A method for establishing a photoresist model and electronic equipment

Abstract

The present invention relates to the technical field of integrated circuit manufacturing, and in particular to a method for establishing a photoresist model and an electronic device, comprising: S1, providing a mask design layout and an electron microscope scanning image, wherein the mask design layout includes at least one mask image, and the electron microscope scanning image includes at least one scanning pattern, and aligning the at least one scanning pattern with the at least one mask image to obtain at least one aligned scanning pattern; S2, identifying the outer boundary or inner boundary of the at least one aligned scanning pattern; S3, extracting at least the position information of the outer boundary or inner boundary of the at least one aligned scanning pattern to form a data set; and S4, establishing a photoresist model based on the data set. The position information of the outer boundary or the inner boundary is extracted to form a data set, and the data is relatively easy to obtain and the quantity is relatively large, so that the formed data set is better used for model establishment, and at the same time, the position information of the outer boundary or the inner boundary is single point data, which is absolute position information, and the photoresist model can be established more accurately.

Description

[Technical field]

[0001] The present invention relates to the technical field of integrated circuit manufacturing, and in particular to a method for establishing a photoresist model and electronic equipment. [Background technology]

[0002] In the manufacturing process of modern very large-scale integrated circuits, the photolithography process is the most important step, which transfers the pattern on the mask to the silicon wafer to prepare for the subsequent process. At the current nano-level technology node, in order to produce the desired silicon wafer pattern, it is necessary to use computational lithography technology to optimize the mask design layout. Therefore, when calibrating the current process parameters, the quality of the obtained photoresist model will directly affect the subsequent operations of computational lithography: such as mask optimization, light source mask coordination optimization and other processes.

[0003] In the process of model building, silicon wafer critical dimension (CD) data is one of the modeling inputs and is the main factor affecting the model building effect. Traditional silicon wafer CD data is obtained by manual measurement on the scanning electron micrograph (S EM) of silicon wafers, so the amount of data is often very limited, and the establishment and verification of the model is not sufficient. Especially in the photoresist modeling in the negative development (NTD) technology, there are many adjustable optimization parameters, which leads to an abnormally large solution space of the model and a very slow speed when performing gradient-free optimization. If there is abundant silicon wafer data, the restrictions on the adjustable parameters of the photoresist item can be increased, making the optimization direction more obvious, thereby speeding up the modeling speed and improving the model accuracy. [Summary of the invention]

[0004] In order to overcome the current technical problem of low accuracy in establishing a photoresist model, the present invention provides a method for establishing a photoresist model and an electronic device.

[0005] In order to solve the above technical problems, the present invention provides a technical solution: a method for establishing a photoresist model, which comprises the following steps: S1, providing a mask design layout and an electron microscope scanning image corresponding to the mask design layout, imaging the mask design layout, wherein the mask design layout after imaging includes at least one mask image, the electron microscope scanning image includes at least one scanning pattern corresponding to the at least one mask image, and aligning the at least one scanning pattern with the at least one mask image to obtain at least one aligned scanning pattern; S2, identifying the outer boundary or inner boundary of the at least one aligned scanning pattern based on an edge detection algorithm; S3, at least extracting the position information of the outer boundary or inner boundary of the at least one aligned scanning pattern to form a data set; and S4, establishing a photoresist model based on the data set.

[0006] Preferably, the method for establishing the photoresist model also includes the following steps: S20, determining whether there is measured CD data, if not, executing steps S3 and S4; if so, executing steps S21, S22 and S4: S21, adjusting the at least one alignment scanning pattern at least once based on the measured CD data to obtain at least one precise alignment scanning pattern; S22, extracting at least the position information of the outer boundary or inner boundary of the at least one precise alignment scanning pattern to form a data set; steps S20, 21 and S22 are after step S2.

[0007] Preferably, the above-mentioned step S1 specifically includes the following steps: S11, identifying the contour of the scanning pattern and the contour of the mask image based on an edge detection algorithm; S12, providing coordinate parameters about the electron microscope scanning image, and preliminarily aligning the contour of the scanning pattern with the contour of the mask image based on the coordinate parameters; S13, establishing an alignment evaluation function using the coordinate difference between the corresponding points of the contour of the scanning pattern and the contour of the mask image, and adjusting the re-alignment of the contour of the scanning pattern and the contour of the mask image based on the alignment evaluation function until the alignment evaluation function converges to obtain the aligned scanning pattern.

