Aberration processing method, electronic device, and storage medium

Abstract

The disclosure provides an aberration processing method, an electronic device and a storage medium, which can be applied to the field of high-resolution imaging technology. The method comprises: calculating an influence parameter of I geometric aberration terms in the aberration information according to an experimental development pattern parameter corresponding to the aberration information of the photoetching system and a sampling number of sampling on the I geometric aberration terms, wherein the experimental development pattern parameter is obtained by performing an experiment on the photoetching system according to an experimental aberration coefficient, the experimental aberration coefficient is obtained by sampling on the I geometric aberration terms, the influence parameter is used to represent the influence degree of the geometric aberration term on the development pattern parameter of the photoetching system, and I is a positive integer greater than 1; determining a target geometric aberration term from the I geometric aberration terms according to the influence parameter of the I geometric aberration terms; and optimizing the aberration information according to the target geometric aberration term to obtain target aberration information.

Description

Technical Field

[0001] This disclosure relates to the field of high-resolution imaging, and more particularly to an aberration processing method, apparatus, electronic device, medium, and program product. Background Technology

[0002] Photolithography is a key process in the manufacturing of large-scale integrated circuits.

[0003] From an optical design perspective, zero aberration in projection lithography is an ideal design. However, in actual lithography systems, due to diffraction limitations and manufacturing errors, the propagation direction and phase of the ideal wavefront on the image plane change, resulting in aberrations between the actual and ideal wavefronts.

[0004] In the process of realizing the inventive concept disclosed herein, the inventors discovered that modeling and verifying aberrations is time-consuming. Summary of the Invention

[0005] In view of the above problems, this disclosure provides aberration methods, apparatus, electronic devices, media, and program products.

[0006] According to a first aspect of this disclosure, an aberration processing method is provided, comprising: calculating influence parameters of I geometric aberration terms based on experimental development pattern parameters corresponding to aberration information of a lithography system and the number of sampling operations for I geometric aberration terms in the aberration information, wherein the experimental development pattern parameters are obtained by experimenting with the lithography system based on experimental aberration coefficients, the experimental aberration coefficients are obtained by sampling the I geometric aberration terms, and the influence parameters are used to characterize the degree of influence of the geometric aberration terms on the development pattern parameters of the lithography system, where I is a positive integer greater than 1; determining a target geometric aberration term from the I geometric aberration terms based on the influence parameters of the I geometric aberration terms; and optimizing the aberration information based on the target geometric aberration term to obtain target aberration information.

[0007] According to embodiments of this disclosure, the aberration processing method further includes: using a Sopol sequence to sample I geometric aberration terms J times to obtain J sets of experimental aberration coefficients corresponding to each of the I geometric aberration terms, wherein the j-th set of experimental aberration coefficients in the J sets of experimental aberration coefficients includes I first experimental aberration coefficients and I second experimental aberration coefficients, where j is a positive integer less than or equal to J, and J is a positive integer greater than 1; constructing a first matrix based on I×J first experimental aberration coefficients, wherein the elements in the j-th row of the first matrix are I first experimental aberration coefficients, and the elements in the i-th column of the first matrix correspond to the i-th geometric aberration term in the I geometric aberration terms, where i is a positive integer less than or equal to J. A positive integer equal to I; construct a second matrix based on I×J second experimental aberration coefficients, where the elements in the j-th row of the second matrix are I second experimental aberration coefficients, and the elements in the i-th column of the second matrix correspond to the i-th geometric aberration term in I geometric aberration terms; by exchanging the elements in the i-th column of the first matrix and the i-th column of the second matrix, obtain the i-th exchange matrix; based on the elements in the J-th row of the first matrix, the J-th row of the second matrix, and the J-th row of the I exchange matrices, obtain the experimental aberration coefficients corresponding to (I+2)×J experiments, so as to perform (I+2)×J experiments on the lithography system and obtain (I+2)×J experimental development pattern parameters.

[0008] According to embodiments of this disclosure, the influence parameters of the I geometric aberration terms are calculated based on the experimental development pattern parameters corresponding to the aberration information of the lithography system and the number of samplings for the I geometric aberration terms in the aberration information. This includes calculating the parameter variance corresponding to the experimental development pattern parameters based on (I+2)×J experimental development pattern parameters; and calculating the influence parameters based on the first target experimental development pattern parameter in the (I+2)×J experimental development pattern parameters, the second target development pattern parameter in the (I+2)×J experimental development pattern parameters, the parameter variance, and the number of samplings. The first target experimental development pattern parameter corresponds to the first target element in the i-th exchange matrix, and the second target experimental development pattern parameter corresponds to the second target element in the first matrix. The row position of the first target element in the i-th exchange matrix is ​​the same as the row position of the second target element in the first matrix.

[0009] According to embodiments of this disclosure, each of the (I+2)×J experimental development pattern parameters includes a development pattern linewidth parameter and a development pattern position offset parameter. Based on the influence parameters of I geometric aberration terms, determining a target geometric aberration term from the I geometric aberration terms includes: determining a first target geometric aberration term corresponding to the development pattern linewidth parameter from the I geometric aberration terms based on the influence parameters corresponding to the development pattern linewidth parameter; determining a second target geometric aberration term corresponding to the development pattern position offset parameter from the I geometric aberration terms based on the influence parameters corresponding to the development pattern position offset parameter; and obtaining the target geometric aberration term based on the first and second target geometric aberration terms.

[0010] According to an embodiment of this disclosure, determining a first target geometric aberration term corresponding to the linewidth parameter of the developed pattern from I geometric aberration terms based on an influence parameter corresponding to the linewidth parameter of the developed pattern includes: sorting the I geometric aberration terms according to the influence parameter corresponding to the linewidth parameter of the developed pattern to obtain a first sorting result; and determining the first target geometric aberration term from the I geometric aberration terms based on the influence parameter corresponding to the linewidth parameter of the developed pattern, the first sorting result, and a first predetermined threshold.

[0011] According to an embodiment of this disclosure, there are I influence parameters corresponding to the linewidth parameter of the developing pattern. Determining a first target geometric aberration term from the I geometric aberration terms based on the influence parameters corresponding to the linewidth parameter of the developing pattern, a first sorting result, and a first predetermined threshold includes: calculating a first total parameter sum based on the I influence parameters corresponding to the linewidth parameter of the developing pattern; summing i influence parameters from the I influence parameters corresponding to the linewidth parameter of the developing pattern according to the first sorting result to obtain a first parameter sum; obtaining a first ratio based on the proportion of the first parameter to the total parameter sum; and determining the geometric aberration term corresponding to the i influence parameters from the I influence parameters corresponding to the linewidth parameter of the developing pattern as the first target geometric aberration term if the first ratio is greater than or equal to the first predetermined threshold.

