Method and system for rapidly acquiring X-ray scattering spectrum of nanostructure

Abstract

The invention belongs to the field of X-ray critical dimension measurement, and provides a method and a system for rapidly acquiring an X-ray scattering spectrum of a nano-structure, and the method comprises the steps: carrying out the sampling of each cross section through a cross section sampling algorithm improved by a Green algorithm, converting the area integral corresponding to the cross section contour of each cross section into a line integral, and obtaining the X-ray scattering spectrum of the nano-structure; the number of sampling points of each cross section is obviously reduced; the integral height node corresponding to the morphology model is obtained through the Gaussian Legendre integral algorithm, and the longitudinal section sampling is carried out on the morphology model in cooperation with the section shape factor of each cross section, so that the data required for calculating the overall shape factor is further reduced, and therefore, the sampling accuracy can be ensured, and the calculation efficiency can be improved. And rapid acquisition of the X-ray scattering spectrum of the high-depth-ratio complex nano-structure is realized.

Description

Technical Field

[0001] The present application belongs to the field of X-ray critical dimension measurement, and more specifically, relates to a method and system for rapidly acquiring X-ray scattering spectra of nanostructures. Background Art

[0002] With the introduction of more complex technologies such as artificial intelligence, digital twins, 5G+, autonomous vehicles, and the Internet of Things, massive amounts of data are expected to continue to grow. This enormous demand for data storage and computing is driving the rapid transition of the semiconductor industry from planar structures to three-dimensional nanostructures. Monitoring high-aspect-ratio nanostructures is crucial to ensuring product yield, production volume, and end-product performance. Consequently, XCD (X-ray Critical Dimension) measurement methods have gained widespread application.

[0003] The XCD measurement process is to perform forward modeling on the nanostructure, establish a mapping from the structural parameters of the nanostructure to the X-ray scattering spectrum, and then use an inverse iterative algorithm to finally extract the nanostructure parameters from the measured scattering spectrum. Existing methods for obtaining X-ray scattering spectra, whether it is a method that performs accurate three-dimensional full sampling of the entire nanostructure and then uses FFT to calculate and obtain it, or a method that uses a slicing method to divide the complex nanostructure into multiple layers of simple cylinders and then calculates and obtains it, all have the disadvantages of high computing power consumption and slow calculation speed. Summary of the Invention

[0004] In view of the above-mentioned defects in the prior art, the present application provides a method and system for quickly acquiring X-ray scattering spectra of nanostructures, aiming to solve the problem of slow scattering spectrum measurement speed of the existing XCD measurement method.

[0005] In a first aspect, the present application provides a method for rapidly acquiring an X-ray scattering spectrum of a nanostructure, comprising: Based on the morphology model of the nanostructure, three-dimensional morphology information of the nanostructure is obtained, and the morphology model is transversely sliced ​​based on the three-dimensional morphology information to obtain multiple cross sections to be sampled; Sampling each cross section based on the three-dimensional morphology information to obtain a cross-sectional shape factor corresponding to the cross section, where the cross-sectional shape factor is used to characterize the spatial mapping relationship between each sampling point of the cross section and the cross section; Based on the three-dimensional morphology information and the cross-sectional shape factors corresponding to each cross section, the morphology model is sampled in the longitudinal section, and the overall shape factor of the morphology model is obtained. The overall shape factor is used to characterize the spatial mapping relationship between each sampling point of the morphology model and the morphology model; Based on the overall shape factor and three-dimensional morphology information, the X-ray scattering spectrum corresponding to the nanostructure is obtained.

[0006] Furthermore, the morphology model is subjected to transverse slicing processing based on the three-dimensional morphology information, including: Based on the three-dimensional morphology information, the Gauss-Legendre integral algorithm is used to obtain the integral height nodes corresponding to the morphology model, and the morphology model is transversely sliced ​​based on the integral height nodes.