[0008] Preferably, the step S11 comprises the following steps: S111, adjusting the direction of the scanning pattern to be consistent with the direction of the mask image, and adjusting the size of the scanning pattern to match the size of the mask image;

[0009] S112, performing noise reduction processing on the scanned pattern using a Gaussian filter function; and S113, identifying the contours of the scanned image and the mask image based on an edge detection algorithm.

[0010] Preferably, the step S1 further comprises the following steps: S10, rounding the corners of the mask design layout, and imaging the rounded mask design layout; the step S10 is before the step S11.

[0011] Preferably, the above-mentioned step S21 specifically includes the following steps: S211, based on the position information of the measured CD data, intercepting the simulated CD data on the current alignment scanning pattern in the same direction as the measured CD data; S212, subtracting the measured CD data from the simulated CD data, and establishing an adjustment evaluation function based on at least the sum of the squares of the differences between all the measured CD data and the simulated CD data; S213, adjusting the current alignment scanning pattern at least once, and extracting the boundaries of the alignment scanning pattern after each adjustment, until the adjustment evaluation function converges to obtain a precise alignment scanning pattern.

[0012] Preferably, in the above step S4, a photoresist model is established based on the data set obtained in the step S3 in combination with the measured CD data, or a photoresist model is established based on the data set obtained in the step S22 in combination with the measured CD data.

[0013] Preferably, the data set obtained in step S3 and the data set obtained in step S22 are subjected to type conversion and denoising to establish a photoresist model.

[0014] Preferably, in the above step S3 or step S22, if it is a bright field mask, the outer boundary is extracted; if it is a dark field mask, the inner boundary is extracted.

[0015] In order to solve the above technical problems, the present invention also provides an electronic device, which includes one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method for establishing the photoresist model as described above.

[0016] Compared with the prior art, the method for establishing a photoresist model and the electronic device provided by the present invention have the following beneficial effects, including the following steps: S1, providing a mask design layout and an electron microscope scanning image, wherein the mask design layout includes at least one mask pattern, imaging the mask design layout, wherein the mask design layout after imaging includes at least one mask image corresponding to at least one mask pattern, and the electron microscope scanning image includes at least one scanning pattern corresponding to the at least one mask image, and aligning the at least one scanning pattern with the at least one mask image to obtain at least one aligned scanning pattern; S2, identifying the outer boundary or inner boundary of the at least one aligned scanning pattern based on an edge detection algorithm; S3, extracting at least the position information of the outer boundary or inner boundary of the at least one aligned scanning pattern to form a data set; and S4. 4. Establish a photoresist model based on the data set, extract the position information of the outer boundary or inner boundary of at least one pair of aligned scanning patterns to form a data set, the data of which is easier to obtain and the quantity is relatively large, so that the formed data set can be better used for model establishment. At the same time, the position information of the outer boundary or inner boundary is single-point data, which is absolute position information, and can establish the photoresist model more accurately.

[0017] The method for establishing the photoresist model also includes the following steps: S20, determining whether there is measured CD data, if not, executing step S3 and step S4; if so, executing step S21, step S22 and step S4: S21, adjusting the at least one alignment scanning pattern at least once based on the measured CD data to obtain at least one precise alignment scanning pattern; S22, extracting at least the position information of the outer boundary or inner boundary of the at least one precise alignment scanning pattern to form a data set; step S20, step 21 and step S22 are performed after step S2, and combined with the measured CD data, the alignment degree of the scanning pattern relative to the mask image can be well improved, so as to further improve the extracted data set to better represent the scanning pattern and improve the accuracy of model establishment.

[0018] In the above step S4, a photoresist model is established based on the data set obtained in step S3 combined with the measured CD data, or a photoresist model is established based on the data set obtained in step S22 combined with the measured CD data. The measured CD data and the data representing the boundary of the scanned pattern are combined as a data set to establish a photoresist model, so that the representativeness of the data set is greatly improved, so as to further improve the accuracy of model establishment.

[0019] The electronic device provided by the present invention has the same beneficial effects as the method.