[0012] According to an embodiment of this disclosure, determining a second target geometric aberration term corresponding to the developing pattern position offset parameter from I geometric aberration terms based on an influence parameter corresponding to the developing pattern position offset parameter includes: sorting the I geometric aberration terms according to the influence parameter corresponding to the developing pattern position offset parameter to obtain a second sorting result; and determining the second target geometric aberration term from the I geometric aberration terms based on the influence parameter corresponding to the developing pattern position offset parameter, the second sorting result, and a second predetermined threshold.

[0013] According to an embodiment of this disclosure, there are I influence parameters corresponding to the developing pattern position offset parameter. The determination of a second target geometric aberration term from the I geometric aberration terms based on the influence parameters corresponding to the developing pattern position offset parameter, a second sorting result, and a second predetermined threshold includes: calculating a second total parameter sum based on the I influence parameters corresponding to the developing pattern position offset parameter; accumulating i influence parameters from the I influence parameters corresponding to the developing pattern position offset parameter according to the second sorting result to obtain a second parameter sum; obtaining a second ratio based on the proportion of the second parameter to the total parameter sum; and determining the geometric aberration term corresponding to the i influence parameters from the I influence parameters corresponding to the developing pattern position offset parameter as the second target geometric aberration term if the second ratio is greater than or equal to the second predetermined threshold.

[0014] A second aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the methods described above.

[0015] A third aspect of this disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described above.

[0016] According to the aberration processing method, electronic device, and storage medium provided in this disclosure, sampling is performed using a photolithography system. The influence parameters of geometric aberration terms on the developed pattern parameters are calculated based on the number of samplings. Based on these influence parameters, target geometric aberration terms with a high degree of influence on the developed pattern can be identified. Furthermore, based on these target geometric aberration terms, the aberration information is optimized, reducing geometric aberration terms with weak influence on the developed pattern information and calculating only those with strong influence. This fully utilizes the computing power of the computer, improving the efficiency of aberration information processing and reducing the time spent on aberration modeling and verification. Therefore, since the amount of aberration information is reduced without sacrificing aberration accuracy, the required number of geometric aberrations can be reasonably selected according to different accuracy and computation time requirements, providing greater flexibility and offering reasonable guidance for other parameter influence analysis fields. Attached Figure Description

[0017] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0018] Figure 1 This diagram schematically illustrates an application scenario of the aberration processing method according to an embodiment of the present disclosure.

[0019] Figure 2 A flowchart illustrating an aberration processing method according to an embodiment of the present disclosure is shown schematically.

[0020] Figure 3 A schematic diagram of an imaging pattern under diode illumination of a lithography system according to an embodiment of the present disclosure is shown.

[0021] Figure 4 A schematic diagram of an imaging pattern under ring illumination conditions of a lithography system according to an embodiment of the present disclosure is shown.

[0022] Figure 5 This schematically illustrates the relationship between a predetermined threshold for target geometric aberration terms, development pattern parameter deviation, and the percentage of target geometric aberration terms in a photolithography system with diode illumination and vertical lines according to an embodiment of the present disclosure.

[0023] Figure 6 This schematically illustrates the relationship between a predetermined threshold for target geometric aberrations, development pattern parameter deviation, and the percentage of target geometric aberrations in a lithography system with ring illumination and vertical lines according to an embodiment of the present disclosure.

[0024] Figure 7 This schematically illustrates the relationship between a predetermined threshold for a target geometric aberration term, a development pattern parameter deviation, and the percentage of the number of target geometric aberration terms in a lithography system with ring illumination and horizontal lines according to an embodiment of the present disclosure.

[0025] Figure 8 A schematic block diagram of an aberration processing apparatus according to an embodiment of the present disclosure is shown; and

[0026] Figure 9 A block diagram schematically illustrates an electronic device suitable for implementing an aberration processing method according to an embodiment of the present disclosure. Detailed Implementation

[0027] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0029] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0030] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0031] In the technical solution of this invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0032] As the most crucial component in a projection lithography system, the projection lens plays a decisive role in the lithography imaging performance. In practical projection lithography systems, due to diffraction limitations of the lithography system and errors in processing and manufacturing, aberration-free projection lenses do not exist. Aberration information can be represented by orthogonal Zernike polynomials within the unit circle, with each term representing a type of geometric aberration.

[0033] Aberration information can affect the lithographic imaging quality of a lithography system; therefore, it is necessary to control and optimize aberration information.

[0034] Different geometric aberration terms have varying degrees of influence on lithography results. Furthermore, there are complex coupling effects among different geometric aberration terms, so a large number of terms usually need to be considered when conducting research on aberration optimization and control.

[0035] Based on this, the inventors discovered that modeling and verifying aberrations is time-consuming.

[0036] In view of this, embodiments of the present disclosure provide an aberration processing method, comprising: calculating influence parameters of I geometric aberration terms based on experimental development pattern parameters corresponding to aberration information of a lithography system and the number of sampling operations for I geometric aberration terms in the aberration information, wherein the experimental development pattern parameters are obtained by conducting experiments on the lithography system based on experimental aberration coefficients, the experimental aberration coefficients are obtained by sampling the I geometric aberration terms, and the influence parameters are used to characterize the degree of influence of the geometric aberration terms on the development pattern parameters of the lithography system, where I is a positive integer greater than 1; determining a target geometric aberration term from the I geometric aberration terms based on the influence parameters of the I geometric aberration terms; and optimizing the aberration information based on the target geometric aberration term to obtain target aberration information.

[0037] Figure 1 The diagram illustrates an application scenario of aberration processing according to an embodiment of the present disclosure.

[0038] like Figure 1 As shown, application scenario 100 according to this embodiment may include a lithography system 101 and a server 102. A network can be used as a medium to provide a communication link between the server 102 and the lithography system 101. The network may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0039] Server 102 can collect aberration information and experimental development patterns from lithography system 101 via the network.

[0040] Server 102 can be a server that provides various services, such as a backend management server (for example only). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0041] It should be noted that the aberration processing method provided in this embodiment can generally be executed by server 102. Correspondingly, the aberration processing apparatus provided in this embodiment can generally be located in server 102. The aberration processing method provided in this embodiment can also be executed by a server or server cluster that is different from server 102 and capable of communicating with lithography system 101 and / or server 102. Correspondingly, the aberration processing apparatus provided in this embodiment can also be located in a server or server cluster that is different from server 102 and capable of communicating with lithography system 101 and / or server 102.

[0042] It should be understood that Figure 1The number of servers 101 and lithography systems 102 shown is merely illustrative. Depending on implementation requirements, any number of servers 101 and lithography systems 102 can be used.

[0043] The following will be based on Figure 1 The described scene, through Figures 2-7 The aberration processing method of the disclosed embodiments will be described in detail.