[0007] Among them, the three-dimensional morphology information includes the spatial coordinates of each sampling point of the morphology model of the nanostructure and the morphology size, cross-sectional profile and other information of the morphology model. The morphology model corresponding to the three-dimensional morphology information can be a polynomial, a spline curve, a sine and cosine function or a combination of multiple ones, or a geometric set of discrete points of the boundary cross-sectional profile. Therefore, a numerical integration method can be used to obtain the integral height node of the morphology model, and then the integral height node is used for transverse slicing. On the basis of retaining the effective feature points of the morphology model to ensure the calculation accuracy, the number of cross sections required for calculating the overall shape factor can be reduced. The numerical integration method preferably uses the Gauss-Legendre integral algorithm, which can set a specific number of integral nodes and determine the position of the integral height node according to the integral weight of the morphology model at different heights, thereby completing transverse slicing. The slicing method based on the Gauss-Legendre integral algorithm can significantly reduce the number of slices and the amount of calculation compared to the dense slicing method.

[0008] Furthermore, each cross section is sampled based on the three-dimensional morphology information to obtain a cross-sectional shape factor corresponding to each cross section, including: Based on the three-dimensional morphology information, the cross-section sampling algorithm improved by Green's algorithm is used to sample each cross section, and the surface integral corresponding to the cross-sectional profile of each cross section is converted into a line integral to obtain the two-dimensional position relationship information corresponding to each cross section; Based on the two-dimensional positional relationship information corresponding to each cross section, the cross-sectional shape factor corresponding to each cross section is obtained. The two-dimensional positional relationship information includes the two-dimensional coordinates, scattering vector and electron density distribution of each sampling point of the cross section corresponding to the two-dimensional positional relationship information.

[0009] Among them, the cross-section sampling algorithm improved by the Green algorithm can convert the surface integral corresponding to the cross-sectional profile of the cross section into a line integral using the Green algorithm, thereby realizing data dimensionality reduction, thereby reducing the computational complexity of the method of the present application and improving the measurement speed of the X-ray scattering spectrum.

[0010] Furthermore, the steps for obtaining the cross-sectional shape factor corresponding to each cross section are shown in the following formula: ; in, F ( q x , q y ) represents the cross-sectional shape factor, qx and q y denote the components of the scattering vector q in the x and y directions, respectively, ( x j ,y j ) indicates the j The two-dimensional coordinates of the sampling points, ρ 0 represents the electron density distribution of the nanostructure, represents the Sigmoid function, .

[0011] Furthermore, longitudinal cross-section sampling is performed on the morphology model, including: Based on the three-dimensional morphology information and the cross-sectional shape factor corresponding to each cross section, the three-dimensional positional relationship information between each sampling point of each cross section is obtained. The three-dimensional positional relationship information includes the spatial position vector, electron density distribution and total height of the nanostructure between each sampling point of each cross section.

[0012] Furthermore, the overall shape factor of the morphology model is obtained as shown in the following formula:

[0013] in, F (q) represents the overall shape factor, q x 、 q y and q z denote the components of the scattering vector q in the x, y, and z directions, respectively, V represents the three-dimensional integration interval of the topography model, D represents the two-dimensional integration interval of the cross section corresponding to height z, ( x j ,y j ,z) represents the j The three-dimensional coordinates of the sampling point at height z, r represents the spatial position vector of the sampling point, ρ (r) represents the electron density distribution of the nanostructure, H is the total height of the nanostructure, F ( q x , q y | z ) represents the cross-sectional shape factor of the cross section corresponding to height z.

[0014] Sampling the topography model in the longitudinal section refers to sampling the two-dimensional information of the cross section at a specific height in the longitudinal section, such as the two-dimensional positional relationship information, to obtain the cross-sectional shape factor of the cross section at that height. Finally, the cross-sectional shape factors of each cross section are linked by numerical integration to obtain the overall shape factor. This longitudinal section sampling method, by sparsely sampling the cross sections at a specific height in the longitudinal section, can effectively obtain the overall shape factor by combining the cross-sectional shape factors of each cross section, while further reducing the amount of calculation.

