Metrology method and system for overlay error, apparatus and storage medium

Abstract

A method, system and device for measuring overlay error and a storage medium are provided. The method comprises: providing a front layer structure and a current layer structure on the front layer structure, the front layer structure comprising a plurality of second alignment patterns, and the current layer structure comprising a plurality of measurement areas corresponding to the second alignment patterns; setting a measurement interval of the current layer structure; in each measurement area of the current layer structure, obtaining a plurality of measurement patterns arranged in parallel at the measurement interval, including a first alignment pattern and other measurement patterns on both sides of the first alignment pattern; obtaining a first alignment signal of the measurement pattern and the second alignment pattern of the front layer at each measurement pattern as a measurement position; obtaining position information of a measurement pattern at a center position in the measurement pattern according to a plurality of first alignment signals; and obtaining an overlay error of the first alignment pattern and the second alignment pattern of the front layer according to the position information. The method is advantageous in improving the accuracy of overlay error measurement and reducing the measurement cost.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of semiconductor manufacturing, and particularly to a method and system for measuring overlay error, a device and a storage medium. BACKGROUND

[0002] Overlay error refers to the offset between the current layer and the previous layer in the lithography process. With the development of integrated circuit manufacturing technology, the control requirement for overlay error is becoming more and more stringent. If the overlay error is too large, it will cause short circuit and open circuit of the device, and affect the quality of the product. However, the overlay error is related to many factors such as the deformation of the mask and the wafer, the inconsistency of the projection system of the lithography machine itself and the displacement of the wafer worktable, and the influence of external environmental factors such as temperature, humidity and vibration.

[0003] Since the integrated circuit chip is manufactured by stacking multiple layers of structures, the structure formed by each lithography process needs to be aligned with each layer of structure formed before, so the overlay precision between each layer of structure directly affects the effectiveness and yield of the integrated circuit chip. In the preparation process of the semiconductor chip, the process parameters for preparing the integrated circuit chip can be adjusted according to the overlay error value to improve the effectiveness and yield of the integrated circuit chip. The deviation of the interlayer overlay alignment will have a great influence on the performance of the device, and may even cause the device to fail, reduce the yield, waste time and money, and increase the cost. Therefore, OVL calculation is becoming more and more important, and measuring and calculating accurate overlay error value is a key step to improve the yield. SUMMARY

[0004] The problem solved by the embodiments of the present application is to provide a method and system for measuring overlay error, a device and a storage medium, to improve the accuracy of overlay error measurement and reduce the measurement cost.

[0005] To solve the above problem, the embodiments of the present application provide a method for measuring overlay error, comprising: providing a previous layer structure and a current layer structure on the previous layer structure, the previous layer structure comprising a plurality of second alignment patterns, and the current layer structure comprising a plurality of measurement areas corresponding to the second alignment patterns; setting a measurement interval of the current layer pattern; in each measurement area of the current layer, obtaining a plurality of measurement patterns arranged in parallel at the measurement interval, including a first alignment pattern and other measurement patterns on both sides of the first alignment pattern; taking each measurement pattern as a measurement position, obtaining a first alignment signal of the measurement pattern and the second alignment pattern of the previous layer; obtaining position information of the measurement pattern at the center position according to a plurality of first alignment signals; and obtaining the overlay error of the first alignment pattern and the second alignment pattern of the previous layer according to the position information.

[0006] Optionally, the first alignment signal includes an optical signal.

[0007] Optionally, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of first alignment signals, including: performing dimension reduction processing on the plurality of first alignment signals to obtain corresponding second alignment signals; and obtaining the position information of the measurement pattern at the center position in the measurement pattern according to the plurality of second alignment signals.

[0008] Optionally, before the dimension reduction processing on the plurality of first alignment signals, the method further includes: in each measurement area, performing simplified processing on the first alignment signal, and subtracting the first alignment signal corresponding to the first alignment pattern from the first alignment signal of each measurement pattern; and in the dimension reduction processing on the plurality of first alignment signals, performing dimension reduction processing on the first alignment signal after the simplified processing.

[0009] Optionally, the dimension reduction processing on the plurality of first alignment signals is performed by using a principal component analysis method.

[0010] Optionally, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of second alignment signals, including: selecting, as third alignment signals, data corresponding to a dimension that can best reflect a nonlinear feature of the overlay error from the plurality of second alignment signals; and obtaining the position information of the measurement pattern at the center position in the measurement pattern according to the plurality of third alignment signals.

[0011] Optionally, the data corresponding to the dimension that can best reflect the nonlinear feature of the overlay error is selected as the third alignment signal according to a key performance indicator.

[0012] Optionally, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of third alignment signals, including: taking the plurality of third alignment signals as output signals of machine learning, and taking the plurality of first alignment signals as input signals of machine learning, to obtain an algorithm model of machine learning; taking the plurality of first alignment signals as input signals, and obtaining corresponding fourth alignment signals according to the algorithm model; and obtaining the position information of the measurement pattern at the center position in the measurement pattern according to the plurality of fourth alignment signals.

[0013] Optionally, the position information of the measurement pattern in the center position in the measurement pattern is obtained according to the plurality of fourth alignment signals, including: performing function fitting on the plurality of fourth alignment signals of the plurality of measurement areas to obtain an ideal function; obtaining an ideal signal value corresponding to each measurement position in each measurement area according to the ideal function; obtaining an updated machine learning algorithm model according to the plurality of ideal signal values; obtaining updated plurality of fourth alignment signals according to the algorithm model; judging whether the function topography of the ideal function meets the feature requirement; if yes, obtaining the position information of the measurement pattern in the center position in the measurement pattern according to the updated plurality of fourth alignment signals; otherwise, returning to perform function fitting on the plurality of fourth alignment signals of the plurality of measurement areas to obtain an ideal function.

[0014] Optionally, the machine learning algorithm model is obtained by using a supervised learning algorithm or a neural network algorithm.

[0015] Optionally, the function fitting on the plurality of fourth alignment signals of the plurality of measurement areas to obtain an ideal function includes: in each measurement area, performing decentralization processing on the plurality of fourth alignment signals along the data direction of the measurement interval; after the decentralization processing, obtaining a function type formed by the plurality of fourth alignment signals; and fitting the plurality of fourth alignment signals of the plurality of measurement areas into the ideal function by using a fitting function of the same type as the function type.

[0016] Optionally, the fitting function of the same type as the function type is used to fit the plurality of fourth alignment signals of the plurality of measurement areas into the ideal function, and the order of the fitting function used this time is higher than the order of the fitting function used last time.

[0017] Optionally, the updated machine learning algorithm model is obtained according to the plurality of ideal signal values, including: taking the plurality of ideal signal values as the output signal of machine learning, and taking the plurality of first alignment signals as the input signal of machine learning to update the algorithm model of machine learning; and the updated plurality of fourth alignment signals is obtained according to the algorithm model, including: taking the plurality of ideal signals as the input signal, and obtaining the updated plurality of fourth alignment signals according to the updated algorithm model.

