Photoetching pattern prediction method and device based on NTD model, equipment and medium
By constructing a photolithography pattern prediction method based on the NTD model, using the photoresist evaporation amount and Lamé constant to construct a deformation kernel function, and simulating the photoresist shrinkage effect, the problem of insufficient simulation accuracy caused by the photoresist shrinkage effect in the negative development model is solved, and high-precision prediction of photolithography patterns is achieved.
Patent Information
- Application Number
- CN202510555892.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-29
- Publication Date
- 2025-09-26
AI Technical Summary
The existing negative development model has a photoresist shrinkage effect during the photolithography process, resulting in insufficient accuracy in small-size graphic simulation and affecting the prediction accuracy of photolithography graphics.
By constructing a photolithography pattern prediction method based on the NTD model, using the photoresist evaporation amount and the Lamé constant as parameters, a deformation kernel function is constructed to simulate the shrinkage effect of the photoresist during the negative development process, and the target NTD model is optimized to improve the accuracy of the photolithography pattern.
The simulation accuracy of photolithography patterns has been improved, and the deformation of photoresist during negative development can be more accurately predicted, thereby improving the precision and reliability of the photolithography process.
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Figure CN120704072A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to, but is not limited to, the field of semiconductor technology, and in particular to a method, device, equipment, and medium for predicting photolithography patterns based on an NTD model. Background Art
[0002] With the continuous advancement of photolithography technology and increasingly advanced process nodes, the requirements for the accuracy and complexity of photolithography models are also increasing. Positive development (PTD) is a common development technology currently in use. Positive development models based on PTD technology add multiple photoresist parameters to the optical model to simulate various effects such as photoacid diffusion and nonlinearity, thereby improving model accuracy. However, as critical dimensions continue to shrink, the positive development model faces challenges with insufficient simulation resolution and reduced pattern fidelity due to the physical and chemical limitations of the exposure and development processes. To address these issues, negative development (NTD) technology has emerged. By washing away the positive resist, negative development technology offers higher contrast. Furthermore, negative development models employing this technology can also simulate patterns with smaller critical dimensions (CDs). However, in practical applications, significant photoresist shrinkage effects exist, making it difficult for negative development models to predict pattern cross-sectional shapes, which in turn affects the accuracy of simulations for small patterns. Summary of the Invention
[0003] The embodiments of the present application provide a method, device, equipment, and medium for predicting photolithographic patterns based on the NTD model, which can simulate the deformation of the photoresist caused by the photoresist shrinkage effect during the negative development process, thereby improving the accuracy of the photolithographic pattern.
[0004] In a first aspect, an embodiment of the present application provides a lithography pattern prediction method based on an NTD model, comprising:
[0005] Acquiring photoresist information, wafer information, mask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information;
[0006] Importing the photoresist information, the wafer information, the mask information and the light source information into the first OPC model for iterative calculation to obtain a second OPC model;
[0007] Determining the photoresist evaporation amount of the target photoresist, and iteratively calculating the second OPC model based on the photoresist evaporation amount and the Lamé constant to obtain a target NTD model;
[0008] The lithographic pattern of the target wafer is predicted based on the target NTD model.
[0009] In some embodiments, iteratively calculating the second OPC model based on the photoresist evaporation amount and the Lamé constant to obtain a target NTD model includes:
[0010] Constructing a deformation kernel function of the target photoresist based on the photoresist evaporation amount and the Lame constant;
[0011] The second OPC model is iteratively calculated based on the deformation kernel function and the deformation displacement of each position point on the target photoresist to obtain the target NTD model.
[0012] In some embodiments, constructing a deformation kernel function of the target photoresist based on the photoresist evaporation amount and the Lamé constant includes:
[0013] Determining a first stress tensor and a first strain tensor of the target photoresist, wherein the first stress tensor is the stress tensor of the target photoresist without considering photoresist evaporation loss, and the first strain tensor is the strain tensor of the target photoresist without considering photoresist evaporation loss;
[0014] Obtaining a second stress tensor according to the photoresist evaporation amount, the Lame constant, the first stress tensor, and the first strain tensor, wherein the second stress tensor is a stress tensor corresponding to the target photoresist taking into account the photoresist evaporation loss;
[0015] Determining, based on the second stress tensor, the displacement distribution of each position point in the target photoresist under a photoresist shrinkage effect state and stress balance conditions;
[0016] The light intensity distribution of the target photoresist is determined, and a two-dimensional Fourier transform is performed on the displacement distribution and the light intensity distribution to obtain the deformation kernel function.