[0044] Figure 2 A flowchart illustrating an aberration processing method according to an embodiment of the present disclosure is shown schematically.

[0045] like Figure 2 As shown, this embodiment 200 includes operations S210 to S230.

[0046] In operation S210, the influence parameters of the I geometric aberration terms are calculated based on the experimental development pattern parameters corresponding to the aberration information of the lithography system and the number of samplings for the I geometric aberration terms in the aberration information.

[0047] In operation S220, the target geometric aberration term is determined from the I geometric aberration terms based on the influence parameters of the I geometric aberration terms.

[0048] In operation S230, the aberration information is optimized based on the target geometric aberration term to obtain the target aberration information.

[0049] According to embodiments of this disclosure, aberration information can be represented by orthogonal Zernike polynomials within a unit circle, where each term represents a type of geometric aberration, such as spherical aberration, coma, astigmatism, etc. The aberration information may include I geometric aberration terms corresponding to I coefficients, where I is a positive integer greater than 1.

[0050] According to embodiments of this disclosure, the experimental development pattern parameters are obtained by experimenting with the photolithography system based on experimental aberration coefficients. The experimental development pattern parameters can be parameters of the development pattern obtained by experimenting with the photolithography system on an object. For example, the object can perform experiments using the photolithography system according to experimental aberration coefficients to obtain development pattern parameters corresponding to the experimental aberration coefficients.

[0051] According to embodiments of this disclosure, experimental aberration coefficients are obtained by sampling I geometric aberration terms, where I is a positive integer greater than 1. For example, sampling I geometric aberration terms can generate I experimental aberration coefficients corresponding to the I geometric aberration terms. Thus, by sampling the experimental aberration coefficients J times, J experimental aberration coefficients corresponding to the i-th geometric aberration term among the I geometric aberration terms can be obtained. Based on this, the more times the experimental aberration coefficients are sampled, the more experimental aberration coefficients are obtained. With more experimental aberration coefficients, the calculated influence parameters are more accurate.

[0052] According to embodiments of this disclosure, the influence parameter is used to characterize the degree of influence of geometric aberration terms on the development pattern parameters of the lithography system. For example, the larger the value of the influence parameter, the greater the influence of the geometric aberration term corresponding to the influence parameter on the development pattern parameters of the lithography system; the smaller the value of the influence parameter, the smaller the influence of the geometric aberration term corresponding to the influence parameter on the development pattern parameters of the lithography system.

[0053] According to embodiments of this disclosure, the target geometric aberration term can be the geometric aberration term that has a high degree of influence on the development pattern parameters of the photolithography system among I geometric aberration terms. For example, the I geometric aberration terms can be sorted according to the influence parameter to obtain a sorted set of I geometric aberration terms. Then, according to a predetermined position threshold, the target geometric aberration term is determined from the sorted set of I geometric aberration terms. According to embodiments of this disclosure, optimizing the aberration information can include: deleting geometric aberration terms that do not correspond to the target coefficient from the I geometric aberration terms included in the aberration information, thereby optimizing the aberration information.

[0054] According to the aberration processing method, electronic device, and storage medium provided in this disclosure, sampling is performed using a photolithography system. The influence parameters of geometric aberration terms on the developed pattern parameters are calculated based on the number of samplings. Based on these influence parameters, target geometric aberration terms with a high degree of influence on the developed pattern can be identified. Furthermore, based on these target geometric aberration terms, the aberration information is optimized, reducing geometric aberration terms with weak influence on the developed pattern information and calculating only those with strong influence. This fully utilizes the computing power of the computer, improving the efficiency of aberration information processing and reducing the time spent on aberration modeling and verification. Therefore, since the amount of aberration information is reduced without sacrificing aberration accuracy, the required number of geometric aberrations can be reasonably selected according to different accuracy and computation time requirements, providing greater flexibility and offering reasonable guidance for other parameter influence analysis fields.

[0055] According to embodiments of this disclosure, the aberration processing method further includes: sampling I geometric aberration terms J times using a Sopol sequence to obtain J sets of experimental aberration coefficients corresponding to each of the I geometric aberration terms; constructing a first matrix based on I×J first experimental aberration coefficients; constructing a second matrix based on I×J second experimental aberration coefficients; obtaining an i-th exchange matrix by exchanging the elements of the i-th column of the first matrix and the i-th column of the second matrix; obtaining experimental aberration coefficients corresponding to (I+2)×J experiments based on the elements of the J rows in the first matrix, the J rows in the second matrix, and the J rows in the I exchange matrices, so as to perform (I+2)×J experiments on the lithography system to obtain (I+2)×J experimental development pattern parameters.

[0056] According to embodiments of this disclosure, the Sopol sequence can be used to sample I geometric terms to randomly generate experimental aberration coefficients corresponding to the I geometric aberration terms. Sampling the I geometric aberrations once yields a set of experimental aberration coefficients. Accordingly, sampling the I geometric aberration terms J times yields J sets of experimental aberration coefficients. The j-th set of experimental aberration coefficients in the J sets includes I first experimental aberration coefficients and I second experimental aberration coefficients, where j is a positive integer less than or equal to J, and J is a positive integer greater than 1.

[0057] According to an embodiment of this disclosure, the elements in the j-th row of the first matrix are I first experimental aberration coefficients, and the elements in the i-th column of the first matrix correspond to the i-th geometric aberration term among the I geometric aberration terms, where i is a positive integer less than or equal to I. Taking I=3 and J=3 as an example, the generated first matrix can be represented as matrix A.

[0058]

[0059] Among them, Z 11 Z 21 Z 31 Each of these can be the experimental aberration coefficient of the first geometric aberration term out of I geometric aberration terms. 12 Z 22 Z 32 Both Z can be the experimental aberration coefficient of the second geometric aberration term out of I geometric aberration terms. 13 Z 23 Z 33 All of them can be the experimental aberration coefficient of the third geometric aberration term out of I geometric aberration terms. 11 Z 12 and Z 13 Z can be the first experimental aberration coefficient obtained by sampling the first, second, and third geometric aberration terms. 21 Z 22and Z 23 Z can be the first experimental aberration coefficient obtained by sampling the first, second, and third geometric aberration terms a second time. 31 Z 32 and Z 33 It can be the first experimental aberration coefficient obtained by sampling the first, second, and third geometric aberration terms a third time.

[0060] According to an embodiment of this disclosure, the elements in the j-th row of the second matrix are I second experimental aberration coefficients, and the elements in the i-th column of the second matrix correspond to the i-th geometric aberration term among the I geometric aberration terms. Taking I=3 and J=3 as an example, the generated second matrix can be represented as matrix B.