[0018] Optionally, the position information of the measurement pattern in the center position in the measurement pattern is obtained according to the plurality of fourth alignment signals, including: in each measurement area, obtaining a center point of a point graph formed by the plurality of fourth alignment signals; and obtaining a measurement interval corresponding to the center point.

[0019] Optionally, the overlay error between the first alignment pattern and the second alignment pattern of the previous layer is obtained according to the position information, including: taking a negative value of the measurement interval corresponding to the center point as the overlay error.

[0020] Correspondingly, the embodiment of the present application also provides a lithography error measurement system, comprising: a structure providing module, configured to provide a front layer structure and a current layer structure on the front layer structure, wherein the front layer structure comprises a plurality of second alignment patterns, and the current layer structure comprises a plurality of measurement areas corresponding to the second alignment patterns; a measurement interval setting module, configured to set a measurement interval of the current layer structure; a measurement pattern obtaining module, configured to obtain, in each measurement area of the current layer structure, a plurality of measurement patterns arranged in parallel at the measurement interval, wherein the measurement patterns comprise a first alignment pattern and other measurement patterns arranged on both sides of the first alignment pattern; a first alignment signal obtaining module, configured to obtain, by taking each measurement pattern as a measurement position, a first alignment signal of the measurement pattern and the second alignment pattern of the front layer; a position information obtaining module, configured to obtain position information of a measurement pattern at a center position in the measurement pattern according to a plurality of first alignment signals; and a lithography error obtaining module, configured to obtain a lithography error of the first alignment pattern and the second alignment pattern of the front layer according to the position information.

[0021] Correspondingly, the embodiment of the present application also provides a device, comprising at least one memory and at least one processor, wherein the memory stores one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the lithography error measurement method provided by the embodiment of the present application.

[0022] Correspondingly, the embodiment of the present application also provides a storage medium, wherein the storage medium stores one or more computer instructions, and the one or more computer instructions are used to implement the lithography error measurement method provided by the embodiment of the present application.

[0023] Compared with the prior art, the technical scheme of the embodiment of the present application has the following advantages:

[0024] In the lithography error measurement method provided by the embodiment of the present application, the measurement interval of the current layer structure is set, the plurality of measurement patterns arranged in parallel at the measurement interval are obtained in each measurement area of the current layer structure, the first alignment signal of the measurement pattern and the second alignment pattern of the front layer is obtained by taking each measurement pattern as a measurement position, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to a plurality of first alignment signals, and the lithography error of the first alignment pattern and the second alignment pattern of the front layer is obtained according to the position information; by setting the measurement interval, the first alignment signal of each measurement position is detected, the change of the first alignment signal is detected, the lithography error is obtained according to the mutation of the first alignment signal, that is, the lithography error is obtained by using a nonlinear method, which is beneficial to improve the accuracy of the lithography error measurement, and the measurement cost is low. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 is a flowchart of the lithography error measurement method according to an embodiment of the present application.

[0026] Figure 2 is a corresponding schematic diagram of an embodiment of the overlay error measurement method of the present application;

[0027] Figure 3 is a functional block diagram of an embodiment of the overlay error measurement system of the present application;

[0028] Figure 4 is a hardware structure diagram of an embodiment of the device provided by the present application. DETAILED DESCRIPTION

[0029] As known from the prior art, in the process of semiconductor structure manufacturing, some process flows cause the alignment marks on the wafer to be asymmetric, which results in that the absolute overlay error between the adjacent two layers of structures cannot be accurately obtained in the optical overlay error measurement process.

[0030] To solve the technical problem, an embodiment of the present application provides an overlay error measurement method. Figure 1 , a flowchart of an embodiment of the overlay error measurement method of the present application is shown.

[0031] In the embodiment, the overlay error measurement method comprises the following basic steps:

[0032] Step S1: providing a front layer structure and a current layer structure on the front layer structure, the front layer structure comprising a plurality of second alignment patterns, and the current layer structure comprising a plurality of measurement regions corresponding to the second alignment patterns;

[0033] Step S2: setting a measurement interval of the current layer pattern;

[0034] Step S3: in each measurement region of the current layer, a plurality of measurement patterns parallelly arranged at the measurement interval are obtained, including a first alignment pattern and other measurement patterns on both sides of the first alignment pattern;

[0035] Step S4: taking each measurement pattern as a measurement position, a first alignment signal of the measurement pattern and the second alignment pattern of the front layer is obtained;

[0036] Step S5: according to the plurality of first alignment signals, position information of the measurement pattern at the center position in the measurement pattern is obtained;

[0037] Step S6: according to the position information, an overlay error of the first alignment pattern and the second alignment pattern of the front layer is obtained.

[0038] In the embodiment of the present application, the measurement interval is set, the first alignment signal of each measurement position is detected, the change of the first alignment signal is detected, the overlay error is obtained according to the mutation of the first alignment signal, that is, the nonlinear method is used to obtain the overlay error, which is beneficial to improve the accuracy of the overlay error measurement, and the measurement cost is low.

[0039] In order to make the above-mentioned purpose, characteristics and advantages of the embodiments of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0040] Figure 2 is the corresponding schematic diagram in the embodiment of the overlay error measurement method of the present application.

[0041] Step S1 is performed: a front layer structure and a current layer structure on the front layer structure are provided, the front layer structure includes a plurality of second alignment patterns, and the current layer structure includes a plurality of measurement areas corresponding to the second alignment patterns.

[0042] The second alignment patterns of the front layer structure and the measurement areas corresponding to the second alignment patterns of the current layer structure are used for alignment of the current layer and the front layer, and the overlay error of the current layer and the front layer is obtained.

[0043] It should be noted that in the present embodiment, the measurement area of the current layer structure corresponds to the second alignment pattern of the front layer structure, that is, the front layer structure has a plurality of second alignment patterns at different positions, and each second alignment pattern has a corresponding measurement area in the current layer structure.

[0044] Step S2 is performed: a measurement interval of the current layer pattern is set.

[0045] In the current layer structure, the measurement interval of the current layer pattern is set, which is used to arrange the measurement patterns in the measurement area.

[0046] In the present embodiment, in actual application, the measurement interval is set according to specific requirements, the measurement interval is set smaller, which can have higher measurement accuracy of the overlay error, and for the case where the measurement accuracy requirement is not high, the size of the measurement interval can be appropriately relaxed.

[0047] Step S3 is performed: in each measurement area of the current layer, a plurality of measurement patterns parallelly arranged at the measurement interval are obtained, including the first alignment pattern and other measurement patterns on both sides of the first alignment pattern.

[0048] The measurement patterns are used for measurement with the second alignment patterns of the front layer structure to obtain the first alignment signal, wherein the first alignment pattern in the measurement patterns is used for measurement with the second alignment pattern to obtain the overlay error.

[0049] As an example, the second alignment pattern of the front layer structure is a fin structure, and the measurement pattern of the layer structure is a plurality of gate structures arranged in parallel, the gate structures being arranged in parallel along the extension direction of the fin structure and crossing the fin structure.