Brief Description of the Drawings

[0020] Figure 1 is a flow chart of a method for establishing a photoresist model provided by a first embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of a mask design layout in a method for establishing a photoresist model provided in a first embodiment of the present invention;

[0022] Figure 3 is a schematic diagram of an electron microscope scanning image in the method for establishing a photoresist model provided in the first embodiment of the present invention;

[0023] Figure 4 It is a schematic diagram of aligning a scanning pattern with a mask image in the method for establishing a photoresist model provided by the first embodiment of the present invention;

[0024] Figure 5 is a detailed flow chart of step S1 in the method for establishing a photoresist model provided by the first embodiment of the present invention;

[0025] Figure 6 is a detailed flow chart of a variation of step S1 in the method for establishing a photoresist model provided in the first embodiment of the present invention;

[0026] Figure 7is a flow chart of a modified embodiment of the method for establishing a photoresist model provided by the first embodiment of the present invention;

[0027] Figure 8 is a detailed flow chart of step S21 in the method for establishing a photoresist model provided by the first embodiment of the present invention;

[0028] Fig. 9 is a schematic diagram of a module of an electronic device provided in a second embodiment of the present invention;

[0029] Fig.10 It is a schematic diagram of the structure of a computer system suitable for implementing a server of an embodiment of the present invention. [Specific implementation method]

[0030] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0031] See also Figure 1 The first embodiment of the present invention provides a method for establishing a photoresist model, comprising the following steps:

[0032] S1. Provide a mask design layout and an electron microscope scanning image, wherein the mask design layout includes at least one mask pattern, image the mask design layout, and the imaged mask design layout includes at least one mask image corresponding to the at least one mask pattern, and the electron microscope scanning image includes at least one scanning pattern corresponding to the at least one mask image, and align the at least one scanning pattern with the at least one mask image to obtain at least one aligned scanning pattern;

[0033] S2. Identifying the outer boundary or inner boundary of the at least one alignment scanning pattern based on an edge detection algorithm;

[0034] S3. Extracting at least the position information of the outer boundary or the inner boundary of the at least one alignment scanning pattern to form a data set; and

[0035] S 4. Establishing a photoresist model based on the data set.

[0036] In step S1 above, see Figure 2, a schematic diagram of a mask design layout, on which a plurality of long strip mask graphics are formed, corresponding to the area M in the figure. In some other embodiments, it can also be other shapes, such as trapezoids, irregular polygons, regular polygons and other graphics. Usually, when executing step S1 or performing lithography calculations, it is necessary to input the mask design layout in the format of GDS. Imaging the mask design layout usually involves converting it into a binary image. The grayscale value in the mask graphic area in the binary image can be 1, and the external grayscale value can be 0 to obtain the mask image. Similarly, the electron microscope scanning image can also be converted into a binary image.

[0037] See also Figure 3 , which is an electron microscope scanning image corresponding to the mask design layout obtained by a scanning electron microscope, wherein area M1 corresponds to the scanning pattern, corresponding to the mask image.

[0038] Please combine Figure 2 , Figure 3 and Figure 4 In the actual process of preparing chips by photolithography, the scanning pattern in the electron microscope scanning image obtained by a scanning electron microscope is usually not aligned with the mask image coordinates on the mask design layout. Therefore, it is necessary to load the electron microscope scanning image so that the scanning pattern thereon is aligned with the mask image on the mask design layout. The scanning pattern after alignment is called the alignment scanning pattern. The shape itself between the alignment scanning pattern and the scanning pattern has not changed, only the position is adjusted.

[0039] See also Figure 5 , the above step S1 specifically includes the following steps:

[0040] S11, identifying the contour of the scanning pattern and the contour of the mask image based on an edge detection algorithm;

[0041] S12, providing coordinate parameters about the electron microscope scanning image, and preliminarily aligning the contour of the scanning pattern with the contour of the mask image based on the coordinate parameters;

[0042] S13. Establish an alignment evaluation function using the coordinate difference between the corresponding points of the contour of the scanning pattern and the contour of the mask image, and adjust the re-alignment of the contour of the scanning pattern and the contour of the mask image based on the alignment evaluation function until the alignment evaluation function converges to obtain the aligned scanning pattern.

[0043] In the above step S11, the edge detection algorithm is the existing canny edge detection algorithm, and its specific recognition process is existing, which will not be described here.