[0061]

[0062] Among them, Z 14 Z 24 Z 34 Each of these can be the experimental aberration coefficient of the first geometric aberration term out of I geometric aberration terms. 15 Z 25 Z 35 Both Z can be the experimental aberration coefficient of the second geometric aberration term out of I geometric aberration terms. 16 Z 26 Z 36 All of them can be the experimental aberration coefficient of the third geometric aberration term out of I geometric aberration terms. 14 Z 15 and Z 16 Z can be the first experimental aberration coefficient obtained by sampling the first, second, and third geometric aberration terms. 24 Z 25 and Z 26 Z can be the first experimental aberration coefficient obtained by sampling the first, second, and third geometric aberration terms a second time. 34 Z 35 and Z 36 It can be the first experimental aberration coefficient obtained by sampling the first, second, and third geometric aberration terms a third time.

[0063] According to embodiments of this disclosure, the number of commutation matrices corresponds to the number of geometric aberration terms. Taking I=3 and J=3 as an example, the generated commutation matrix can be represented as AB. 1 AB 2 and AB 3 The experimental aberration coefficients can be elements of each row in the first matrix, the second matrix, and the exchange matrix.

[0064]

[0065] For example, when I=3 and J=3, the first matrix A can be: The second matrix B can be...

[0066] In the first matrix A, the first row contains the first aberration coefficients (1, 2, 3) obtained by the first sampling of the three geometric aberration terms; the first column contains the first aberration coefficients (1, 4, 7) obtained by the third sampling of the first geometric aberration term. In the second matrix B, the first row contains the second aberration coefficients (7, 7, 4) obtained by the first sampling of the three geometric aberration terms; the first column contains the second aberration coefficients (7, 8, 9) obtained by the third sampling of the first geometric aberration term.

[0067] Replacing the elements in columns 1, 2, and 3 of the second matrix B with the elements in columns 1, 2, and 3 of the first matrix A in sequence yields three new matrices AB. 1 AB 2 and AB 3 That is, the commutative matrix.

[0068]

[0069] Each row element in the three commutation matrices is also used as a set of experimental aberration coefficients. Taking matrices A and B as examples, a total of 15 sets of experimental aberration coefficients for the three geometric aberration terms can be obtained for experiments on the lithography system. The experimental aberration coefficients are (1, 2, 3), (4, 5, 6), (7, 8, 9), (7, 1, 4), (8, 2, 5), (9, 3, 6), (7, 2, 3), (8, 5, 6), (9, 8, 9), (1, 1, 3), (4, 2, 6), (7, 3, 9), (1, 2, 4), (4, 5, 5), and (7, 8, 6).

[0070] According to embodiments of this disclosure, each set of experimental aberration coefficients corresponds to one experiment of the photolithography system, and each experiment can yield a corresponding experimental development pattern parameter.

[0071] According to embodiments of this disclosure, the geometric aberration term is sampled multiple times using a Sopol sequence. The sampled data is used to construct two matrices with the same number of rows and columns. Corresponding column elements of the two matrices are then swapped to obtain a swapped matrix. Multiple experiments are performed based on the experimental aberration coefficients corresponding to the column elements of all matrices, yielding multiple experimental development parameters corresponding to these experiments. By using the Sopol sequence and the swapped matrix, as many experimental aberration coefficients as possible corresponding to the experimental schemes of the lithography system can be obtained, thus maximizing the collection of experimental development parameters. This improves the accuracy of the calculated influence parameters.

[0072] According to embodiments of this disclosure, the influence parameters of the I geometric aberration terms are calculated based on the experimental development pattern parameters corresponding to the aberration information of the lithography system and the number of samplings for the I geometric aberration terms in the aberration information. This includes: calculating the parameter variance corresponding to the experimental development pattern parameters based on (I+2)×J experimental development pattern parameters; and calculating the influence parameters based on the first target experimental development pattern parameter in the (I+2)×J experimental development pattern parameters, the second target development pattern parameter in the (I+2)×J experimental development pattern parameters, the parameter variance, and the number of samplings.

[0073] According to embodiments of this disclosure, the first target experimental development pattern parameters correspond to the first target element in the i-th exchange matrix. The second target experimental development pattern parameters correspond to the second target element in the first matrix. The row position of the first target element in the i-th exchange matrix is ​​the same as the row position of the second target element in the first matrix.

[0074] According to embodiments of this disclosure, the influencing parameters may include a first influencing parameter on the linewidth parameter of the experimental developed pattern in the experimental developed pattern parameters and a second influencing parameter on the position offset parameter of the experimental developed pattern in the experimental developed pattern parameters.

[0075] According to an embodiment of this disclosure, the first influence parameter can be calculated using formula (1).

[0076]

[0077] Among them, S_CD SOBOL_i It can characterize the geometric aberration Z of the i-th term. i The parameters affecting the linewidth of the experimental developed pattern are E (expectation value), Var (variance), and z (z). ～i It can characterize the geometric aberration Z excluding the i-th term. i The set of all geometric aberration terms except CD. ABij CD can represent the linewidth parameter of the experimental developed pattern obtained from the lithography system experiment corresponding to the j-th row of the i-th exchange matrix. AjIt can represent the linewidth parameter of the experimental development pattern obtained from the lithography system experiment corresponding to the j-th row of the first matrix.

[0078] According to an embodiment of this disclosure, the first influence parameter of all geometric aberration terms on the linewidth parameter of the experimental developed pattern in the experimental developed pattern parameters can be obtained according to formula (1).

[0079] According to an embodiment of this disclosure, the second influence parameter can be calculated according to formula (2).

[0080]

[0081] Where S_PS SOBOL_i The parameter that can characterize the influence of the i-th geometric aberration Zi on the positional offset parameter of the experimental developed pattern, E can represent the expectation, Var can represent the variance, and z ～i It can characterize the geometric aberration Z excluding the i-th term. i The set of all geometric aberration terms except for PS. ABij PS can represent the position offset parameter of the experimental developed pattern obtained from the lithography system experiment corresponding to the j-th row of the i-th exchange matrix. Aj It can represent the position offset parameter of the experimental development pattern obtained from the photolithography system experiment corresponding to the j-th row of the first matrix.

[0082] According to an embodiment of this disclosure, the second influence parameter of all geometric aberration terms on the position offset parameter of the experimental development pattern in the experimental development pattern parameters can be obtained according to formula (2).

[0083] According to embodiments of this disclosure, accurate influence parameters can be calculated based on the first target experimental development pattern parameters, the second target experimental development pattern parameters, the parameter variance, and the number of samplings.

[0084] According to embodiments of this disclosure, determining a target geometric aberration term from the I geometric aberration terms based on the influence parameters of the I geometric aberration terms includes: determining a first target geometric aberration term corresponding to the linewidth parameter of the developed pattern from the I geometric aberration terms based on the influence parameters corresponding to the linewidth parameter of the developed pattern; determining a second target geometric aberration term corresponding to the position offset parameter of the developed pattern from the I geometric aberration terms based on the influence parameters corresponding to the position offset parameter of the developed pattern; and obtaining the target geometric aberration term based on the first target geometric aberration term and the second target geometric aberration term.