[0050] In the embodiment, in each measurement area of the layer, a plurality of measurement patterns are arranged, the spacing between adjacent measurement patterns is a measurement interval, that is, each measurement pattern corresponds to different position information, then the position information of the measurement pattern at the center position is obtained by acquiring the first alignment signal of each measurement pattern and the second alignment pattern of the front layer.

[0051] As an example, the measurement interval is set to 1 nm, and the position information of the first alignment pattern is taken as the origin, marked as OVL, then in one measurement area, the position information of the plurality of measurement patterns arranged in sequence is OVL+n, OVL+(n-1), OVL+(n-2)…OVL+0…OVL-n, OVL-(n+1), OVL-(n+2), a total of 2n+3 measurement patterns are arranged.

[0052] It should be noted that in the embodiment, the first alignment pattern is a pattern structure for measuring overlay error, in the measurement area, the first alignment pattern is arranged on both sides of the plurality of measurement patterns, but the first alignment pattern can be located at the center position of the plurality of measurement patterns, or can not be located at the center position of the plurality of measurement patterns.

[0053] Step S4 is performed: taking each measurement pattern as a measurement position, acquiring the first alignment signal of the measurement pattern and the second alignment pattern of the front layer.

[0054] The first alignment signal is used to judge the positional relationship between the measurement pattern and the second alignment pattern of the front layer, so as to obtain the position information of the measurement pattern at the center position.

[0055] In the embodiment, the first alignment signal includes an optical signal.

[0056] The measurement is performed by acquiring the optical signal, which is simple and easy to operate, and can be performed in real time when the layer structure is formed, so that the overlay error is obtained quickly and conveniently.

[0057] In other embodiments, the first alignment signal can also be an electrical signal.

[0058] Step S5 is performed: according to the plurality of first alignment signals, the position information of the measurement pattern at the center position is obtained.

[0059] The position information of the measurement pattern at the center position is obtained according to the plurality of first alignment signals, so that the overlay error of the first alignment pattern and the second alignment pattern is subsequently obtained according to the position information of the measurement pattern at the center position.

[0060] Specifically, in the embodiment, the measurement pattern at the center position is the best position relative to the second alignment pattern, that is, the measurement pattern at the center position is the reference position required by the process in the semiconductor process, and the first alignment pattern is the formation position of the first alignment pattern in the layer structure. Moreover, as known from the foregoing, the position information includes the information of the relative position deviation of each measurement pattern relative to the first alignment pattern, so that the overlay error can be subsequently obtained according to the position information of the measurement pattern at the center position.

[0061] In the embodiment, before the plurality of first alignment signals are subsequently subjected to dimension reduction processing, the method further includes: in each measurement area, subtracting the first alignment signal corresponding to the first alignment pattern from the first alignment signal of each measurement pattern to perform simplification processing on the first alignment signal.

[0062] The first alignment signal corresponding to the first alignment pattern is taken as a reference to perform simplification processing on the first alignment signal of each measurement pattern, which is beneficial to simplify the subsequent dimension reduction processing process and improve the efficiency of the dimension reduction processing.

[0063] In the embodiment, the position information of the measurement pattern at the center position is obtained according to the plurality of first alignment signals, including: subjecting the plurality of first alignment signals to dimension reduction processing to obtain corresponding second alignment signals.

[0064] The plurality of first alignment signals are subjected to dimension reduction processing to obtain corresponding second alignment signals, and the position information of the measurement pattern at the center position is subsequently obtained through the second alignment signals obtained after the dimension reduction, which is beneficial to simplify the processing, reduce the amount of operation data, shorten the operation time, and improve the processing efficiency.

[0065] Correspondingly, in the embodiment, the first alignment signals subjected to the simplification processing are subjected to dimension reduction processing in the dimension reduction processing of the plurality of first alignment signals, which is beneficial to improve the processing efficiency.

[0066] In the embodiment, the plurality of first alignment signals are subjected to dimension reduction processing by using a principal component analysis method.

[0067] The principal component analysis method (PCA) is used for dimension reduction processing, which can use less dimensional data to replace the original more dimensional data while reflecting the information of the original more dimensional data, which is beneficial to achieve the effect of dimension reduction while retaining the original information of the plurality of first alignment signals.

[0068] Specifically, as an example, the embodiment is m first alignment signals, each first alignment signal is n-dimensional, in the embodiment, the principal component analysis method is used to reduce the dimension of the plurality of first alignment signals, including: subtracting the mean value of each dimension from the dimension, and forming an n*m matrix X; calculating the covariance matrix c=1 / m XX T ; calculating the eigenvalues and eigenvectors of the covariance matrix, and arranging the n eigenvectors in a matrix A from top to bottom according to the corresponding eigenvalues from large to small; taking the top k eigenvectors of the matrix A to form a matrix P; Y=PX, which is the data after dimensionality reduction to K.

[0069] In the embodiment, the top k eigenvectors of the matrix A are taken according to the principal component contribution rate and the cumulative contribution rate. Generally, the greater the contribution rate of the principal component, the more information the original data retains.

[0070] Correspondingly, in the embodiment, the position information of the measurement pattern in the center position in the measurement pattern is obtained according to the plurality of second alignment signals.

[0071] In the embodiment, the position information of the measurement pattern in the center position in the measurement pattern is obtained according to the plurality of second alignment signals, including: selecting data corresponding to a dimension of a non-linear feature of a overlay error in the plurality of second alignment signals as a third alignment signal.

[0072] Selecting data corresponding to a dimension of a non-linear feature of a overlay error in the plurality of second alignment signals as a third alignment signal is beneficial to obtain a third alignment signal with regularity, filter chaotic information, and thus is beneficial to improve the accuracy of the position information of the measurement pattern in the center position in the measurement pattern.

[0073] As an example, each measurement area has 12 measurement patterns, and the third alignment signals of the plurality of measurement areas are plotted into point graphs, each point graph is the third alignment signal corresponding to the 12 measurement patterns in a measurement area, the horizontal coordinate is the position information of the measurement pattern, and the vertical coordinate is the third alignment signal corresponding to the measurement pattern.

[0074] Specifically, in the embodiment, the data corresponding to the dimension of the non-linear feature of the overlay error is selected as the third alignment signal, and the regularity includes an odd function rule or an even function rule.

[0075] In the embodiment, the plurality of third alignment signals obtained are one-dimensional signals.

[0076] In the embodiment, according to the key performance indicator, the data corresponding to the dimension of the non-linear feature of the overlay error in the plurality of second alignment signals is selected as the third alignment signal.

[0077] According to the key performance indicators, the third alignment signal is obtained, which is simple and easy to operate, and can more accurately obtain the data corresponding to the dimension of the non-linear feature that can best reflect the overlay error.

[0078] Correspondingly, in the embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of third alignment signals.