[0015] Furthermore, before obtaining the cross-sectional shape factors corresponding to each cross section, the following steps are also included: Determine whether the cross-sectional profile corresponding to each two-dimensional positional relationship information is a resolvable cross-sectional profile, and when the cross-sectional profile of the cross-sectional profile is characterized as resolvable, obtain the target analytical formula corresponding to the cross-sectional profile of the cross-sectional profile, and perform parameter compression processing on the calculation formula of the cross-sectional shape factor of the cross-sectional profile based on the target analytical formula.

[0016] Among them, since the cross-sectional profiles of some cross sections are analyzable cross-sectional profiles such as circles, rectangles, and trapezoids, which have analytical formulas, the cross-sectional shape factors can be directly calculated using the Bessel function, thereby avoiding the use of the above-mentioned cross-sectional shape factor calculation formula for these cross sections, thereby reducing the number of parameters for calculating the overall shape factor.

[0017] Furthermore, based on the overall shape factor and three-dimensional morphology information, an X-ray scattering spectrum corresponding to the nanostructure is obtained, including: Obtaining nanostructure periodic information of the morphology model based on the three-dimensional morphology information, the nanostructure periodic information including a periodic structure factor, and obtaining an X-ray scattering spectrum corresponding to the nanostructure based on the periodic structure factor and the overall shape factor; Among them, the formula for obtaining X-ray scattering spectrum is expressed as , I (q) represents the X-ray scattering spectrum, I 0 represents the light intensity scaling factor, S (q) represents the structure factor, I bk represents the background light intensity, and q represents the scattering vector.

[0018] In a second aspect, the present application further provides a system for rapidly acquiring X-ray scattering spectra of nanostructures, comprising: A morphology data acquisition module is used to obtain three-dimensional morphology information of the nanostructure; A transverse sampling module is used to sample each cross section of the nanostructure using the three-dimensional morphology information to obtain a cross-sectional shape factor corresponding to the cross section; A longitudinal sampling module is used to perform longitudinal cross-section sampling on the topography model using the three-dimensional topography information and the cross-sectional shape factors corresponding to each cross section, and obtain the overall shape factor of the topography model; The X-ray scattering spectrum acquisition module is used to obtain the X-ray scattering spectrum corresponding to the nanostructure by using the overall shape factor and three-dimensional morphology information.

[0019] In a third aspect, the present application further provides an electronic device, comprising: at least one memory for storing a computer program; At least one processor is configured to execute a program stored in a memory. When the program stored in the memory is executed, the processor is configured to execute any one of the methods of the first aspect.

[0020] In general, the above technical solutions conceived by the present application have the following beneficial effects compared with the existing technology: the present application provides a method and system for quickly acquiring X-ray scattering spectra of nanostructures, which samples each cross section through a cross-section sampling algorithm improved by the Green algorithm, and converts the area integral corresponding to the cross-sectional profile of each cross section into a line integral, significantly reducing the number of sampling points of each cross section; the integral height nodes corresponding to the morphology model are obtained through the Gauss-Legendre integral algorithm, and the longitudinal section of the morphology model is sampled in conjunction with the cross-sectional shape factor of each cross section, further reducing the data required to calculate the overall shape factor, thereby ensuring sampling accuracy while achieving rapid acquisition of X-ray scattering spectra of complex nanostructures with a high depth ratio. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in this application or related technologies, the following is a brief introduction to the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1 This is a schematic flow chart of a method for rapidly acquiring an X-ray scattering spectrum of a nanostructure provided in an embodiment of the present application; Figure 2 A schematic structural diagram of a morphology model corresponding to a nanostructure provided in an embodiment of the present application; Figure 3 A schematic diagram of a system for rapidly acquiring X-ray scattering spectra of nanostructures provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application.