[0044] In the above step S12, the coordinate parameters of the scanned pattern in the electron microscope scanning image provided are derived from the scanning electron microscope, which includes information such as the coordinate parameters of the scanned pattern, pixel size, and image size.

[0045] In the actual alignment process, due to the difference between the contour of the mask image and the contour of the scanned pattern, it is difficult to know how the positions between the two are related to each other so as to be considered aligned. Therefore, it is necessary to perform step S13, establish an alignment evaluation function based on the coordinate difference between the contour of the scanned pattern and the corresponding points of the contour of the mask image, and adjust the matching of the contour of the scanned pattern and the contour of the mask image based on the alignment evaluation function until the alignment evaluation function converges.

[0046] In the above step S2, the outer boundary or inner boundary of the at least one aligned scanning pattern is identified based on an edge detection algorithm. In this step, the boundary of the scanning pattern usually has a certain width. Therefore, it has an inner boundary and an outer boundary.

[0047] See also Figure 6 , the step S1 further comprises the following steps:

[0048] S10, performing rounding processing on the mask design layout, and imaging the rounded mask design layout;

[0049] The step S10 is before the step S11.

[0050] In some specific implementations, the step S11 includes the following steps:

[0051] S111, adjusting the direction of the scanning pattern to be consistent with the direction of the mask image, and adjusting the size of the scanning pattern to match the size of the mask image;

[0052] S112, performing noise reduction processing on the scan pattern using a Gaussian filter function; and

[0053] S113: Identify the contours of the scanned image and the mask image based on an edge detection algorithm.

[0054] In the above step S111, if the direction of the scan pattern is rotated relative to the direction of the mask image, it is necessary to rotate its direction accordingly first, otherwise good registration cannot be achieved.

[0055] In the above step S112, using a Gaussian filter function to perform noise reduction processing on the scan pattern can effectively remove image noise and improve recognition accuracy.

[0056] See also Figure 7As a variation, the method for establishing the photoresist model further includes the following steps:

[0057] S20, determine whether there is actual CD data, if not, execute step S3 and step S4;

[0058] If yes, then execute step S21, step S22 and step S4:

[0059] S21, adjusting the at least one alignment scanning pattern at least once based on the measured CD data to obtain at least one precise alignment scanning pattern;

[0060] S22, extracting at least the position information of the outer boundary or the inner boundary of the at least one precise alignment scanning pattern to form a data set;

[0061] Step S20 , step S21 and step S22 are performed after step S2 .

[0062] In the above step S20, the CD value is about the critical dimension of the silicon wafer. The measured CD data is obtained by manual measurement on the electron microscope scanning image of the silicon wafer, and the data volume is relatively limited.

[0063] If there is measured CD data, executing the above steps S21 and S22 (that is, replacing the above step S3 with steps S21 and S22) can further adjust the alignment degree between at least one scanning pattern and the at least one mask image, so that the accuracy of the extracted inner boundary or outer boundary data is higher, so as to obtain a more accurate model.

[0064] See also Figure 8 , the above step S21 specifically includes the following steps:

[0065] S211, intercepting the simulated CD data on the current alignment scanning pattern in the same direction as the measured CD data according to the position information of the measured CD data;

[0066] S212, subtracting the measured CD data from the simulated CD data, and establishing an adjustment evaluation function based at least on the sum of squares of all differences between the measured CD data and the simulated CD data;

[0067] S213, adjusting the current alignment scanning pattern at least once, and extracting the boundary of the alignment scanning pattern after each adjustment, until the adjustment evaluation function converges to obtain a precise alignment scanning pattern.

[0068] Usually, the user will first measure the CD data of the electron microscope scanning image to obtain the measured CD data. At this time, the user will also record the position information corresponding to the measured CD data, and the position information is calibrated with coordinate values. The simulated CD data is obtained by intercepting the alignment scan image. It can be understood that in step S11, the contour of the scan pattern and the contour of the mask image have been identified based on the edge detection algorithm. Therefore, the alignment scan image is also a contour image, but the position is appropriately adjusted relative to the contour of the scan pattern. Therefore, the simulated CD data can be obtained by directly intercepting it.

[0069] In the above step S4, a photoresist model is established based on the data set obtained in the step S3 in combination with the measured CD data, or a photoresist model is established based on the data set obtained in the step S22 in combination with the measured CD data.