[0085] According to embodiments of this disclosure, each of the (I+2)×J experimental development pattern parameters includes a development pattern linewidth parameter and a development pattern position offset parameter, and the development pattern can be determined based on the development pattern linewidth parameter and the development pattern position offset parameter.

[0086] According to embodiments of this disclosure, the experimental pattern linewidth parameter (ritual dimension, CD) can be used to characterize the linewidth of the developed pattern obtained through experimental imaging.

[0087] According to embodiments of this disclosure, the experimental pattern shift parameter (PS) can be used to characterize the positional shift of the developed pattern in the experimental imaging.

[0088] According to embodiments of this disclosure, the first target geometric aberration term can be a geometric aberration term with a higher influence parameter corresponding to the linewidth parameter of the developed pattern. The second target coefficient can be a geometric aberration term with a higher influence parameter corresponding to the position offset parameter of the developed pattern.

[0089] According to an embodiment of this disclosure, determining a first target geometric aberration term corresponding to the linewidth parameter of the developed pattern from I geometric aberration terms based on an influence parameter corresponding to the linewidth parameter of the developed pattern includes: sorting the I geometric aberration terms according to the influence parameter corresponding to the linewidth parameter of the developed pattern to obtain a first sorting result; and determining the first target geometric aberration term from the I geometric aberration terms based on the influence parameter corresponding to the linewidth parameter of the developed pattern, the first sorting result, and a first predetermined threshold.

[0090] According to embodiments of this disclosure, the first sorting result can characterize the result of sorting I geometric aberration terms from largest to smallest based on the influence parameter corresponding to the linewidth parameter of the developing pattern. A first target geometric aberration term can be determined from the I geometric aberration terms arranged from largest to smallest based on the influence parameter corresponding to the linewidth parameter of the developing pattern and a first predetermined threshold. The first predetermined threshold can be used to characterize a threshold that is manually preset according to actual needs, and this disclosure does not limit its use.

[0091] According to embodiments of this disclosure, when performing aberration modeling, the more geometric aberrations considered, the higher the model accuracy; however, the more geometric aberrations selected, the longer the runtime. Therefore, based on actual needs, a first target geometric aberration term is determined, reducing the number of geometric aberration terms, thereby reducing computation time without sacrificing aberration accuracy.

[0092] According to an embodiment of this disclosure, there are I influence parameters corresponding to the linewidth parameter of the developing pattern. Determining a first target geometric aberration term from the I geometric aberration terms based on the influence parameters corresponding to the linewidth parameter of the developing pattern, a first sorting result, and a first predetermined threshold includes: calculating a first total parameter sum based on the I influence parameters corresponding to the linewidth parameter of the developing pattern; summing i influence parameters from the I influence parameters corresponding to the linewidth parameter of the developing pattern according to the first sorting result to obtain a first parameter sum; obtaining a first ratio based on the proportion of the first parameter to the total parameter sum; and determining the geometric aberration term corresponding to the i influence parameters from the I influence parameters corresponding to the linewidth parameter of the developing pattern as the first target geometric aberration term if the first ratio is greater than or equal to the first predetermined threshold.

[0093] According to embodiments of this disclosure, the geometric aberration term of the first target can be determined according to the following formula (3).

[0094]

[0095] Where n_SOBOL_cd is the number of geometric aberration terms corresponding to the influence parameters of the selected developing pattern linewidth parameter, that is, the number of the i accumulated influence parameters mentioned above. S_CD SOBOL_i This can represent the influencing parameters corresponding to the developed pattern linewidth parameter. D is the total number of influencing parameters corresponding to the developed pattern linewidth parameter. T is the first predetermined threshold.

[0096] According to embodiments of this disclosure, the accuracy of the determined first geometric aberration term is improved by determining the first target geometric aberration term based on the first parameter of the i-th influencing parameter among the I influencing parameters corresponding to the developing pattern linewidth parameter and the proportion of the first total parameter of the I influencing parameters corresponding to the developing pattern linewidth parameter.

[0097] According to an embodiment of this disclosure, determining a second target geometric aberration term corresponding to the developing pattern position offset parameter from I geometric aberration terms based on an influence parameter corresponding to the developing pattern position offset parameter includes: sorting the I geometric aberration terms according to the influence parameter corresponding to the developing pattern position offset parameter to obtain a second sorting result; and determining the second target geometric aberration term from the I geometric aberration terms based on the influence parameter corresponding to the developing pattern position offset parameter, the second sorting result, and a second predetermined threshold.

[0098] According to embodiments of this disclosure, the second sorting result can characterize the result of sorting I geometric aberration terms from largest to smallest based on the influence parameter corresponding to the developing pattern position offset parameter. A second target geometric aberration term can be determined from the I geometric aberration terms arranged from largest to smallest according to a second predetermined threshold. The second predetermined threshold can be used to characterize a threshold that is manually preset according to actual needs, and this disclosure does not limit its use.

[0099] According to embodiments of this disclosure, when performing aberration modeling, the more geometric aberrations considered, the higher the model accuracy; however, the more geometric aberrations selected, the longer the runtime. Therefore, based on actual needs, a second target geometric aberration term is determined, reducing the number of geometric aberration terms, thereby reducing computation time without sacrificing aberration accuracy.

[0100] According to an embodiment of this disclosure, there are I influence parameters corresponding to the developing pattern position offset parameter. Determining a second target geometric aberration term from the I geometric aberration terms based on a second sorting result and a second predetermined threshold includes: calculating a second total parameter sum based on the I influence parameters corresponding to the developing pattern position offset parameter; accumulating i influence parameters from the I influence parameters corresponding to the developing pattern position offset parameter according to the second sorting result to obtain a second parameter sum; obtaining a second ratio based on the proportion of the second parameter to the total parameter sum; and determining the geometric aberration term corresponding to the i influence parameters from the I influence parameters corresponding to the developing pattern position offset parameter as the second target geometric aberration term if the second ratio is greater than or equal to the second predetermined threshold.

[0101] According to embodiments of this disclosure, the second target geometric aberration term can be determined according to the following formula (4).

[0102]

[0103] Where n_SOBOL_cd is the number of geometric aberration terms corresponding to the influence parameters of the selected developing pattern linewidth parameter, that is, the number of the i accumulated influence parameters mentioned above. S_PS SOBOL_i These are the influencing parameters corresponding to the developing pattern position offset parameters. D is the total number of influencing parameters corresponding to the developing pattern position offset parameters. T is the second predetermined threshold.