[0024] In the following introduction, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. The following introduction provides multiple embodiments of the present application. Different embodiments can be replaced or combined, so the present application can also be considered to include all possible combinations of the same and / or different embodiments described. Therefore, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then the present application should also be considered to include embodiments containing one or more of all other possible combinations of A, B, C, and D, even though the embodiment may not be clearly described in the following text.

[0025] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the elements described without departing from the scope of the present application. Various examples may appropriately omit, replace, or add various processes or components. For example, the described method may be performed in an order different from the order described, and various steps may be added, omitted, or combined. In addition, features described in some examples may be combined in other examples.

[0026] Figure 1 FIG. 1 is a flow chart of a method for rapidly acquiring an X-ray scattering spectrum of a nanostructure provided in an embodiment of the present application. Figure 1 As shown, the method comprises at least the following steps: S101 , based on the morphology model of the nanostructure, obtaining three-dimensional morphology information of the nanostructure, and performing transverse slicing processing on the morphology model based on the three-dimensional morphology information to obtain a plurality of cross sections to be sampled.

[0027] The execution subject of this method may be a central processing unit of an X-ray-based nanometer detector.

[0028] In the embodiments of this application, Figure 2 As shown, an embodiment provides a morphological model of a nanostructure, wherein the three-dimensional morphological information includes the coordinates of each sampling point of the nanostructure in three-dimensional space, the vector relationship between the sampling points, the appearance and the dimensions of each part, etc. The morphological model of this embodiment can be a polynomial, a spline curve, a sine and cosine function, or a combination of these, and is used to represent the morphological characteristics of the nanostructure in real physical space, so as to facilitate the acquisition of X-ray scattering spectra based on the morphological model.

[0029] Because some nanostructures may be irregular and complex, it is impossible to use a single set of mathematical models to perform a comprehensive sampling analysis of the nanostructures to calculate the X-ray scattering spectrum. Therefore, it is necessary to transversely slice the corresponding morphological model of the nanostructure to obtain multiple cross-sections to be sampled, so that the morphological model can be quantitatively analyzed from both horizontal and vertical perspectives.

[0030] In one possible implementation, performing transverse slicing processing on the topography model based on the three-dimensional topography information includes: Based on the three-dimensional morphology information, the Gauss-Legendre integral algorithm is used to obtain the integral height nodes corresponding to the morphology model, and the morphology model is transversely sliced ​​based on the integral height nodes.

[0031] In the embodiments of the present application, the slicing of the morphology model is generally carried out in an osculating manner, for example, a dense height parameter is set, and the morphology model is divided into a large number of transverse slices according to the height of the nanostructure, but this consumes a lot of computing power. There are many options for numerical integration methods, including but not limited to the Simpson integral formula, the Romberg integral formula, and the Gauss-Legendre integral formula. In order to ensure the integration accuracy while reducing the number of sampling points, the present embodiment adopts the Gauss-Legendre integral to achieve longitudinal sparse sampling, and selects the calculated integral height node to slice the morphology model, and the Gauss-Legendre integral algorithm can set a specific number of integral nodes, and determine the position of the integral height node according to the integral weight of the morphology model at different heights, thereby ensuring the sampling accuracy while reducing the amount of calculation.

[0032] S102 . Sample each cross section based on the three-dimensional shape information to obtain a cross-sectional shape factor corresponding to the cross section. The cross-sectional shape factor is used to characterize a spatial mapping relationship between each sampling point of the cross section and the cross section.

[0033] In the field of X-ray critical dimension measurement, the form factor is a core physical quantity that describes the scattering field characteristics of nanostructures when they interact with X-rays. To accurately analyze the topography of nanostructures, especially those with high depth and complexity, this embodiment introduces the form factor to calculate the corresponding X-ray scattering spectrum of the nanostructure. Therefore, each cross-section is sampled based on the three-dimensional topography information, and the cross-sectional form factor is calculated on a two-dimensional level.