[0017] In some embodiments, after predicting the lithographic pattern of the target wafer based on the target NTD model, the method further includes:
[0018] Acquire real wafer data, including reference lithography patterns actually produced on the production line that meet mask requirements;
[0019] Comparing the reference lithography pattern with the lithography pattern predicted by the target NTD model to obtain an error value;
[0020] When the error value falls within the preset error range, the photoresist evaporation amount and the Lame constant are adjusted according to the preset parameter adjustment range, and the second OPC model is iteratively optimized based on the adjusted photoresist evaporation amount and the Lame constant until the error value between the photolithography pattern predicted by the optimized target NTD model and the reference photolithography pattern falls within the preset error range.
[0021] In a second aspect, an embodiment of the present application provides a lithography pattern prediction device based on an NTD model, comprising:
[0022] A first data acquisition unit is configured to acquire photoresist information, wafer information, mask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information;
[0023] A first model building unit is configured to import the photoresist information, the wafer information, the mask information, and the light source information into a first OPC model for iterative calculation to obtain a second OPC model;
[0024] a second model building unit, configured to determine a photoresist evaporation amount of the target photoresist, and iteratively calculate the second OPC model based on the photoresist evaporation amount and a Lame constant to obtain a target NTD model;
[0025] A lithography pattern prediction unit is used to predict the lithography pattern of the target wafer based on the target NTD model.
[0026] In some embodiments, the second model building unit includes:
[0027] a deformation kernel function construction unit, configured to construct a deformation kernel function of the target photoresist based on the photoresist evaporation amount and the Lamé constant;
[0028] The target NTD model construction unit is configured to iteratively calculate the second OPC model based on the deformation kernel function and the deformation displacement of each position point on the target photoresist to obtain the target NTD model.
[0029] In some embodiments, the deformation kernel function construction unit includes:
[0030] a second data acquisition unit, configured to determine a first stress tensor and a first strain tensor of the target photoresist, wherein the first stress tensor is the stress tensor of the target photoresist without considering photoresist evaporation loss, and the first strain tensor is the strain tensor of the target photoresist without considering photoresist evaporation loss;
[0031] a first data processing unit, configured to obtain a second stress tensor according to the photoresist evaporation amount, the Lame constant, the first stress tensor, and the first strain tensor, wherein the second stress tensor is a stress tensor corresponding to the target photoresist taking into account the photoresist evaporation loss;
[0032] a second data processing unit for determining, based on the second stress tensor, the displacement distribution of each position point in the target photoresist under the photoresist shrinkage effect state and stress balance conditions;
[0033] The third data processing unit is used to determine the light intensity distribution of the target photoresist, perform a two-dimensional Fourier transform on the displacement distribution and the light intensity distribution, and obtain the deformation kernel function.
[0034] In some embodiments, the lithography pattern prediction apparatus based on the NTD model further includes:
[0035] A third data acquisition unit is used to acquire real wafer data, where the real wafer data includes a reference lithography pattern actually produced on the production line that meets the mask requirements;
[0036] an error calculation unit, configured to compare the reference lithography pattern with the lithography pattern predicted by the target NTD model to obtain an error value;
[0037] A model optimization unit is configured to adjust the photoresist evaporation amount and the Lame constant according to a preset parameter adjustment range when the error value portion falls within a preset error range, and iteratively optimize the second OPC model based on the adjusted photoresist evaporation amount and the Lame constant until the error value between the photolithography pattern predicted by the optimized target NTD model and the reference photolithography pattern falls within the preset error range.
[0038] In a third aspect, an embodiment of the present application provides an electronic device comprising at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor to enable the at least one control processor to execute the NTD model-based lithography graphic prediction method as described in the first aspect.
[0039] In a third aspect, an embodiment of the present application further provides an electronic device comprising the control device of the second aspect.
[0040] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the lithography pattern prediction method based on the NTD model as described in the first aspect.