[0070] The data set obtained in the step S3 and the data set obtained in the step S22 are subjected to type conversion and denoising to establish a photoresist model. The data is mainly converted into the same type as the measured CD data to facilitate modeling. Usually, after the data type conversion, the data set includes not only coordinate information but also corresponding direction information. The direction information can be consistent with the normal direction of the scan pattern contour boundary.

[0071] In the above step S3 or step S22, if it is a bright field mask, the outer boundary data is extracted; if it is a dark field mask, the inner boundary data is extracted.

[0072] After the photoresist model is obtained, in the process of evaluating the performance of the photoresist model, an evaluation function is established using the difference of the measured CD data as a variable and the coordinate difference of the data set obtained in step S3 or step S22 as a variable. The mask or other lithography variables are optimized based on the established objective function until the evaluation function converges.

[0073] See also Fig. 9 , a second embodiment of the present invention provides an electronic device 300, which includes one or more processors 301;

[0074] The storage device 302 is used to store one or more programs.

[0075] When the one or more programs are executed by the one or more processors 301 , the one or more processors 301 implement the method for establishing a photoresist model as provided in the first embodiment or its variant embodiments.

[0076] Reference below Fig.10, which shows a schematic diagram of the structure of a computer system 800 of a terminal device / server suitable for implementing an embodiment of the present invention. Fig.10 The terminal device / server shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present application.

[0077] like Fig.10 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage part 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the system 800 are also stored. The CPU 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0078] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed, so that a computer program read therefrom is installed into the storage section 808 as needed.

[0079] According to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above functions defined in the method of the present invention are executed. It should be noted that the computer-readable medium described in the present invention can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0080] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0081] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0082] The computer-readable medium carries one or more programs. When the one or more programs are executed by the device, the device executes the following steps: S1. Provide a mask design layout and an electron microscope scanning image, wherein the mask design layout includes at least one mask pattern, image the mask design layout, and the imaged mask design layout includes at least one mask image corresponding to the at least one mask pattern, and the electron microscope scanning image includes at least one scanning pattern corresponding to the at least one mask image, and align the at least one scanning pattern with the at least one mask image to obtain at least one aligned scanning pattern; S2. Identify the outer boundary or inner boundary of the at least one aligned scanning pattern based on an edge detection algorithm; S3. At least extract the position information of the outer boundary or inner boundary of the at least one aligned scanning pattern to form a data set; and S4. Establish a photoresist model based on the data set.

[0083] Compared with the prior art, the method for establishing a photoresist model and the electronic device provided by the present invention have the following beneficial effects, including the following steps: S1, providing a mask design layout and an electron microscope scanning image, wherein the mask design layout includes at least one mask pattern, imaging the mask design layout, wherein the mask design layout after imaging includes at least one mask image corresponding to at least one mask pattern, and the electron microscope scanning image includes at least one scanning pattern corresponding to the at least one mask image, and aligning the at least one scanning pattern with the at least one mask image to obtain at least one aligned scanning pattern; S2, identifying the outer boundary or inner boundary of the at least one aligned scanning pattern based on an edge detection algorithm; S3, extracting at least the position information of the outer boundary or inner boundary of the at least one aligned scanning pattern to form a data set; and S4. 4. Establish a photoresist model based on the data set, extract the position information of the outer boundary or inner boundary of at least one pair of aligned scanning patterns to form a data set, the data of which is easier to obtain and the quantity is relatively large, so that the formed data set can be better used for model establishment. At the same time, the position information of the outer boundary or inner boundary is single-point data, which is absolute position information, and can establish the photoresist model more accurately.

[0084] The method for establishing the photoresist model also includes the following steps: S20, determining whether there is measured CD data, if not, executing step S3 and step S4; if so, executing step S21, step S22 and step S4: S21, adjusting the at least one alignment scanning pattern at least once based on the measured CD data to obtain at least one precise alignment scanning pattern; S22, extracting at least the position information of the outer boundary or inner boundary of the at least one precise alignment scanning pattern to form a data set; step S20, step 21 and step S22 are performed after step S2, and combined with the measured CD data, the alignment degree of the scanning pattern relative to the mask image can be well improved, so as to further improve the extracted data set to better represent the scanning pattern and improve the accuracy of model establishment.