[0034] In one possible implementation, sampling each cross section based on the three-dimensional topography information to obtain a cross-sectional shape factor corresponding to each cross section includes: Based on the three-dimensional morphology information, the cross-section sampling algorithm improved by Green's algorithm is used to sample each cross section, and the surface integral corresponding to the cross-sectional profile of each cross section is converted into a line integral to obtain the two-dimensional position relationship information corresponding to each cross section; Based on the two-dimensional positional relationship information corresponding to each cross section, the cross-sectional shape factor corresponding to each cross section is obtained. The two-dimensional positional relationship information includes the two-dimensional coordinates, scattering vector and electron density distribution of each sampling point of the cross section corresponding to the two-dimensional positional relationship information.

[0035] In the embodiment of the present application, the cross-section sampling algorithm that directly performs dense sampling of the cross section from a two-dimensional perspective requires recording a large number of sampling points. The cross-section sampling algorithm improved by the Green algorithm can D The surface integral inside is converted into the contour along the region boundary L The line integral of , and then the number of sampling points required to calculate the overall shape factor will be greatly reduced.

[0036] In one possible implementation, the step of obtaining the cross-sectional shape factor corresponding to each cross section is as shown in the following formula: ; in, F ( q x , q y ) represents the cross-sectional shape factor, q x and q y denote the components of the scattering vector q in the x and y directions, respectively, ( x j ,y j ) indicates the j The two-dimensional coordinates of the sampling points are in a counterclockwise sequence, which is determined by the way Green's formula calculates the line integral; ρ 0 represents the electron density distribution of the nanostructure, represents the Sigmoid function, .

[0037] In the embodiment of the present application, the cross-section sampling algorithm that does not use the Green algorithm directly uses the surface integral to calculate the cross-section shape factor, as shown in the following formula:

[0038] in, q x and q y The scattering vector q is x and y The direction component, ρ ( x , y , z ) is the electron density distribution of the coordinate point in three-dimensional space, which is generally uniformly distributed in the nanostructure, so ρ ( x, y , z ) can be unified ρ 0 represents. Since the cross-section of a complex nanostructure is very complex, directly calculating the cross-sectional shape factor using surface integrals requires a large amount of data. However, the cross-sectional sampling algorithm improved by the Green algorithm only requires line integrals of the cross-sectional contours to calculate, thus achieving dimensionality reduction at the data level, thereby reducing the computational complexity of the method of the present application and improving the measurement speed of X-ray scattering spectra.

[0039] S103. Based on the three-dimensional morphology information and the cross-sectional shape factors corresponding to each cross section, perform longitudinal cross-sectional sampling on the morphology model and obtain an overall shape factor of the morphology model. The overall shape factor is used to characterize the spatial mapping relationship between each sampling point of the morphology model and the morphology model.

[0040] In the embodiment of the present application, sampling the longitudinal section of the morphology model refers to sampling the two-dimensional information of the cross section at a specific height of the longitudinal section, such as the two-dimensional position relationship information, so as to obtain the cross-sectional shape factor of the cross section at the height, and finally using the numerical integration method to establish the relationship between the cross-sectional shape factors of each cross section, so as to obtain the overall shape factor. Figure 2 As shown, this embodiment uses the Gauss-Legendre integral method to calculate the specific height of the longitudinal section. Specifically, the total number of integral height nodes is set, and then the heights of multiple integral height nodes are calculated. Multiple rectangular spaces are constructed between the cross sections corresponding to the integral height nodes. Combined with the cross-sectional shape factors of each cross section and the three-dimensional morphology information of the morphology model in each rectangular space, the longitudinal section sampling is achieved, that is, the spatial mapping relationship between the sampling points of the cross section corresponding to each integral height node and the morphology model is sampled. The purpose of constructing multiple rectangular spaces of this type shown in the figure is to perform segmented sampling of the cross section. The space between two cross sections corresponds to the scattering field corresponding to a single X-ray scattering spectrum, reducing the computational complexity of a single sampling.