[0041] The present application provides a method, apparatus, device, and medium for predicting photolithographic patterns based on an NTD model. The method comprises: obtaining photoresist information, wafer information, photomask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information; importing the photoresist information, wafer information, photomask information, and light source information into a first OPC model for iterative calculation to obtain a second OPC model; determining the photoresist evaporation amount of the target photoresist, and iteratively calculating the second OPC model based on the photoresist evaporation amount and the Lamé constant to obtain a target NTD model; and predicting the photolithographic pattern of the target wafer based on the target NTD model. According to the solution provided in the present application, the photoresist evaporation amount and the Lamé constant are used as new model construction parameters to construct a target NTD model that takes into account the photoresist shrinkage effect. This method can simulate the deformation of the photoresist caused by the photoresist shrinkage effect during the negative development process, effectively improving the accuracy of the photolithographic pattern compared to existing negative development photoresist models. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] Figure 1 This is a flowchart of the steps of a lithography pattern prediction method based on an NTD model provided in one embodiment of the present application;
[0043] Figure 2 This is a module diagram of a lithography pattern prediction device based on an NTD model provided by an embodiment of the present application; Figure 3 This is a structural diagram of an electronic device provided in another embodiment of the present application. DETAILED DESCRIPTION
[0044] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.
[0045] It is understood that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and the like in the specification, claims, or accompanying drawings are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.
[0046] With the continuous development of photolithography technology and increasingly advanced process nodes, the requirements for the accuracy and complexity of photolithography models are also increasing. Positive development (PTD) is currently a common development technology. Positive development models based on PTD technology add multiple photoresist parameters to the optical model to simulate various effects such as photoacid diffusion and nonlinearity, thereby improving model accuracy. However, as critical dimensions continue to shrink, the positive development model faces problems such as insufficient simulation resolution and reduced pattern fidelity due to the physical and chemical limitations of the exposure and development processes, which in turn affects the accuracy of the simulated photolithography patterns.
[0047] To address the above-mentioned problems, embodiments of the present application provide a method, apparatus, device, and medium for predicting photolithographic patterns based on an NTD model. The method comprises: obtaining photoresist information, wafer information, mask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information; importing the photoresist information, wafer information, mask information, and light source information into a first OPC model for iterative calculation to obtain a second OPC model; determining the photoresist evaporation amount of the target photoresist, and iteratively calculating the second OPC model based on the photoresist evaporation amount and the Lame constant to obtain a target NTD model; and predicting the photolithographic pattern of the target wafer based on the target NTD model. According to the solution provided in the embodiments of the present application, the photoresist evaporation amount and the Lame constant are used as new model construction parameters to construct a target NTD model that takes into account the photoresist shrinkage effect, thereby simulating the deformation of the photoresist caused by the photoresist shrinkage effect during the negative development process. Compared with the existing negative development photoresist model, the accuracy of the photolithographic pattern is effectively improved.
[0048] The embodiments of the present application are further described below with reference to the accompanying drawings.
[0049] refer to Figure 1 , Figure 1 This is a flowchart of a method for predicting a lithography pattern based on an NTD model provided by an embodiment of the present application. The embodiment of the present application provides a method for predicting a lithography pattern based on an NTD model, which includes but is not limited to the following steps:
[0050] Step S10 , obtaining photoresist information, wafer information, mask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information.
[0051] In step S20 , the photoresist information, wafer information, mask information, and light source information are imported into the first OPC model for iterative calculation to obtain a second OPC model.
[0052] Specifically, the photoresist information, wafer information, mask information, and light source information of this embodiment are actual measurement data for the target wafer, and serve as modeling data for the subsequent two-dimensional OPC model.
[0053] Specifically, this embodiment implements the construction of the second OPC model by using OPC software. The steps of obtaining data such as photoresist information, wafer information, mask information and light source information ensure that the physical information related to the lithography process of the target wafer is accurately captured, providing an effective data basis for the subsequent construction of the target NTD model and obtaining accurate lithography graphics. Moreover, after obtaining the photoresist information, wafer information, mask information and light source information, this information is imported into the OPC software, so that the OPC software performs in-depth calculation processing on this information and the first OPC model. After multiple iterative calculations, a preliminary simulation model, namely the second OPC model, is calculated. The second OPC model can calculate the chemical effects and optical proximity effects in the lithography process.
[0054] Step S30 , determining the photoresist evaporation amount of the target photoresist, and iteratively calculating the second OPC model based on the photoresist evaporation amount and the Lamé constant to obtain a target NTD model.
[0055] Specifically, the target NTD model constructed based on the second OPC model in this embodiment is a photoresist model based on negative development technology that takes into account the shrinkage effect of the photoresist (ie, photoresist) during the negative development process.