[0079] In the embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of third alignment signals, including: taking the plurality of third alignment signals as the output signal of machine learning, taking the plurality of first alignment signals as the input signal of machine learning, and obtaining the algorithm model of machine learning.

[0080] The third alignment signal is data that meets the feature requirements after dimensionality reduction filtering, and the first alignment signal is original data. Therefore, the machine learning algorithm model established by taking the plurality of third alignment signals as the output signal of machine learning and taking the plurality of first alignment signals as the input signal of machine learning trains a model that can filter out data meeting the feature requirements from the original data, so that subsequent input of original data to the machine learning algorithm model can directly obtain output data meeting the feature requirements through the algorithm model.

[0081] In the embodiment, a supervised learning algorithm or a neural network algorithm is used to obtain the algorithm model of machine learning.

[0082] The supervised learning algorithm or the neural network algorithm is used to obtain the algorithm model of machine learning, which is simple and easy to operate, and the model is more accurate.

[0083] In the embodiment, the plurality of first alignment signals are taken as the input signal, and the corresponding plurality of fourth alignment signals are obtained according to the algorithm model.

[0084] After the machine learning algorithm model is established, the plurality of first alignment signals are taken as the input signal, and more accurate fourth alignment signals can be directly output through the model. The fourth alignment signals are used to obtain the position information of the measurement pattern at the center position.

[0085] Correspondingly, in the embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of fourth alignment signals.

[0086] In the embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of fourth alignment signals, including: function fitting the plurality of fourth alignment signals of the plurality of measurement areas to obtain an ideal function.

[0087] The fourth alignment signals of the plurality of measurement areas are functionally fitted to obtain an ideal function with more obvious topographic characteristics, which is beneficial to obtaining ideal data to update the fourth alignment signals according to the ideal function.

[0088] In this embodiment, the fourth alignment signals of the plurality of measurement areas are functionally fitted to obtain an ideal function, including: in each measurement area, the fourth alignment signals are decentered along the data direction of the measurement interval.

[0089] The decentering processing means that the origin of the function formed by the plurality of fourth alignment signals is moved from the origin of the position information to the position of the measurement pattern at the center position.

[0090] The decentering processing can make the function formed by the plurality of fourth alignment signals uniform in topography, so that the plurality of fourth alignment signals can be functionally fitted subsequently.

[0091] In this embodiment, after the decentering processing, the type of the function formed by the plurality of fourth alignment signals is obtained.

[0092] The fourth alignment signals are functionally fitted according to the type of the function formed by the plurality of fourth alignment signals.

[0093] In this embodiment, the plurality of fourth alignment signals of the plurality of measurement areas are fitted into an ideal function by using a fitting function of the same type as the type of the function.

[0094] As an example, the type of the function formed by the plurality of fourth alignment signals is an odd function, and an odd function is used to fit the plurality of fourth alignment signals; the type of the function formed by the plurality of fourth alignment signals is an even function, and an even function is used to fit the plurality of fourth alignment signals.

[0095] In this embodiment, the plurality of fourth alignment signals of the plurality of measurement areas are fitted into an ideal function by using a fitting function of the same type as the type of the function, and the order of the fitting function used this time is higher than the order of the fitting function used last time.

[0096] The order of the fitting function used this time is higher than the order of the fitting function used last time, so that in the process of continuous iterative fitting, the topographic characteristics of the ideal function become more and more obvious. Figure 4 The change trend indicated by the arrow makes the topographic characteristics of the ideal function more and more obvious.

[0097] In this embodiment, according to the ideal function, ideal signal values corresponding to the plurality of measurement positions in each measurement area are obtained.

[0098] The ideal signal values are used to update the algorithm model of machine learning, so that the algorithm model of machine learning is more accurate after each function fitting.

[0099] In this embodiment, the updated machine learning algorithm model is obtained according to a plurality of ideal signal values.

[0100] The updated machine learning algorithm model is obtained according to a plurality of ideal signal values, so that the machine learning algorithm model is continuously updated and iterated, and is continuously more accurate.

[0101] In this embodiment, the updated machine learning algorithm model is obtained according to a plurality of ideal signal values, including: taking a plurality of ideal signal values as output signals of machine learning, taking a plurality of first alignment signals as input signals of machine learning, and updating the machine learning algorithm model.

[0102] Taking a plurality of ideal signal values as output signals of machine learning, taking a plurality of first alignment signals as input signals of machine learning, and updating the machine learning algorithm model, so that the machine learning algorithm model is continuously updated and iterated according to actual data, and is continuously more accurate.

[0103] In this embodiment, a plurality of fourth alignment signals are obtained according to the updated algorithm model.

[0104] The updated plurality of fourth alignment signals are used to obtain position information of a measurement pattern in a center position in a measurement pattern.

[0105] In this embodiment, the updated plurality of fourth alignment signals are obtained according to the algorithm model, including: taking a plurality of ideal signals as input signals, and obtaining the updated plurality of fourth alignment signals according to the updated algorithm model.

[0106] The updated plurality of fourth alignment signals are obtained according to the updated algorithm model, so that the fourth alignment signals are also continuously iterated and updated, and are continuously more accurate.

[0107] In this embodiment, it is judged whether a function appearance of an ideal function meets a feature requirement.

[0108] It is judged whether a fitting process needs to be returned to iterate according to whether a feature performance of the function appearance of the ideal function meets a feature accuracy requirement.

[0109] Specifically, in this embodiment, if yes, position information of a measurement pattern in a center position in a measurement pattern is obtained according to the updated plurality of fourth alignment signals; otherwise, a function fitting is performed on a plurality of fourth alignment signals of a plurality of measurement areas to obtain an ideal function.

[0110] In this embodiment, the position information of the measurement pattern in the center position in the measurement pattern is obtained according to the plurality of fourth alignment signals, including: in each measurement area, a center point of a point graph formed by the plurality of fourth alignment signals is obtained.

[0111] In each measurement area, the center point of the dot diagram is obtained according to the dot diagram constituted by the plurality of fourth alignment signals, which is intuitive and efficient, and the position information of the center point is the position information of the measurement pattern in the center position in the plurality of measurement patterns.

[0112] In this embodiment, the measurement interval corresponding to the center point is obtained.

[0113] The measurement interval corresponding to the center point is obtained, so that the position information corresponding to the center point is obtained.

[0114] As an example, the measurement interval corresponding to the center point is +2, and the position information corresponding to the center point is OVL+2.

[0115] Step S6 is performed: the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is obtained according to the position information.

[0116] According to the position information, the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is obtained, which can more accurately obtain the absolute overlay error of the first alignment pattern and the second alignment pattern of the previous layer.

[0117] In this embodiment, by setting the measurement interval, the change of the first alignment signal at each measurement position is detected, the change of the first alignment signal is detected, and the overlay error is obtained according to the mutation of the first alignment signal, that is, the nonlinear method is used to obtain the overlay error, which is beneficial to improve the accuracy of the overlay error measurement, and the measurement cost is lower.