[0104] According to embodiments of this disclosure, the accuracy of the determined second geometric aberration term is improved by determining the second target geometric aberration term based on the second parameter of the i-th influence parameter among the I influence parameters corresponding to the developing pattern position offset parameter and the proportion of the second total parameter of the I influence parameters corresponding to the developing pattern position offset parameter.

[0105] According to embodiments of this disclosure, the target geometric aberration term can be represented as the union of the first target geometric aberration term and the second target geometric aberration term. The target geometric aberration term can be obtained according to the following formula (5):

[0106] Z SOBOL =Z_CD SOBOL ∪Z_PS SOBOL (5)

[0107] Among them, Z SOBOL Z_CD can represent all determined target geometric aberration terms. SOBOL This can represent the geometric aberration term of the first target. Z_PS SOBOL It can represent the second objective geometric aberration term. ∪ can represent the union of two sets.

[0108] To better understand the above content, this disclosure combines... Figures 3-7 The following embodiments are also provided to illustrate the above aberration processing method.

[0109] According to embodiments of this disclosure, the aberration processing method is applied to various development patterns under different illumination conditions in an extreme ultraviolet (EUV) lithography system, considering cases at 13 different field-of-view positions. For optical surface types with the same linewidth, the wavefront aberration of the EUV lithography system is approximately 10 times that of the deep ultraviolet (DUV) lithography system. Experimental conditions are shown in Table 1.

[0110] Table 1

[0111]

[0112] Figure 3 The diagram illustrates an image pattern of a photolithography system under diode illumination conditions according to an embodiment of the present disclosure.

[0113] Figure 4 The diagram illustrates an image pattern of a lithography system under ring illumination conditions according to an embodiment of the present disclosure.

[0114] According to embodiments of this disclosure, the first 37 geometric aberration terms are considered, with aberration variations ranging from -20mλ to 20mλ. Experimental aberration coefficients are confirmed using the Sopol sequence to identify target geometric aberration terms affecting pattern imaging.

[0115] Referring to step S210 in embodiment 200 above, the sampling number for the geometric aberration term is 9. Based on the developing pattern parameters and the sampling number, the influence parameters of the geometric aberration term on the developing pattern linewidth parameters and the developing pattern position offset parameters are calculated.

[0116] Referring to step S220 in embodiment 200 above, the calculated influence parameters are sorted. According to embodiments of this disclosure, in order to reflect the necessity of optimizing geometric aberration information to obtain the target aberration, predetermined thresholds of 70%, 80%, and 90% are preset. These preset predetermined thresholds correspond to the first and second predetermined thresholds mentioned above.

[0117] According to embodiments of this disclosure, the average aberrations selected for each lighting condition are shown in Table 2.

[0118] Table 2

[0119]

[0120] According to embodiments of this disclosure, the union of the first target geometric aberration term and the second target geometric aberration term is taken as the target geometric aberration term.

[0121] According to embodiments of this disclosure, random experiments can be conducted using experimental aberration coefficients for 37 geometric aberration terms, and development pattern parameters can be collected. These development pattern parameters can then be used as development pattern parameters considering all geometric aberration terms. Alternatively, the values ​​corresponding to the target geometric aberration terms in the above experiments can be kept unchanged, while the values ​​of unselected non-target geometric aberration terms can be set to 0. The experiments can then be conducted again, and development pattern parameters can be collected again. These development pattern parameters can then be used as development pattern parameters considering only the target geometric aberration terms. The deviation between the development pattern parameters considering all geometric aberration terms and considering only the target geometric aberration terms is then considered in relation to the light source and pattern under study.

[0122] Figure 5 The diagram illustrates the relationship between a predetermined threshold for a target geometric aberration, a development pattern parameter deviation, and the percentage of the number of target geometric aberrations in a photolithography system with diode illumination and vertical lines according to an embodiment of the present disclosure.

[0123] like Figure 5 As shown, the horizontal axis represents the proportion of the influence parameters of the target geometric aberration term to the influence parameters of I geometric aberration terms, the vertical axis on the right represents the proportion of the number of target geometric aberration terms, and the vertical axis on the left represents the deviation between the development pattern parameters considering I geometric aberration terms and the development pattern parameters considering only the target geometric aberration term.

[0124] According to embodiments of this disclosure, the selected CD aberration average proportion refers to the proportion of the average number of the first target geometric aberration items to the total number of geometric aberration items in the aberration information. The selected PS aberration average proportion refers to the proportion of the average number of the second target geometric aberration items to the total number of geometric aberration items in the aberration information. The selected aberration average proportion refers to the proportion of the average number of the union of the first and second target geometric aberration items to the total number of geometric aberration items in the aberration information.

[0125] Figure 6 The diagram illustrates the relationship between a predetermined threshold for a target geometric aberration term, a development pattern parameter deviation, and the percentage of the number of target geometric aberration terms in a lithography system with ring illumination and vertical lines according to an embodiment of the present disclosure.

[0126] like Figure 6 As shown, the horizontal axis represents the proportion of the influence parameters of the target geometric aberration term to the influence parameters of I geometric aberration terms, the vertical axis on the right represents the proportion of the number of target geometric aberration terms, and the vertical axis on the left represents the deviation between the development pattern parameters considering I geometric aberration terms and the development pattern parameters considering only the target geometric aberration term.

[0127] Figure 7 The diagram illustrates the relationship between a predetermined threshold for a target geometric aberration term, a development pattern parameter deviation, and the percentage of the number of target geometric aberration terms in a lithography system under ring illumination-horizontal line conditions according to an embodiment of the present disclosure.

[0128] like Figure 7 As shown, the horizontal axis represents the proportion of the influence parameters of the predetermined threshold target geometric aberration term to the influence parameters of the I geometric aberration terms, the vertical axis on the right represents the proportion of the number of selected target geometric aberration terms, and the vertical axis on the left represents the deviation between the development pattern parameters considering all I geometric aberration terms and the development pattern parameters considering only the target geometric aberration term.

[0129] According to embodiments of this disclosure, based on the comparison of the above experimental results, the Sopol sequence method achieves high accuracy while significantly reducing the number of target geometric aberration terms. Specifically, by selecting no more than 35% of the geometric aberration terms, a 90% target geometric aberration term ratio can be achieved, with an average CD bias of no more than 1.3% and an average PS bias of no more than 1%.

[0130] Based on the above aberration processing method, this disclosure also provides an aberration processing apparatus. The following will be combined with... Figure 8 The device is described in detail.

[0131] Figure 8 A schematic block diagram of an aberration processing apparatus according to an embodiment of the present disclosure is shown.

[0132] like Figure 8 As shown, the aberration processing apparatus 800 of this embodiment includes a calculation module 810, a determination module 820, and an optimization module 830.