[0056] It is understandable that because the physical effect of the target photoresist during the shrinkage effect is very similar to the elastic deformation of a solid, and it is in a solid state after PEB and development, the deformation caused by the shrinkage effect can be simulated using the elastic mechanics of a solid. In this embodiment, the photoresist evaporation amount of the target photoresist is determined, and the second OPC model is iteratively calculated in combination with the Lamé constant and other shrinkage effect information related to elastic mechanics. The resulting target NTD model can calculate the impact of the shrinkage effect of the target photoresist on the photolithography process, including the evaporation effect and the shrinkage rate caused by stress. The environment considered will be more specific and realistic, thereby effectively ensuring the accuracy of the predicted photolithography pattern.
[0057] Specifically, in some embodiments, Figure 1 Step S30 includes but is not limited to the following steps:
[0058] Step S31, constructing a deformation kernel function of the target photoresist based on the photoresist evaporation amount and the Lamé constant;
[0059] Step S32 , performing iterative calculation on the second OPC model based on the deformation kernel function and the deformation displacement of each position point on the target photoresist, to obtain a target NTD model.
[0060] Specifically, in some embodiments, step S31 includes but is not limited to the following steps:
[0061] Step S311, determining a first stress tensor and a first strain tensor of a target photoresist, wherein the first stress tensor is the stress tensor of the target photoresist without considering photoresist evaporation loss, and the first strain tensor is the strain tensor of the target photoresist without considering photoresist evaporation loss;
[0062] Step S312, obtaining a second stress tensor according to the photoresist evaporation amount, the Lamé constant, the first stress tensor, and the first strain tensor, wherein the second stress tensor is a stress tensor corresponding to the target photoresist taking into account the photoresist evaporation loss;
[0063] Step S313, determining the displacement distribution of each position point in the target photoresist under the photoresist shrinkage effect state and stress balance condition based on the second stress tensor;
[0064] In step S314, the light intensity distribution of the target photoresist is determined, and a two-dimensional Fourier transform is performed on all displacement distributions and light intensity distributions to obtain a deformation kernel function.
[0065] It is understandable that the shrinkage effect of the photoresist will cause the displacement distribution and stress of the target photoresist to exist in the following three situations: (1) Boundary condition 1, that is, the target photoresist does not deform on the contact surface between the target photoresist and the target wafer, that is, the displacement of each position point on the target photoresist is 0; (2) Boundary condition 2, that is, the stress in the normal direction of the contact surface between the target photoresist and the air is 0; (3) The condition of internal steady state, that is, the stress in all directions inside the target photoresist is balanced. This embodiment takes the steady state condition of the target photoresist after exposure and development as the simulation target. Specifically, this embodiment determines the first stress tensor and the first strain tensor of the target photoresist, and then obtains the second stress tensor corresponding to the photoresist evaporation loss based on the photoresist evaporation amount, the Lame constant, the first stress tensor and the first strain tensor. Based on the second stress tensor, the displacement distribution of each position point in the target photoresist under the photoresist shrinkage effect state and stress balance conditions is determined, and the light intensity distribution of the target photoresist is determined. A two-dimensional Fourier transform is performed on all the displacement distributions and light intensity distributions to obtain the deformation kernel function. The deformation kernel function is a bridge connecting the light intensity distribution and the deformation of the photoresist. In this embodiment, the deformation kernel function is first calculated, and then the displacement of each position point of the target photoresist is calculated by convolution of the deformation kernel function and the evaporation ratio at each position point of the target photoresist during simulation to achieve a quantitative shrinkage effect. Finally, the second OPC model is iteratively calculated based on the deformation kernel function and the deformation displacement of each position point on the target photoresist to obtain a target NTD model, that is, the quantified result of the shrinkage effect is integrated into the second OPC model to construct an accurate target NTD model.
[0066] It should be noted that the relationship between the displacement of each position point of the target photoresist and the deformation kernel function of this embodiment is obtained according to the following formula:
[0067]
[0068] Among them, r s (x, y, z) is the displacement of each position point on the target photoresist, G(x, y, z) is the deformation kernel function, is the roll-and-roll operation, V(x,y,z) is the evaporation ratio of each position point on the target photoresist under the shrinkage effect, (x,y,z) and (x ′ ,y ′ ,z ′ ) corresponds to the spatial coordinates of different positions on the target photoresist.
[0069] Step S40 , predicting the lithographic pattern of the target wafer based on the target NTD model.