[0041] In one embodiment, the overall shape factor of the topography model is obtained as shown in the following formula:

[0042] in, F (q) represents the overall shape factor, q x 、 q y and q z denote the components of the scattering vector q in the x, y, and z directions, respectively, V represents the three-dimensional integration interval of the topography model, D represents the two-dimensional integration interval of the cross section corresponding to height z, ( xj ,y j ,z) represents the j The three-dimensional coordinates of the sampling point at height z, r represents the spatial position vector of the sampling point, ρ (r) represents the electron density distribution of the nanostructure, H is the total height of the nanostructure, F ( q x , q y | z ) represents the cross-sectional shape factor of the cross section corresponding to height z.

[0043] In the embodiments of the present application, longitudinal cross-section sampling of the topography model refers to sampling two-dimensional information, such as two-dimensional positional relationship information, of a cross section at a specific height on the longitudinal section to obtain the cross-sectional shape factor of the cross section at that height. Finally, numerical integration is used to establish a relationship between the cross-sectional shape factors of each cross section to obtain the overall shape factor. This longitudinal cross-section sampling method, by sparsely sampling cross sections at a specific height on the longitudinal section, can effectively obtain the overall shape factor by combining the cross-sectional shape factors of each cross section, while further reducing the amount of computation.

[0044] In one possible implementation, before obtaining the cross-sectional shape factor corresponding to each cross section, the method further includes: Determine whether the cross-sectional profile corresponding to each two-dimensional positional relationship information is a resolvable cross-sectional profile, and when the cross-sectional profile of the cross-sectional profile is characterized as resolvable, obtain the target analytical formula corresponding to the cross-sectional profile of the cross-sectional profile, and perform parameter compression processing on the calculation formula of the cross-sectional shape factor of the cross-sectional profile based on the target analytical formula.

[0045] In the embodiments of this application, Figure 2 As shown in the figure, several groups of cross-sections with different shapes are shown. Some, such as rounded rectangular cross-sections, do not have a target analytic formula, while others, such as circular rectangular cross-sections, do. Therefore, the cross-sectional shape factor can be directly calculated using the Bessel function, thus avoiding the use of the cross-sectional shape factor calculation formula for these cross-sections, thereby reducing the number of parameters required to calculate the overall shape factor. Combining the target analytic formula for these cross-sections with the calculation formula for the overall shape factor can reduce the calculation process for the cross-sectional shape factor of these cross-sections, further improving the speed of obtaining the overall shape factor, and thus faster acquisition of X-ray scattering spectra.

[0046] S104 , obtaining an X-ray scattering spectrum corresponding to the nanostructure based on the overall shape factor and the three-dimensional morphology information.

[0047] In an embodiment of the present application, the specific steps of obtaining an X-ray scattering spectrum corresponding to the nanostructure include: obtaining nanostructure periodic information of the morphology model based on the three-dimensional morphology information, the nanostructure periodic information including a periodic structure factor, and obtaining an X-ray scattering spectrum corresponding to the nanostructure based on the periodic structure factor and the overall shape factor; Among them, the periodic information of nanostructure refers to the periodic characteristics of the spatial arrangement of nanostructures, which is inherent in the nanostructure and has nothing to do with the intensity and direction of the X-ray incident. The formula for obtaining the X-ray scattering spectrum is expressed as , I (q) represents the X-ray scattering spectrum, I 0 represents the light intensity scaling factor, S (q) represents the structure factor, I bk represents the background light intensity, and q represents the scattering vector.

[0048] Table 1 Comparison of calculation time for X-ray scattering spectra of different nanostructures

[0049] As shown in Table 1, this embodiment provides a comparison of the computational time required to obtain X-ray scattering spectra of different nanostructures based on the NUFFT (Non-Uniform Fast Fourier Transform) sampling method and the sampling method of this embodiment, respectively, under the same RMSE (Root Mean Squared Error).