[0133] The calculation module 810 is used to calculate the influence parameters of the I geometric aberration terms based on the experimental development pattern parameters corresponding to the aberration information of the lithography system and the number of samplings for the I geometric aberration terms in the aberration information. In one embodiment, the calculation module 810 can be used to perform the operation S210 described above, which will not be repeated here.

[0134] The determining module 820 is used to determine the target geometric aberration term from the I geometric aberration terms based on the influence parameters of the I geometric aberration terms. In one embodiment, the determining module 820 can be used to perform the operation S220 described above, which will not be repeated here.

[0135] The optimization module 830 is used to optimize the aberration information based on the target geometric aberration term to obtain the target aberration information. In one embodiment, the optimization module 830 can be used to perform the operation S230 described above, which will not be repeated here.

[0136] According to embodiments of this disclosure, the aberration processing apparatus further includes a sampling module, a first construction module, a second construction module, an exchange module, and an acquisition module.

[0137] The sampling module is used to perform J samplings on each of the I geometric aberration terms using the Sopol sequence, to obtain J sets of experimental aberration coefficients corresponding to each of the I geometric aberration terms.

[0138] The first construction module is used to construct the first matrix based on I×J first experimental aberration coefficients.

[0139] The second construction module is used to construct the second matrix based on I×J second experimental aberration coefficients.

[0140] The swapping module is used to obtain the i-th swapped matrix by swapping the elements of the i-th column of the first matrix and the elements of the i-th column of the second matrix.

[0141] The acquisition module is used to obtain the experimental aberration coefficients corresponding to (I+2)×J experiments based on the elements of the J rows in the first matrix, the elements of the J rows in the second matrix, and the elements of the J rows in the I exchange matrices, so as to perform (I+2)×J experiments on the lithography system and obtain (I+2)×J experimental development pattern parameters.

[0142] According to embodiments of this disclosure, the computing module 810 includes a first computing submodule and a second computing submodule.

[0143] The first calculation submodule is used to calculate the parameter variance corresponding to the experimental development pattern parameters based on (I+2)×J experimental development pattern parameters.

[0144] The second calculation submodule is used to calculate the influence parameters based on the first target experimental development pattern parameter, the second target development pattern parameter, the parameter variance, and the number of samplings from (I+2)×J experimental development pattern parameters.

[0145] According to embodiments of this disclosure, the determining module 820 includes a first determining submodule, a second determining submodule, and an obtaining submodule.

[0146] The first determining submodule is used to determine the first target geometric aberration term corresponding to the linewidth parameter of the developing pattern from I geometric aberration terms based on the influence parameters corresponding to the linewidth parameter of the developing pattern.

[0147] The second determining submodule is used to determine the second target geometric aberration term corresponding to the position offset parameter of the developing pattern from I geometric aberration terms based on the influence parameter corresponding to the position offset parameter of the developing pattern.

[0148] The submodule is used to obtain the target geometric aberration term based on the first target geometric phase difference term and the second target geometric aberration term.

[0149] According to embodiments of this disclosure, the first determining submodule includes a sorting unit and a determining unit.

[0150] The sorting unit is used to sort the I geometric aberration items according to the influence parameters corresponding to the line width parameters of the developing pattern, and obtain the first sorting result;

[0151] The determining unit is used to determine a first target geometric aberration term from I geometric aberration terms based on the influence parameter corresponding to the linewidth parameter of the developing pattern, the first sorting result, and the first predetermined threshold.

[0152] According to embodiments of this disclosure, the determining unit includes a calculation subunit, a first obtaining subunit, a second obtaining subunit, and a determining subunit.

[0153] The calculation subunit is used to calculate the first total parameter sum based on the I influence parameters corresponding to the developing pattern linewidth parameter.

[0154] The first obtaining subunit is used to accumulate i of the i influence parameters among the I influence parameters corresponding to the developing pattern linewidth parameter according to the first sorting result, to obtain the first parameter sum.

[0155] The second obtaining subunit is used to obtain a first ratio based on the proportion of the first parameter to the total parameters.

[0156] A sub-unit is defined as follows: when the first parameter is greater than or equal to a first predetermined threshold, the geometric aberration term corresponding to the i-th of the I-influence parameters corresponding to the developing pattern linewidth parameter is determined as the first target geometric aberration term.

[0157] According to embodiments of this disclosure, the second determining submodule includes a sorting unit and a determining unit.

[0158] The sorting unit is used to sort the I geometric aberration terms according to the influence parameters corresponding to the position offset parameters of the developing pattern, and obtain the second sorting result.

[0159] The determining unit is used to determine the second target geometric aberration term from I geometric aberration terms based on the influence parameter corresponding to the position offset parameter of the developing pattern, the second sorting result, and the second predetermined threshold.

[0160] According to embodiments of this disclosure, the determining unit includes a calculation subunit, a first obtaining subunit, a determining subunit, and a second obtaining subunit.

[0161] The calculation subunit is used to calculate the second total parameter sum based on the I influence parameters corresponding to the developing pattern position offset parameter.

[0162] The first obtaining subunit is used to accumulate i of the i influence parameters among the I influence parameters corresponding to the developing pattern position offset parameter according to the second sorting result, so as to obtain the second parameter sum.

[0163] The second obtaining subunit is used to obtain the second ratio based on the proportion of the second parameter to the total number of parameters.

[0164] A sub-unit is defined as follows: when the second ratio is greater than or equal to the second predetermined threshold, the geometric aberration term corresponding to the i-th of the I-influence parameters corresponding to the developing pattern position offset parameter is determined as the second target geometric aberration term.

[0165] According to embodiments of this disclosure, any plurality of modules among the calculation module 810, determination module 820, and optimization module 830 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least a portion of the functionality of one or more of these modules may be combined with at least a portion of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the calculation module 810, determination module 820, and optimization module 830 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the calculation module 810, determination module 820, and optimization module 830 may be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0166] Figure 9 A block diagram schematically illustrates an electronic device suitable for implementing an aberration processing method according to an embodiment of the present disclosure.

[0167] like Figure 9 As shown, an electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage portion 908 into a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0168] RAM 903 stores various programs and data required for the operation of electronic device 900. Processor 901, ROM 902, and RAM 903 are interconnected via bus 904. Processor 901 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 902 and / or RAM 903. It should be noted that the programs may also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 may also perform various operations of aberration processing according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0169] According to embodiments of this disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to a bus 904. The electronic device 900 may also include one or more of the following components connected to the input / output (I / O) interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the input / output (I / O) interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 910 as needed so that computer programs read from it can be installed into the storage section 908 as needed.

[0170] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0171] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 902 and / or RAM 903 and / or one or more memories other than ROM 902 and RAM 903 described above.