[0118] Specifically, in this embodiment, the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is obtained according to the position information, including: taking the negative value of the measurement interval corresponding to the center point as the overlay error.

[0119] As an example, the measurement interval corresponding to the center point is +2, and the position information corresponding to the center point is OVL+2, and the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is -2.

[0120] Correspondingly, the present application also provides a kind of overlay error measurement system. Figure 3 It is the function block diagram of an embodiment of the optical proximity correction system of the present application.

[0121] In the embodiment, the optical proximity correction system 50 comprises: a structure providing module 501 configured to provide a front layer structure and a current layer structure on the front layer structure, the front layer structure comprising a plurality of second alignment patterns, and the current layer structure comprising a plurality of measurement areas corresponding to the second alignment patterns; a measurement interval setting module 502 configured to set a measurement interval of the current layer pattern; a measurement pattern obtaining module 503 configured to obtain, in each measurement area of the current layer, a plurality of measurement patterns arranged in parallel at the measurement interval, including a first alignment pattern and other measurement patterns on both sides of the first alignment pattern; a first alignment signal obtaining module 504 configured to obtain, taking each measurement pattern as a measurement position, a first alignment signal of the measurement pattern and the second alignment pattern of the front layer; a position information obtaining module 505 configured to obtain position information of a measurement pattern at a center position in the measurement pattern according to a plurality of first alignment signals; and an overlay error obtaining module 506 configured to obtain an overlay error of the first alignment pattern and the second alignment pattern of the front layer according to the position information.

[0122] Step S1 is performed: a front layer structure and a current layer structure on the front layer structure are provided, the front layer structure comprising a plurality of second alignment patterns, and the current layer structure comprising a plurality of measurement areas corresponding to the second alignment patterns.

[0123] The second alignment patterns of the front layer structure and the measurement areas of the current layer structure corresponding to the second alignment patterns are used for alignment of the current layer and the front layer, and an overlay error of the current layer and the front layer is obtained.

[0124] It should be noted that, in the embodiment, the measurement areas of the current layer structure correspond to the second alignment patterns of the front layer structure, which means that the front layer structure has a plurality of second alignment patterns at different positions, and each second alignment pattern has a corresponding measurement area in the current layer structure.

[0125] Step S2 is performed: a measurement interval of the current layer pattern is set.

[0126] In the current layer structure, the measurement interval of the current layer pattern is set, which is used to arrange the measurement patterns in the measurement area.

[0127] In the embodiment, in actual application, the measurement interval is set according to specific requirements, the measurement interval is set to be small, and the measurement precision of the overlay error is high. In the case where the measurement precision requirement is not high, the size of the measurement interval can be appropriately relaxed.

[0128] Step S3 is performed: in each measurement area of the current layer, a plurality of measurement patterns arranged in parallel at the measurement interval are obtained, including a first alignment pattern and other measurement patterns on both sides of the first alignment pattern.

[0129] The measurement pattern is used to acquire a first alignment signal with the second alignment pattern of the front layer structure, wherein the first alignment pattern in the measurement pattern is used to acquire overlay error with the second alignment pattern.

[0130] As an example, the second alignment pattern of the front layer structure is a fin structure, and the measurement pattern of the layer structure is a plurality of gate structures arranged in parallel, the gate structures being arranged in parallel along the extension direction of the fin structure and crossing the fin structure.

[0131] In the embodiment, in each measurement area of the layer, a plurality of measurement patterns are arranged, the spacing between adjacent measurement patterns is a measurement interval, that is, each measurement pattern corresponds to different position information, and then the first alignment signal corresponding to each position information is acquired by acquiring the first alignment signal of each measurement pattern and the second alignment pattern of the front layer, so as to obtain the position information of the measurement pattern at the center position.

[0132] As an example, the measurement interval is set to 1 nm, and the position information of the first alignment pattern is taken as the origin, marked as OVL, then in one measurement area, the position information of the plurality of measurement patterns arranged in sequence is OVL+n, OVL+(n-1), OVL+(n-2)……OVL+0……OVL-n, OVL-(n+1), OVL-(n+2), and a total of 2n+3 measurement patterns are arranged.

[0133] It should be noted that in the embodiment, the first alignment pattern is a pattern structure used for measuring overlay error, and in the measurement area, the first alignment pattern is arranged on both sides of the plurality of measurement patterns, but the first alignment pattern can be located at the center position of the plurality of measurement patterns or can not be located at the center position of the plurality of measurement patterns.

[0134] The step S4 is performed: acquiring the first alignment signal of the measurement pattern and the second alignment pattern of the front layer with each measurement pattern as the measurement position.

[0135] The first alignment signal is used to judge the positional relationship between the measurement pattern and the second alignment pattern of the front layer, so as to obtain the position information of the measurement pattern at the center position.

[0136] In the embodiment, the first alignment signal includes an optical signal by acquiring the first alignment signal of the measurement pattern and the second alignment pattern of the front layer with each measurement pattern as the measurement position.

[0137] The measurement is performed by acquiring the optical signal, which is simple and easy to operate, and can be performed in real time when the layer structure is formed, so that the overlay error is acquired quickly and conveniently.

[0138] In other embodiments, the first alignment signal can also be an electrical signal.

[0139] The step S5 is performed to obtain position information of the measurement pattern at the center position in the measurement pattern according to the plurality of first alignment signals.

[0140] The position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of first alignment signals, so that the overlay error of the first alignment pattern and the second alignment pattern is obtained according to the position information of the measurement pattern at the center position in the subsequent process.

[0141] Specifically, in the embodiment, the measurement pattern at the center position in the measurement pattern is the best position relative to the second alignment pattern, that is, the measurement pattern at the center position in the measurement pattern is the reference position required by the process in the semiconductor process, and the first alignment pattern is the formation position of the first alignment pattern in the layer structure, and moreover, as known from the foregoing, the position information includes the information of the relative position deviation of the individual measurement pattern relative to the first alignment pattern, so that the overlay error can be obtained according to the position information of the measurement pattern at the center position in the measurement pattern in the subsequent process.

[0142] In the embodiment, before the plurality of first alignment signals are subjected to the dimension reduction processing in the subsequent process, the first alignment signal is subjected to a simplification processing in each measurement area, and the first alignment signal of each measurement pattern is subtracted by the first alignment signal corresponding to the first alignment pattern.

[0143] The first alignment signal corresponding to the first alignment pattern is taken as a reference to simplify the first alignment signal of each measurement pattern, which is beneficial to simplify the subsequent dimension reduction processing process and improve the efficiency of the dimension reduction processing.

[0144] In the embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of first alignment signals, including: the plurality of first alignment signals are subjected to dimension reduction processing to obtain corresponding second alignment signals.

[0145] The plurality of first alignment signals are subjected to dimension reduction processing to obtain corresponding second alignment signals, and the position information of the measurement pattern at the center position is obtained through the second alignment signals obtained after the dimension reduction in the subsequent process, which is beneficial to simplify the processing, reduce the amount of operation data, shorten the operation time, and improve the processing efficiency.