[0050] Among them, CF-T500, CF-B500 and C2D are nanostructures of different complexity. The calculation time comparison results show that compared with the existing method based on NUFFT to obtain X-ray scattering spectra, the calculation speed of the method in this embodiment is improved by 1 to 3 orders of magnitude.

[0051] like Figure 3 As shown, this embodiment also provides a system for rapidly acquiring X-ray scattering spectra of nanostructures, comprising: A morphology data acquisition module is used to obtain three-dimensional morphology information of the nanostructure; A transverse sampling module is used to sample each cross section of the nanostructure using the three-dimensional morphology information to obtain a cross-sectional shape factor corresponding to the cross section; A longitudinal sampling module is used to perform longitudinal cross-section sampling on the topography model using the three-dimensional topography information and the cross-sectional shape factors corresponding to each cross section, and obtain the overall shape factor of the topography model; The X-ray scattering spectrum acquisition module is used to obtain the X-ray scattering spectrum corresponding to the nanostructure by using the overall shape factor and three-dimensional morphology information.

[0052] like Figure 4 As shown, the electronic device may include: a processor (Processor) 401, a communication interface (Communications Interface) 402, a memory (Memory) 403, and a communication bus 404. The processor 401, the communication interface 402, and the memory 403 communicate with each other via the communication bus 404. The processor 401 may call software instructions in the memory 403 to execute the method described in the above embodiment.

[0053] In addition, the logic instructions in the aforementioned memory 403 can be implemented in the form of a software functional unit and, when sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application.

[0054] It is easy for those skilled in the art to understand that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for rapidly acquiring X-ray scattering spectra of nanostructures, characterized in that: include: Based on the morphology model of the nanostructure, obtaining three-dimensional morphology information of the nanostructure, and performing transverse slicing processing on the morphology model based on the three-dimensional morphology information to obtain a plurality of cross sections to be sampled; Sampling each cross section based on the three-dimensional topography information to obtain a cross-sectional shape factor corresponding to the cross section, wherein the cross-sectional shape factor is used to characterize a spatial mapping relationship between each sampling point of the cross section and the cross section; Based on the three-dimensional topography information and the cross-sectional shape factors corresponding to the cross sections, sampling the topography model in a longitudinal direction, and obtaining an overall shape factor of the topography model, wherein the overall shape factor is used to characterize a spatial mapping relationship between each sampling point of the topography model and the topography model; An X-ray scattering spectrum corresponding to the nanostructure is obtained based on the overall shape factor and the three-dimensional morphology information.

2. The method for rapidly acquiring X-ray scattering spectra of nanostructures according to claim 1, characterized in that: The performing transverse slicing processing on the topography model based on the three-dimensional topography information includes: Based on the three-dimensional topography information, a Gauss-Legendre integral algorithm is used to obtain an integral height node corresponding to the topography model, and a transverse slicing process is performed on the topography model based on the integral height node.

3. The method for rapidly acquiring X-ray scattering spectra of nanostructures according to claim 1, characterized in that: The sampling of each cross section based on the three-dimensional topography information to obtain a cross-sectional shape factor corresponding to each cross section includes: Based on the three-dimensional morphology information, each cross section is sampled using a cross-section sampling algorithm improved by the Green algorithm, and the surface integral corresponding to the cross-sectional profile of each cross section is converted into a line integral to obtain two-dimensional positional relationship information corresponding to each cross section; Based on the two-dimensional positional relationship information corresponding to each cross-section, a cross-sectional shape factor corresponding to each cross-section is obtained, wherein the two-dimensional positional relationship information includes the two-dimensional coordinates, scattering vector and electron density distribution of each sampling point of the cross-section corresponding to the two-dimensional positional relationship information.