[0172] When the computer program is executed by the processor 901, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0173] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 909, and / or installed from a removable medium 911. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0174] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0175] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0176] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0177] It should be noted that, unless it is explicitly stated that there is a sequential order of execution between different operations, or that there is a sequential order of execution between different operations in terms of technical implementation, the execution order between multiple operations may not be significant, and multiple operations may be executed simultaneously.

[0178] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0179] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An aberration processing method, comprising: Based on the experimental development pattern parameters corresponding to the aberration information of the lithography system and the number of samplings for the I geometric aberration terms in the aberration information, the influence parameters of the I geometric aberration terms are calculated. The experimental development pattern parameters are obtained by conducting experiments on the lithography system based on experimental aberration coefficients. The experimental aberration coefficients are obtained by sampling the I geometric aberration terms. The influence parameters are used to characterize the degree of influence of the geometric aberration terms on the experimental development pattern parameters of the lithography system. I is a positive integer greater than 1. Based on the influence parameters of the I geometric aberration terms, the target geometric aberration term is determined from the I geometric aberration terms; Based on the target geometric aberration term, the aberration information is optimized to obtain the target aberration information.

2. The method according to claim 1, further comprising: By using the Sopol sequence, the I geometric aberration terms are sampled J times to obtain J sets of experimental aberration coefficients corresponding to each of the I geometric aberration terms. The j-th set of experimental aberration coefficients in the J sets of experimental aberration coefficients includes I first experimental aberration coefficients and I second experimental aberration coefficients, where j is a positive integer less than or equal to J, and J is a positive integer greater than 1. Based on the I×J first experimental aberration coefficients, a first matrix is ​​constructed, wherein the elements in the j-th row of the first matrix are the I first experimental aberration coefficients, and the elements in the i-th column of the first matrix correspond to the i-th geometric aberration term among the I geometric aberration terms, where i is a positive integer less than or equal to I. Based on the I×J second experimental aberration coefficients, a second matrix is ​​constructed, wherein the elements in the j-th row of the second matrix are the I second experimental aberration coefficients, and the elements in the i-th column of the second matrix correspond to the i-th geometric aberration term among the I geometric aberration terms; By swapping the elements of the i-th column of the first matrix and the elements of the i-th column of the second matrix, the i-th swap matrix is ​​obtained; Based on the elements of row J in the first matrix, the elements of row J in the second matrix, and the elements of row J in I of the exchange matrices, experimental aberration coefficients corresponding to (I+2)×J of the experiments are obtained, so as to perform (I+2)×J of the experiments on the lithography system to obtain (I+2)×J of the experimental development pattern parameters.

3. The method according to claim 2, wherein, The step of calculating the influence parameters of the I geometric aberration terms based on the experimental development pattern parameters corresponding to the aberration information of the photolithography system and the number of samplings for the I geometric aberration terms in the aberration information includes: Based on (I+2)×J experimental development pattern parameters, the parameter variance corresponding to the experimental development pattern parameters is calculated. The influence parameter is calculated based on the first target experimental development pattern parameter among (I+2)×J experimental development pattern parameters, the second target experimental development pattern parameter among (I+2)×J experimental development pattern parameters, the parameter variance, and the number of samplings. The first target experimental development pattern parameter corresponds to the first target element in the i-th exchange matrix, and the second target experimental development pattern parameter corresponds to the second target element in the first matrix. The row position of the first target element in the i-th exchange matrix is ​​the same as the row position of the second target element in the first matrix.

4. The method according to claim 3, wherein, Each of the (I+2)×J experimental development pattern parameters includes a development pattern linewidth parameter and a development pattern position offset parameter. The step of determining the target geometric aberration term from the I geometric aberration terms based on the influence parameters of the I geometric aberration terms includes: Based on the influence parameters corresponding to the developed pattern linewidth parameters, a first target geometric aberration term corresponding to the developed pattern linewidth parameters is determined from the I geometric aberration terms. Based on the influence parameter corresponding to the developed pattern position offset parameter, a second target geometric aberration term corresponding to the developed pattern position offset parameter is determined from the I geometric aberration terms; The target geometric aberration term is obtained based on the first target geometric phase difference term and the second target geometric aberration term.

5. The method according to claim 4, wherein, The step of determining the first target geometric aberration term corresponding to the linewidth parameter of the developed pattern from the I geometric aberration terms based on the influence parameter corresponding to the linewidth parameter of the developed pattern includes: Based on the influence parameters corresponding to the line width parameters of the developed pattern, the I geometric aberration terms are sorted to obtain a first sorting result; Based on the influence parameter corresponding to the linewidth parameter of the developed pattern, the first sorting result, and the first predetermined threshold, the first target geometric aberration term is determined from the I geometric aberration terms.

6. The method according to claim 5, wherein, There are I influencing parameters corresponding to the linewidth parameter of the developing pattern; The step of determining the first target geometric aberration term from the I geometric aberration terms based on the influence parameter corresponding to the linewidth parameter of the developed pattern, the first sorting result, and the first predetermined threshold includes: The first total parameter is calculated based on I influence parameters corresponding to the linewidth parameter of the developed pattern; According to the first sorting result, the i-th influencing parameter among the I influencing parameters corresponding to the line width parameter of the developing pattern is accumulated to obtain the first parameter sum; The first ratio is obtained based on the proportion of the first parameter to the sum of the first total parameters; If the first ratio is greater than or equal to the first predetermined threshold, the geometric aberration term corresponding to the i influence parameters among the I influence parameters corresponding to the development pattern linewidth parameter is determined as the first target geometric aberration term.

7. The method according to claim 4, wherein, The step of determining the second target geometric aberration term corresponding to the developed pattern position offset parameter from the I geometric aberration terms based on the influence parameter corresponding to the developed pattern position offset parameter includes: Based on the influence parameters corresponding to the position offset parameters of the developed pattern, the I geometric aberration terms are sorted to obtain a second sorting result; Based on the influence parameter corresponding to the position offset parameter of the developed pattern, the second sorting result, and the second predetermined threshold, the second target geometric aberration term is determined from the I geometric aberration terms.

8. The method according to claim 7, wherein, There are I influencing parameters corresponding to the development pattern position offset parameter; The step of determining the second target geometric aberration term from the I geometric aberration terms based on the influence parameter corresponding to the position offset parameter of the developed pattern, the second sorting result, and the second predetermined threshold includes: The second total parameter is calculated based on the I influence parameters corresponding to the developed pattern position offset parameter; According to the second sorting result, the i-th influencing parameter among the I influencing parameters corresponding to the developing pattern position offset parameter is accumulated to obtain the second parameter sum; The second ratio is obtained based on the proportion of the second parameter to the sum of the second total parameters; If the second ratio is greater than or equal to the second predetermined threshold, the geometric aberration term corresponding to the i influence parameters among the I influence parameters corresponding to the development pattern position offset parameter is determined as the second target geometric aberration term.

9. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 8.

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