[0146] Correspondingly, in the embodiment, the first alignment signal subjected to the simplification processing is subjected to dimension reduction processing in the dimension reduction processing of the plurality of first alignment signals, which is beneficial to improve the processing efficiency.

[0147] In the embodiment, the principal component analysis method is used to subject the plurality of first alignment signals to dimension reduction processing.

[0148] The principle component analysis (PCA) is used for dimension reduction processing, so that the data with less dimensions can replace the data with more dimensions, and the information of the data with more dimensions can be reflected, which is beneficial to retaining the original information of the plurality of first alignment signals while achieving the effect of dimension reduction.

[0149] Specifically, as an example, the embodiment is m first alignment signals, each of which is n-dimensional, and the dimension reduction processing of the plurality of first alignment signals by using the principle component analysis in the embodiment includes: subtracting the mean value of each dimension from the dimension to form an n*m matrix X; calculating the covariance matrix c=1 / m XX T ; calculating the eigenvalues and eigenvectors of the covariance matrix, and arranging the n eigenvectors in a matrix A from top to bottom according to the corresponding eigenvalues from large to small; taking the top k eigenvectors of the matrix A to form a matrix P; Y=PX, which is the data after dimension reduction to K dimensions.

[0150] In the embodiment, the top k eigenvectors of the matrix A are taken according to the principle component contribution rate and the cumulative contribution rate, and generally, the greater the contribution rate of the principle component, the more information of the original data is retained.

[0151] Correspondingly, in the embodiment, the position information of the measurement pattern in the center position in the measurement pattern is obtained according to the plurality of second alignment signals.

[0152] In the embodiment, the position information of the measurement pattern in the center position in the measurement pattern is obtained according to the plurality of second alignment signals, including: selecting the data corresponding to the dimension of the non-linear feature of the overlay error that can best reflect the non-linear feature of the overlay error in the plurality of second alignment signals as the third alignment signal.

[0153] Selecting the data corresponding to the dimension of the non-linear feature of the overlay error that can best reflect the non-linear feature of the overlay error in the plurality of second alignment signals as the third alignment signal is beneficial to obtaining the third alignment signal with regularity, filtering the chaotic information, and thus improving the accuracy of obtaining the position information of the measurement pattern in the center position in the measurement pattern.

[0154] As an example, each measurement area has 12 measurement patterns, and the third alignment signals of the plurality of measurement areas are plotted into point graphs, each point graph is the third alignment signal corresponding to the 12 measurement patterns in a measurement area, the horizontal coordinate is the position information of the measurement pattern, and the vertical coordinate is the third alignment signal corresponding to the measurement pattern.

[0155] Specifically, in the embodiment, the data corresponding to the dimension of the non-linear feature of the overlay error that can best reflect the non-linear feature of the overlay error is taken as the third alignment signal, and the regularity formed includes the odd function regularity or the even function regularity.

[0156] In this embodiment, the plurality of third alignment signals obtained are one-dimensional signals.

[0157] In this embodiment, according to the key performance indicators, the data corresponding to the dimension of the non-linear feature that can best reflect the overlay error in the plurality of second alignment signals is selected as the third alignment signal.

[0158] According to the key performance indicators, the third alignment signal is obtained, which is simple and easy to operate, and can accurately obtain the data corresponding to the dimension of the non-linear feature that can best reflect the overlay error.

[0159] Correspondingly, in this embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of third alignment signals.

[0160] In this embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of third alignment signals, including: taking the plurality of third alignment signals as the output signal of machine learning, taking the plurality of first alignment signals as the input signal of machine learning, and obtaining the algorithm model of machine learning.

[0161] The third alignment signal is data that meets the feature requirements after dimensionality reduction filtering, and the first alignment signal is original data. Therefore, the machine learning algorithm model established by taking the plurality of third alignment signals as the output signal of machine learning and the plurality of first alignment signals as the input signal of machine learning trains a model that can filter out data meeting the feature requirements from the original data, so that subsequent input of original data to the machine learning algorithm model can directly obtain output data meeting the feature requirements through the algorithm model.

[0162] In this embodiment, a supervised learning algorithm or a neural network algorithm is used to obtain the algorithm model of machine learning.

[0163] The supervised learning algorithm or the neural network algorithm is used to obtain the algorithm model of machine learning, which is simple and easy to operate, and the model is constructed more accurately.

[0164] In this embodiment, the plurality of first alignment signals are taken as the input signal, and the corresponding plurality of fourth alignment signals are obtained according to the algorithm model.

[0165] After the machine learning algorithm model is established, the plurality of first alignment signals are taken as the input signal, and more accurate fourth alignment signals can be directly output through the model. The fourth alignment signals are used to obtain the position information of the measurement pattern at the center position.

[0166] Correspondingly, in this embodiment, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the plurality of fourth alignment signals.

[0167] In the embodiment, the position information of the measurement pattern at the center position in the measurement pattern obtained according to the plurality of fourth alignment signals comprises: performing function fitting on the plurality of fourth alignment signals of the plurality of measurement areas to obtain an ideal function.

[0168] The plurality of fourth alignment signals of the plurality of measurement areas are function fitted to obtain an ideal function with more obvious topographic characteristics, which is beneficial to subsequent updating of the fourth alignment signals by obtaining ideal data according to the ideal function.

[0169] In the embodiment, the plurality of fourth alignment signals of the plurality of measurement areas are function fitted to obtain an ideal function, comprising: in each measurement area, the plurality of fourth alignment signals are decentered along the data direction of the measurement interval.

[0170] Decentering refers to moving the origin of the function composed of the plurality of fourth alignment signals from the origin of the position information to the position of the measurement pattern at the center position.

[0171] Decentering can make the topography of the function composed of the plurality of fourth alignment signals uniform, so that the plurality of fourth alignment signals can be function fitted subsequently.

[0172] In the embodiment, after decentering, the type of the function composed of the plurality of fourth alignment signals is obtained.

[0173] The fourth alignment signal is function fitted according to the type of the function composed of the plurality of fourth alignment signals.

[0174] In the embodiment, the plurality of fourth alignment signals of the plurality of measurement areas are fitted into an ideal function by using a fitting function of the same type as the type of the function.

[0175] As an example, the type of the function composed of the plurality of fourth alignment signals is an odd function, and an odd function is used to fit the plurality of fourth alignment signals; the type of the function composed of the plurality of fourth alignment signals is an even function, and an even function is used to fit the plurality of fourth alignment signals.

[0176] In the embodiment, the plurality of fourth alignment signals of the plurality of measurement areas are fitted into an ideal function by using a fitting function of the same type as the type of the function, and the order of the fitting function used this time is higher than the order of the fitting function used last time.

[0177] The order of the fitting function used this time is higher than the order of the fitting function used last time, so that in the process of continuous iterative fitting, the topographic characteristics of the ideal function become more and more obvious. Figure 4 The change trend indicated by the arrow makes the topographic characteristics of the ideal function more and more obvious.