4. The method for rapidly acquiring X-ray scattering spectra of nanostructures according to claim 3, characterized in that: The step of obtaining the cross-sectional shape factor corresponding to each cross section is shown in the following formula: ； in, F ( q x , q y ) represents the cross-sectional shape factor, q x and q y denote the components of the scattering vector q in the x and y directions, respectively, ( x j ,y j ) indicates the j The two-dimensional coordinates of the sampling points, ρ 0 represents the electron density distribution of the nanostructure, represents the Sigmoid function, .

5. The method for rapidly acquiring X-ray scattering spectra of nanostructures according to claim 1, characterized in that: The performing longitudinal section sampling on the morphology model comprises: Based on the three-dimensional morphology information and the cross-sectional shape factor corresponding to each cross-section, three-dimensional positional relationship information between each sampling point of each cross-section is obtained, where the three-dimensional positional relationship information includes a spatial position vector, an electron density distribution, and a total height of the nanostructure between each sampling point of each cross-section.

6. The method for rapidly acquiring X-ray scattering spectra of nanostructures according to claim 1, characterized in that: The overall shape factor of the topography model is obtained as shown in the following formula: in, F (q) represents the overall shape factor, q x 、 q y and q z denote the components of the scattering vector q in the x, y, and z directions, respectively, V represents the three-dimensional integration interval of the topography model, D represents the two-dimensional integration interval of the cross section corresponding to height z, ( x j ,y j ,z) represents the j The three-dimensional coordinates of the sampling point at height z, r represents the spatial position vector of the sampling point, ρ (r) represents the electron density distribution of the nanostructure, H is the total height of the nanostructure, F ( q x , q y | z ) represents the cross-sectional shape factor of the cross section corresponding to height z.

7. The method for rapidly acquiring X-ray scattering spectra of nanostructures according to claim 3, characterized in that: Before obtaining the cross-sectional shape factors corresponding to the cross sections, the method further includes: Determine whether the cross-sectional profile of the cross section corresponding to each of the two-dimensional positional relationship information is a resolvable cross-sectional profile, and when the cross-sectional profile of the cross section is characterized as resolvable, obtain the target analytical formula corresponding to the cross-sectional profile of the cross section, and perform parameter compression processing on the calculation formula of the cross-sectional shape factor of the cross section based on the target analytical formula.

8. The method for rapidly acquiring X-ray scattering spectra of nanostructures according to claim 1, characterized in that: The obtaining of an X-ray scattering spectrum corresponding to the nanostructure based on the overall shape factor and the three-dimensional morphology information includes: Obtaining nanostructure periodic information of the morphology model based on the three-dimensional morphology information, wherein the nanostructure periodic information includes the periodic structure factor, and obtaining an X-ray scattering spectrum corresponding to the nanostructure based on the periodic structure factor and the overall shape factor; The formula for obtaining the X-ray scattering spectrum is expressed as follows: , I (q) represents the X-ray scattering spectrum, I 0 represents the light intensity scaling factor, S (q) represents the structure factor, I bk represents the background light intensity, and q represents the scattering vector.

9. A system for rapidly acquiring X-ray scattering spectra of nanostructures, for implementing the method according to any one of claims 1 to 8, characterized in that: include: A morphology data acquisition module is used to obtain three-dimensional morphology information of the nanostructure; a transverse sampling module, configured to sample each cross section of the nanostructure using the three-dimensional topography information to obtain a cross-sectional shape factor corresponding to the cross section; a longitudinal sampling module, configured to perform longitudinal cross-sectional sampling on the topography model using the three-dimensional topography information and the cross-sectional shape factors corresponding to the cross-sections, and obtain an overall shape factor of the topography model; An X-ray scattering spectrum acquisition module is used to acquire an X-ray scattering spectrum corresponding to the nanostructure by using the overall shape factor and the three-dimensional morphology information.

10. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1 to 8.

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