[0070] It can be understood that this embodiment uses the photoresist evaporation amount and the Lamé constant as new model construction parameters to construct a target NTD model that takes into account the photoresist shrinkage effect, thereby being able to simulate the deformation of the photoresist caused by the photoresist shrinkage effect during the negative development process. The target NTD model is used to predict the photolithography pattern of the target wafer, which is more accurate than the photolithography pattern predicted based on the existing negative development photoresist model, thereby providing an effective data basis for the subsequent production of masks that meet production needs.
[0071] Additionally, in some embodiments, when executing Figure 1 After step S40, the lithography pattern prediction method based on the NTD model provided in the embodiment of the present application includes but is not limited to the following steps:
[0072] Step S51, obtaining real wafer data, where the real wafer data includes a reference lithography pattern actually produced on the production line that meets the mask requirements;
[0073] Step S52, performing an error comparison between the reference lithography pattern and the lithography pattern predicted by the target NTD model to obtain an error value;
[0074] In step S53, when the error value falls within the preset error range, the photoresist evaporation amount and the Lamé constant are adjusted according to the preset parameter adjustment range, and the second OPC model is iteratively optimized based on the adjusted photoresist evaporation amount and the Lamé constant until the error value between the photolithography pattern predicted by the optimized target NTD model and the reference photolithography pattern falls within the preset error range.
[0075] It is understandable that after the target NTD model is constructed, in order to verify the reliability and accuracy of the target NTD model, the present embodiment compares the OPC wafer data actually produced on the production line, that is, the real wafer data, with the model simulation data. The real wafer data includes a reference lithography pattern. The reference lithography pattern is a lithography pattern actually produced on the production line that meets the mask requirements. The present embodiment uses the comparison result between the reference lithography pattern and the lithography pattern as a judgment indicator of the performance of the target NTD model. When the error value falls within the preset error range, it means that the target NTD model constructed by the present embodiment meets the standard and can be directly applied to the actual production of customer products. When the error value does not fall within the preset error range, it means that the standard has not been met. In this case, the present embodiment adjusts the parameter according to the preset range (the error value in this field is not within the preset error range). The technicians can confirm it according to the actual situation, and no restrictions are imposed here) adjust the photoresist evaporation amount and the Lame constant, and re-iterate and optimize the second OPC model based on the adjusted photoresist evaporation amount and the Lame constant until the error value between the photolithography pattern predicted by the optimized target NTD model and the reference photolithography pattern falls within the preset error range. That is to say, the optimization mechanism of the target NTD model provided in this embodiment effectively guarantees the reliability and accuracy of the target NTD model, thereby effectively taking into account the deformation caused by the shrinkage effect of the target photoresist during the negative development process, ensuring the accuracy of the simulation results, and thereby improving the accuracy and reliability of the photolithography process.
[0076] In addition, an embodiment of the present application further provides a lithography pattern prediction device based on the NTD model, comprising:
[0077] A first data acquisition unit 210 is configured to acquire photoresist information, wafer information, mask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information;
[0078] The first model building unit 220 is used to import the photoresist information, wafer information, mask information and light source information into the first OPC model for iterative calculation to obtain the second OPC model;
[0079] The second model building unit 230 is used to determine the photoresist evaporation amount of the target photoresist, and iteratively calculate the second OPC model based on the photoresist evaporation amount and the Lamé constant to obtain a target NTD model;
[0080] The lithography pattern prediction unit 240 is configured to predict the lithography pattern of the target wafer based on the target NTD model.
[0081] In some embodiments, the second model building unit 230 includes:
[0082] A deformation kernel function construction unit 231 is used to construct a deformation kernel function of a target photoresist based on the photoresist evaporation amount and the Lamé constant;
[0083] The target NTD model construction unit 232 is configured to perform iterative calculations on the second OPC model based on the deformation kernel function and the deformation displacement of each position point on the target photoresist to obtain the target NTD model.
[0084] In some embodiments, the deformation kernel function construction unit 231 includes:
[0085] The second data acquisition unit 2311 is configured to determine a first stress tensor and a first strain tensor of a target photoresist, wherein the first stress tensor is the stress tensor of the target photoresist without considering the photoresist evaporation loss, and the first strain tensor is the strain tensor of the target photoresist without considering the photoresist evaporation loss;
[0086] A first data processing unit 2312 is configured to obtain a second stress tensor based on the photoresist evaporation amount, the Lame constant, the first stress tensor, and the first strain tensor, wherein the second stress tensor is a stress tensor corresponding to the target photoresist taking into account the photoresist evaporation loss;
[0087] A second data processing unit 2313 is configured to determine, based on the second stress tensor, a displacement distribution of each position point in the target photoresist under a photoresist shrinkage effect state and a stress balance condition;
[0088] The third data processing unit 2314 is used to determine the light intensity distribution of the target photoresist, perform a two-dimensional Fourier transform on the displacement distribution and the light intensity distribution, and obtain a deformation kernel function.