[0085] In the above step S4, a photoresist model is established based on the data set obtained in step S3 combined with the measured CD data, or a photoresist model is established based on the data set obtained in step S22 combined with the measured CD data. The measured CD data and the data representing the boundary of the scanned pattern are combined as a data set to establish a photoresist model, so that the representativeness of the data set is greatly improved, so as to further improve the accuracy of model establishment.

[0086] The electronic device provided by the present invention has the same beneficial effects as the method.

[0087] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for establishing a photoresist model, characterized in that: The steps include: S1, providing a mask design layout and an electron microscope scanning image corresponding to the mask design layout, imaging the mask design layout, wherein the imaged mask design layout includes at least one mask image, the electron microscope scanning image includes at least one scanning pattern corresponding to the at least one mask image, and aligning the at least one scanning pattern with the at least one mask image to obtain at least one aligned scanning pattern; S2. Identifying the outer boundary or inner boundary of the at least one alignment scanning pattern based on an edge detection algorithm; S3. Extracting at least the position information of the outer boundary or the inner boundary of the at least one alignment scanning pattern to form a data set; and S 4. Establishing a photoresist model based on the data set.

2. The method for establishing a photoresist model as claimed in claim 1, wherein: The method for establishing the photoresist model also includes the following steps: S20, determine whether there is actual CD data, if not, execute step S3 and step S4; If yes, then execute step S21, step S22 and step S4: S21, adjusting the at least one alignment scanning pattern at least once based on the measured CD data to obtain at least one precise alignment scanning pattern; S22, extracting at least the position information of the outer boundary or the inner boundary of the at least one precise alignment scanning pattern to form a data set; Step S20 , step S21 and step S22 are performed after step S2 .

3. The method for establishing a photoresist model as claimed in claim 1, characterized in that: The above step S1 specifically includes the following steps: S11, identifying the contour of the scanning pattern and the contour of the mask image based on an edge detection algorithm; S12, providing coordinate parameters about the electron microscope scanning image, and preliminarily aligning the contour of the scanning pattern with the contour of the mask image based on the coordinate parameters; S13. Establish an alignment evaluation function using the coordinate difference between the corresponding points of the contour of the scanning pattern and the contour of the mask image, and adjust the re-alignment of the contour of the scanning pattern and the contour of the mask image based on the alignment evaluation function until the alignment evaluation function converges to obtain the aligned scanning pattern.

4. The method for establishing a photoresist model as claimed in claim 3, characterized in that: The step S11 comprises the following steps: S111, adjusting the direction of the scanning pattern to be consistent with the direction of the mask image, and adjusting the size of the scanning pattern to match the size of the mask image; S112, performing noise reduction processing on the scan pattern using a Gaussian filter function; and S113: Identify the contours of the scanned image and the mask image based on an edge detection algorithm.

5. The method for establishing a photoresist model as claimed in claim 4, characterized in that: The step S1 further comprises the following steps: S10, performing rounding processing on the mask design layout, and imaging the rounded mask design layout; The step S10 is before the step S11.

6. The method for establishing a photoresist model as claimed in claim 2, characterized in that: The above step S21 specifically includes the following steps: S211, intercepting the simulated CD data on the current alignment scanning pattern in the same direction as the measured CD data according to the position information of the measured CD data; S212, subtracting the measured CD data from the simulated CD data, and establishing an adjustment evaluation function based at least on the sum of squares of all differences between the measured CD data and the simulated CD data; S213, adjusting the current alignment scanning pattern at least once, and extracting the boundary of the alignment scanning pattern after each adjustment, until the adjustment evaluation function converges to obtain a precise alignment scanning pattern.

7. The method for establishing a photoresist model as claimed in claim 6, characterized in that: In the above step S4, a photoresist model is established based on the data set obtained in the step S3 in combination with the measured CD data, or a photoresist model is established based on the data set obtained in the step S22 in combination with the measured CD data.

8. The method for establishing a photoresist model as claimed in claim 7, characterized in that: The data set obtained in step S3 and the data set obtained in step S22 are converted into different types and subjected to denoising to establish a photoresist model.

9. The method for establishing a photoresist model as claimed in claim 2, characterized in that: In the above step S3 or step S22, if it is a bright field mask, the outer boundary is extracted; if it is a dark field mask, the inner boundary is extracted.

10. An electronic device, characterized in that: It includes one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method for establishing a photoresist model as described in any one of claims 1 to 9.

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