[0178] In this embodiment, according to the ideal function, the ideal signal values corresponding to the plurality of measurement positions in each measurement area are obtained.

[0179] The ideal signal values are used to update the algorithm model of machine learning, so that the algorithm model of machine learning is more accurate after each function fitting.

[0180] In this embodiment, the updated algorithm model of machine learning is obtained according to the plurality of ideal signal values.

[0181] The updated algorithm model of machine learning is obtained according to the plurality of ideal signal values, so that the algorithm model of machine learning is continuously updated and iterated, and is continuously more accurate.

[0182] In this embodiment, the updated algorithm model of machine learning is obtained according to the plurality of ideal signal values, comprising: taking the plurality of ideal signal values as the output signal of machine learning, taking the plurality of first alignment signals as the input signal of machine learning, and updating the algorithm model of machine learning.

[0183] The plurality of ideal signal values are taken as the output signal of machine learning, the plurality of first alignment signals are taken as the input signal of machine learning, and the algorithm model of machine learning is updated, so that the algorithm model of machine learning is continuously updated and iterated according to the actual data, and is continuously more accurate.

[0184] In this embodiment, the updated plurality of fourth alignment signals are obtained according to the algorithm model.

[0185] The updated plurality of fourth alignment signals are used to obtain the position information of the measurement pattern at the center position in the measurement pattern.

[0186] In this embodiment, the updated plurality of fourth alignment signals are obtained according to the algorithm model, comprising: taking the plurality of ideal signals as the input signal, and obtaining the updated plurality of fourth alignment signals according to the updated algorithm model.

[0187] The updated plurality of fourth alignment signals are obtained according to the updated algorithm model, so that the fourth alignment signal is also continuously iterated and updated, and is continuously more accurate.

[0188] In this embodiment, it is judged whether the function appearance of the ideal function meets the feature requirement.

[0189] Whether the characteristic performance of the function appearance of the ideal function meets the accuracy requirement of the characteristic is judged to determine whether the fitting processing of iteration needs to be returned.

[0190] Specifically, in this embodiment, if yes, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the updated plurality of fourth alignment signals; otherwise, the plurality of fourth alignment signals of the plurality of measurement areas are returned to be functionally fitted to obtain the ideal function.

[0191] In the embodiment, the position information of the measurement pattern at the center position in the plurality of measurement patterns is obtained according to the plurality of fourth alignment signals, including: in each measurement area, a center point of a point graph formed by the plurality of fourth alignment signals is obtained.

[0192] In each measurement area, the center point of the point graph formed by the plurality of fourth alignment signals is obtained, which is intuitive and efficient, and the position information of the center point is the position information of the measurement pattern at the center position in the plurality of measurement patterns.

[0193] In the embodiment, the measurement interval corresponding to the center point is obtained.

[0194] The measurement interval corresponding to the center point is obtained, so that the position information corresponding to the center point is obtained.

[0195] As an example, the measurement interval corresponding to the center point is +2, and the position information corresponding to the center point is OVL+2.

[0196] Step S6 is performed: the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is obtained according to the position information.

[0197] According to the position information, the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is obtained, which can more accurately obtain the absolute overlay error of the first alignment pattern and the second alignment pattern of the previous layer.

[0198] In the embodiment, by setting the measurement interval, the change of the first alignment signal at each measurement position is detected, the change of the first alignment signal is detected, and the overlay error is obtained according to the mutation of the first alignment signal, that is, the nonlinear method is used to obtain the overlay error, which is beneficial to improve the accuracy of the overlay error measurement, and the measurement cost is lower.

[0199] Specifically, in the embodiment, the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is obtained according to the position information, including: the negative value of the measurement interval corresponding to the center point is obtained as the overlay error.

[0200] As an example, the measurement interval corresponding to the center point is +2, and the position information corresponding to the center point is OVL+2, and the overlay error of the first alignment pattern and the second alignment pattern of the previous layer is -2.

[0201] Correspondingly, the embodiment of the application also provides a device, which can implement the overlay error measurement method provided by the embodiment of the application by loading the above-mentioned overlay error measurement method in the form of a program. An optional hardware structure of the terminal device provided by the embodiment of the application can be as follows: Figure 4As shown, the terminal device comprises at least one processor 01, at least one communication interface 02, at least one memory 03 and at least one communication bus 04.

[0202] In this embodiment, the number of the processor 01, the communication interface 02, the memory 03 and the communication bus 04 is at least one, and the processor 01, the communication interface 02 and the memory 03 complete communication with each other through the communication bus 04. The communication interface 02 can be an interface of a communication module for network communication, such as an interface of a GSM module. The processor 01 can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The memory 03 can include a high-speed RAM memory and can also include a non-volatile memory (NVM), such as at least one disk memory. The memory 03 stores one or more computer instructions, and the one or more computer instructions are executed by the processor 01 to implement the overlay error measurement method provided by the embodiments of the present application.

[0203] It should be noted that the terminal device described above can also include other devices (not shown) that can not be necessary for the disclosure of the embodiments of the present application; since these other devices can not be necessary for understanding the disclosure of the embodiments of the present application, the embodiments of the present application do not introduce them one by one.

[0204] The embodiments of the present application also provide a storage medium, which stores one or more computer instructions, and the one or more computer instructions are used to implement the overlay error measurement method provided by the embodiments of the present application.

[0205] In the overlay error measurement method provided by the embodiments of the present application, the first alignment signal of each measurement position is detected by setting a measurement interval, the change of the first alignment signal is detected, and the overlay error is obtained according to the mutation of the first alignment signal, that is, the nonlinear method is used to obtain the overlay error, which is beneficial to improve the accuracy of overlay error measurement and has low measurement cost.

[0206] The above-described embodiments of the application are combinations of elements and features of the applications. The elements or features can be applied to one another only in combinations other than those explicitly stated herein. Each embodiment of the application can be realized without relying on other embodiments of the application. In addition, the order of the steps of the methods of the application can be rearranged. Some of the configurations of the embodiments of the application can be included in another embodiment of the application, and the configurations of the embodiments of the application can be replaced with corresponding configurations of another embodiment of the application. The application can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The presently disclosed embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

[0207] Embodiments of the present application can be implemented by various means, for example, hardware, firmware, software, or a combination thereof. In a hardware configuration, the methods according to the exemplary embodiments of the present application can be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, etc. In a firmware or software configuration, the embodiments of the present application can be implemented in the form of a module, a procedure, a function, etc. Software code can be stored in a memory unit and executed by a processor. The memory unit is located at the interior or exterior of the processor and can deliver data to and receive data from the processor via various known means.

[0208] The above description of disclosed embodiments of the application allows skilled in the art to carry out or use the application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Therefore, the application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0209] While the application has been disclosed in connection with the embodiments presented, it should be understood that modifications and / or improvements can be made to the above-described embodiments without departing from the spirit and scope of the application. Thus, the scope of the application should be limited only by the appended claims, and all modifications and / or improvements that come within the scope of the claims are intended to be embraced therein.