[0089] In some embodiments, the lithography pattern prediction apparatus based on the NTD model further includes:
[0090] The third data acquisition unit 250 is used to acquire real wafer data, where the real wafer data includes a reference lithography pattern actually produced on the production line that meets the mask requirements;
[0091] an error calculation unit 260 for performing an error comparison between the reference lithography pattern and the lithography pattern predicted by the target NTD model to obtain an error value;
[0092] The model optimization unit 270 is used to adjust the photoresist evaporation amount and the Lame constant according to the preset parameter adjustment range when the error value part falls within the preset error range, and re-iteratively optimize the second OPC model based on the adjusted photoresist evaporation amount and the Lame constant until the error value between the photolithography pattern predicted by the optimized target NTD model and the reference photolithography pattern falls within the preset error range.
[0093] It should be noted that the specific implementation of the lithography pattern prediction device based on the NTD model is basically the same as the specific embodiment of the lithography pattern prediction based on the NTD model mentioned above, and will not be repeated here.
[0094] like Figure 3 As shown, Figure 3 : is a structural diagram of an electronic device provided in one embodiment of the present application. The present invention also provides a control device 300, including:
[0095] The processor 310 may be implemented as a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.
[0096] The memory 320 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 320 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 320 and is called by the processor 310 to execute the XXX method of the embodiments of this application.
[0097] Input / output interface 330, used to implement information input and output;
[0098] Communication interface 340, used to implement communication interaction between the apparatus and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);
[0099] bus 350 , which transmits information between the various components of the device (e.g., processor 310 , memory 320 , input / output interface 330 , and communication interface 340 );
[0100] The processor 310 , the memory 320 , the input / output interface 330 and the communication interface 340 are connected to each other in communication within the device via the bus 350 .
[0101] In addition, an embodiment of the present application further provides a storage medium, which is a computer-readable storage medium and stores a computer program. When the computer program is executed by a processor, the above-mentioned lithography pattern prediction method based on the OPC model is implemented.
[0102] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory optionally includes a memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of the above-mentioned networks include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and a combination thereof. The device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and are located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.
[0103] Those skilled in the art will appreciate that all or some of the steps and systems in the method disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media (or non-transitory media) and communication media (or temporary media). As known to those skilled in the art, the term computer storage media is included in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data) and is volatile and non-volatile, removable, and non-removable. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (DVD), or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage, or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically includes computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.
[0104] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above implementation. Those skilled in the art can also make various equivalent modifications or substitutions under the shared conditions that do not violate the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.
Claims
1. A lithography pattern prediction method based on the NTD model, characterized in that: include: Acquiring photoresist information, wafer information, mask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information; Importing the photoresist information, the wafer information, the mask information and the light source information into the first OPC model for iterative calculation to obtain a second OPC model; Determining the photoresist evaporation amount of the target photoresist, and iteratively calculating the second OPC model based on the photoresist evaporation amount and the Lamé constant to obtain a target NTD model; The lithographic pattern of the target wafer is predicted based on the target NTD model.
2. The lithography pattern prediction method based on the NTD model according to claim 1, characterized in that: The second OPC model is iteratively calculated based on the photoresist evaporation amount and the Lame constant to obtain a target NTD model, including: Constructing a deformation kernel function of the target photoresist based on the photoresist evaporation amount and the Lame constant; The second OPC model is iteratively calculated based on the deformation kernel function and the deformation displacement of each position point on the target photoresist to obtain the target NTD model.
