a standard deviation of all gradient values according to the gradient value, and setting a gradient threshold based on the mean and the standard deviation; The preset wavelength range is divided into a plurality of wavelength segments based on the gradient threshold.

5. The structure measurement method of an integrated circuit device according to claim 1, wherein: The analyzing the spectrum change frequency of each wavelength band to determine the sampling frequency corresponding to each wavelength band includes: Confirm the maximum value of the spectrum variation frequency in each wavelength band; Multiply each maximum value by a preset scaling factor to obtain the sampling frequency corresponding to each wavelength band.

6. The structure measurement method of an integrated circuit device according to claim 1, wherein: The resampling of the initial measured spectrum signal of each wavelength band according to the sampling frequency to obtain the final measured spectrum signal includes: Determining the sampling points of each wavelength band according to the sampling frequency; The initial measurement spectrum signal is sampled and interpolated according to the sampling points to obtain the final measurement spectrum signal.

7. The structure measurement method of an integrated circuit device according to claim 1, wherein: The fitting analysis of the final measured spectral signal to obtain the structural parameters of the sample to be tested includes: Constructing a three-dimensional structural physical model of the sample to be tested, wherein the three-dimensional structural physical model includes a plurality of parameter combinations; Constructing a theoretical spectrum calculation model of the sample to be tested using electromagnetic simulation technology, and setting the wavelength of the theoretical spectrum calculation model to the preset wavelength range; Solving the three-dimensional structure physical model using the theoretical spectrum calculation model to obtain theoretical spectrum signals corresponding to all parameter combinations within the preset wavelength range; Comparing the final measured spectrum signal with each theoretical spectrum signal to determine the closest target theoretical spectrum signal; The parameter combination corresponding to the target theoretical spectral signal is used as the structural parameter of the sample to be tested and output.

8. A structural measurement device for an integrated circuit device, characterized in that: It includes: An acquisition module is used to obtain an initial measurement spectrum signal of the sample to be tested within a preset wavelength range; A wavelength division module, configured to divide the preset wavelength range into a plurality of wavelength segments based on a preset method; Frequency analysis module, used to analyze the spectrum change frequency of each wavelength band and determine the sampling frequency corresponding to each wavelength band; a resampling module, configured to resample the initial measured spectrum signal of each wavelength band according to the sampling frequency to obtain a final measured spectrum signal; The fitting module is used to perform fitting analysis on the final measured spectral signal to obtain the structural parameters of the sample to be tested.

9. A computer device, characterized in that: The computer device includes a processor and a memory coupled to the processor, wherein program instructions are stored in the memory. When the program instructions are executed by the processor, the processor executes the steps of the structure measurement method of the integrated circuit device according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The device stores program instructions capable of implementing the structure measurement method of the integrated circuit device according to any one of claims 1 to 7.

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