Claims

1. A method of metrology of overlay, characterized in that, The method comprises the following steps: providing a front layer structure and a target layer structure on the front layer structure, the front layer structure comprising a plurality of second alignment patterns, and the target layer structure comprising a plurality of measurement areas corresponding to the second alignment patterns; setting a measurement interval of the target layer pattern; in each measurement area of the target layer, obtaining a plurality of measurement patterns arranged in parallel at the measurement interval, including a first alignment pattern and other measurement patterns on both sides of the first alignment pattern; obtaining a first alignment signal of the measurement pattern and the second alignment pattern of the front layer at each measurement position of the measurement pattern; obtaining position information of a measurement pattern at a central position in the measurement pattern according to a plurality of first alignment signals; obtaining overlay error of the first alignment pattern and the second alignment pattern of the front layer according to the position information.

2. The method of overlay metrology of claim 1, wherein, The first alignment signal of the measurement pattern and the second alignment pattern of the front layer at each measurement position of the measurement pattern comprises an optical signal.

3. The method of overlay metrology of claim 1, wherein, The position information of the measurement pattern at the central position in the measurement pattern according to a plurality of first alignment signals comprises: performing dimensionality reduction processing on a plurality of first alignment signals to obtain corresponding second alignment signals; obtaining position information of a measurement pattern at a central position in the measurement pattern according to a plurality of second alignment signals.

4. The overlay metrology method of claim 3, wherein, Before the dimensionality reduction processing on a plurality of first alignment signals, the method further comprises: in each measurement area, performing simplification processing on the first alignment signal, and subtracting the first alignment signal corresponding to the first alignment pattern from the first alignment signal of each measurement pattern; In the dimensionality reduction processing on a plurality of first alignment signals, the first alignment signal after the simplification processing is subjected to dimensionality reduction processing.

5. The overlay metrology method of claim 3, wherein, The dimensionality reduction processing on a plurality of first alignment signals is performed by using principal component analysis.

6. The overlay metrology method of claim 3, wherein, The position information of the measurement pattern at the central position in the measurement pattern according to a plurality of second alignment signals comprises: selecting data corresponding to a dimension that can best reflect the nonlinear characteristics of the overlay error in a plurality of second alignment signals as third alignment signals; obtaining position information of a measurement pattern at a central position in the measurement pattern according to a plurality of third alignment signals.

7. The overlay metrology method of claim 6, wherein, The position information of the measurement pattern at the central position in the measurement pattern according to a plurality of third alignment signals comprises:

8. The overlay metrology method of claim 6, wherein, using a plurality of third alignment signals as output signals of machine learning, and using a plurality of first alignment signals as input signals of machine learning to obtain an algorithm model of machine learning; using a plurality of first alignment signals as input signals, and obtaining a plurality of fourth alignment signals corresponding to the algorithm model; obtaining position information of a measurement pattern at a central position in the measurement pattern according to a plurality of fourth alignment signals. The position information of the measurement pattern at the central position in the measurement pattern according to a plurality of fourth alignment signals comprises:

9. The overlay metrology method of claim 8, wherein, ​ The fourth alignment signals of the multiple measurement areas are functionally fitted to obtain an ideal function; According to the ideal function, the ideal signal values corresponding to the multiple measurement positions in each measurement area are obtained; According to the multiple ideal signal values, the algorithm model of the machine learning is updated; According to the algorithm model, the multiple fourth alignment signals are updated; Determine whether the function profile of the ideal function meets the feature requirement; If yes, the position information of the measurement pattern at the center position in the measurement pattern is obtained according to the multiple updated fourth alignment signals; Otherwise, return to execute the function fitting of the multiple fourth alignment signals of the multiple measurement areas to obtain an ideal function.

10. The overlay metrology method of claim 8 or 9, wherein, The algorithm model of the machine learning is obtained by using a supervised learning algorithm or a neural network algorithm.

11. The overlay metrology method of claim 9, wherein, The fourth alignment signals of the multiple measurement areas are functionally fitted to obtain an ideal function, including: in each measurement area, the fourth alignment signals are decentered along the data direction of the measurement interval; After the decentering processing, the function type composed of the multiple fourth alignment signals is obtained; The multiple fourth alignment signals of the multiple measurement areas are fitted into an ideal function by using a fitting function of the same type as the function type.

12. The overlay metrology method of claim 11, wherein, In the process of fitting the multiple fourth alignment signals of the multiple measurement areas into an ideal function by using a fitting function of the same type as the function type, the order of the fitting function used this time is higher than the order of the fitting function used last time.

13. The overlay metrology method of claim 9, wherein, According to the multiple ideal signal values, the algorithm model of the machine learning is updated, including: taking the multiple ideal signal values as the output signal of machine learning, and taking the multiple first alignment signals as the input signal of machine learning, to update the algorithm model of the machine learning; According to the algorithm model, the multiple fourth alignment signals are updated, including: taking the multiple ideal signals as the input signal, and according to the updated algorithm model, the multiple fourth alignment signals are obtained.

14. The overlay metrology method of claim 8 or 9, wherein, According to the multiple fourth alignment signals, the position information of the measurement pattern at the center position in the measurement pattern is obtained, including: in each measurement area, according to the point graph composed of the multiple fourth alignment signals, the center point of the point graph is obtained; The measurement interval corresponding to the center point is obtained.

15. The overlay metrology method of claim 14, wherein, According to the position information, the overlay error between the first alignment pattern and the second alignment pattern of the previous layer is obtained, including: taking the negative value of the measurement interval corresponding to the center point as the overlay error.

16. A system for measuring overlay error, comprising: The method comprises the following steps: The structure providing module is configured to provide a previous layer structure and a current layer structure located on the previous layer structure, wherein the previous layer structure comprises multiple second alignment patterns, and the current layer structure comprises multiple measurement areas corresponding to the second alignment patterns; The measurement interval setting module is configured to set a measurement interval of a current layer pattern; The measurement pattern obtaining module is configured to obtain, in each measurement area of the current layer, multiple measurement patterns arranged in parallel at the measurement interval, including a first alignment pattern and other measurement patterns located on both sides of the first alignment pattern; a first alignment signal acquisition module, configured to acquire a first alignment signal of the measurement pattern and a second alignment pattern of a previous layer, with each of the measurement patterns as a measurement position; a position information acquisition module, configured to acquire position information of a measurement pattern at a center position in the measurement patterns according to a plurality of the first alignment signals; an overlay error acquisition module, configured to acquire an overlay error of the first alignment pattern and the second alignment pattern of the previous layer according to the position information.

17. An apparatus, comprising: comprising at least one memory and at least one processor, the memory storing one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the overlay error measurement method according to any one of claims 1-15.

18. A storage medium, characterized by The storage medium stores one or more computer instructions for implementing the overlay error measurement method according to any one of claims 1-15.

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