3. The lithography pattern prediction method based on the NTD model according to claim 2, characterized in that: Constructing a deformation kernel function of the target photoresist based on the photoresist evaporation amount and the Lamé constant, comprising: Determining a first stress tensor and a first strain tensor of the target photoresist, wherein the first stress tensor is the stress tensor of the target photoresist without considering photoresist evaporation loss, and the first strain tensor is the strain tensor of the target photoresist without considering photoresist evaporation loss; Obtaining a second stress tensor according to the photoresist evaporation amount, the Lame constant, the first stress tensor, and the first strain tensor, wherein the second stress tensor is a stress tensor corresponding to the target photoresist taking into account the photoresist evaporation loss; Determining, based on the second stress tensor, the displacement distribution of each position point in the target photoresist under a photoresist shrinkage effect state and stress balance conditions; The light intensity distribution of the target photoresist is determined, and a two-dimensional Fourier transform is performed on the displacement distribution and the light intensity distribution to obtain the deformation kernel function.
4. The lithography pattern prediction method based on the NTD model according to claim 1, characterized in that: After predicting the lithographic pattern of the target wafer based on the target NTD model, the method further includes: Acquire real wafer data, including reference lithography patterns actually produced on the production line that meet mask requirements; Comparing the reference lithography pattern with the lithography pattern predicted by the target NTD model to obtain an error value; When the error value falls within the preset error range, the photoresist evaporation amount and the Lame constant are adjusted according to the preset parameter adjustment range, and the second OPC model is iteratively optimized based on the adjusted photoresist evaporation amount and the Lame constant until the error value between the photolithography pattern predicted by the optimized target NTD model and the reference photolithography pattern falls within the preset error range.
5. A lithography pattern prediction device based on the NTD model, characterized in that: include: A first data acquisition unit is configured to acquire photoresist information, wafer information, mask information, and light source information corresponding to a target wafer, wherein the surface of the target wafer is coated with a target photoresist corresponding to the photoresist information; A first model building unit is configured to import the photoresist information, the wafer information, the mask information, and the light source information into a first OPC model for iterative calculation to obtain a second OPC model; a second model building unit, configured to determine a photoresist evaporation amount of the target photoresist, and iteratively calculate the second OPC model based on the photoresist evaporation amount and a Lame constant to obtain a target NTD model; A lithography pattern prediction unit is used to predict the lithography pattern of the target wafer based on the target NTD model.
6. The lithography pattern prediction device based on the NTD model according to claim 5, characterized in that: The second model building unit includes: a deformation kernel function construction unit, configured to construct a deformation kernel function of the target photoresist based on the photoresist evaporation amount and the Lamé constant; The target NTD model construction unit is configured to iteratively calculate the second OPC model based on the deformation kernel function and the deformation displacement of each position point on the target photoresist to obtain the target NTD model.
7. The lithography pattern prediction device based on the NTD model according to claim 6, characterized in that: The deformation kernel function construction unit includes: a second data acquisition unit, configured to determine a first stress tensor and a first strain tensor of the target photoresist, wherein the first stress tensor is the stress tensor of the target photoresist without considering photoresist evaporation loss, and the first strain tensor is the strain tensor of the target photoresist without considering photoresist evaporation loss; a first data processing unit, configured to obtain a second stress tensor according to the photoresist evaporation amount, the Lame constant, the first stress tensor, and the first strain tensor, wherein the second stress tensor is a stress tensor corresponding to the target photoresist taking into account the photoresist evaporation loss; a second data processing unit, configured to determine, based on the second stress tensor, a displacement distribution of each position point in the target photoresist under a photoresist shrinkage effect state and a stress balance condition; The third data processing unit is used to determine the light intensity distribution of the target photoresist, perform a two-dimensional Fourier transform on the displacement distribution and the light intensity distribution, and obtain the deformation kernel function.
8. The lithography pattern prediction device based on the NTD model according to claim 5, characterized in that: Also includes: A third data acquisition unit is used to acquire real wafer data, where the real wafer data includes a reference lithography pattern actually produced on the production line that meets the mask requirements; an error calculation unit, configured to compare the reference lithography pattern with the lithography pattern predicted by the target NTD model to obtain an error value; A model optimization unit is configured to adjust the photoresist evaporation amount and the Lame constant according to a preset parameter adjustment range when the error value portion falls within a preset error range, and iteratively optimize the second OPC model based on the adjusted photoresist evaporation amount and the Lame constant until the error value between the photolithography pattern predicted by the optimized target NTD model and the reference photolithography pattern falls within the preset error range.
9. An electronic device, characterized in that: It includes at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor to enable the at least one control processor to execute the lithography graphic prediction method based on the NTD model as described in any one of claims 1 to 4.
10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the lithography pattern prediction method based on the NTD model according to any one of claims 1 to 4.