Photoetching pattern prediction method based on bottom layer three-dimensional structure visible OPC model
By constructing a three-dimensional OPC model that accounts for underlying structure reflections, the method addresses the limitations of existing models, improving lithography pattern prediction accuracy and process reliability.
Patent Information
- Application Number
- CN202510555890.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-29
- Publication Date
- 2025-07-15
AI Technical Summary
The existing OPC model cannot accurately consider the impact of reflected light from the underlying structure, resulting in a large deviation between the lithographic graphics and the expected graphics, affecting the accuracy and reliability of the lithographic process.
A three-dimensional OPC model based on ray tracing algorithm is constructed, combined with the underlying three-dimensional data and material optical properties parameters, and parameter fitting is performed through differential genetic algorithm and gradient descent algorithm to construct a bottom visual three-dimensional OPC model to predict the target lithography graphics for the mask requirements.
It improves the prediction accuracy of lithographic graphics, ensures that the graphics after lithography develops are consistent with the design goals, improves product yield, and reduces process R&D costs and time.
Smart Images
Figure CN120315239A_ABST
Abstract
Description
Technical Field
[0001] This application relates to, but is not limited to, the field of semiconductor technology, and particularly relates to a lithography pattern prediction method based on an OPC model with visible underlying three-dimensional structure. Background Art
[0002] The pattern distortion caused by the interference and diffraction effects of the laser light source passing through the mask in the lithography process cannot be ignored. OPC builds a lithography model through simulation, and then uses software algorithms to correct the mask and the light source, thus offsetting the interference and diffraction effects when the laser light source passes through the mask. However, the existing OPC models can only consider the interference and diffraction behaviors between the patterns of the current layer, and cannot simulate the reflected light from the underlying structure (especially the underlying structure with complex geometry), so naturally it is impossible to accurately correct the influence of the underlying structure on the exposure result by correcting the photomask in advance, resulting in a large deviation between the final lithography pattern and the expected pattern, affecting the accuracy and reliability of the lithography process. Summary of the Invention
[0003] An embodiment of this application provides a lithography pattern prediction method based on an OPC model with visible underlying three-dimensional structure, constructs a three-dimensional OPC model with visible underlying layer based on the ray tracing algorithm, takes into account the influence of the underlying structure of the lithography pattern, and improves the prediction accuracy of the lithography pattern.
[0004] In a first aspect, an embodiment of this application provides a lithography pattern prediction method based on an OPC model with visible underlying three-dimensional structure, including:
[0005] Obtain the first wafer data, lithography process parameters, and photomask data corresponding to the target wafer, where the surface of the target wafer is coated with a target photoresist, and the first wafer data is wafer data without underlying effects;
[0006] Calculate the first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm in combination with the lithography process parameters and the photomask data;
[0007] Construct a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information;
[0008] Obtain the underlying three-dimensional data and underlying material optical property parameters of the target wafer, and construct a three-dimensional OPC model based on the ray tracing algorithm in combination with the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model;
[0009] Obtain the photomask requirement information, and use the three-dimensional OPC model to predict the target lithography pattern that meets the photomask requirement.
[0010] In some embodiments, constructing a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information includes:
[0011] Calling a differential genetic algorithm and a gradient descent algorithm through OPC software;
[0012] Using the differential genetic algorithm and the gradient descent algorithm to perform parameter fitting of chemical effects on the first wafer data and the first light intensity distribution information, and constructing the two-dimensional OPC model.
[0013] In some embodiments, constructing a three-dimensional OPC model based on a ray tracing algorithm, in combination with the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model includes:
[0014] Based on the ray tracing algorithm, calculating second light intensity distribution information including underlying effects inside the target photoresist in combination with the simulation results of the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model;
[0015] Obtaining second wafer data, where the second wafer data is wafer data including underlying effects;
[0016] Precisely fitting the second wafer data and the second light intensity distribution information through a differential genetic algorithm and a gradient descent algorithm to construct a three-dimensional OPC model.
[0017] In some embodiments, after constructing the three-dimensional OPC model based on the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model, the method further includes:
[0018] Obtaining real wafer data, where the real wafer data includes a reference lithography pattern, and the reference lithography pattern is a lithography pattern actually fabricated on the production line corresponding to the reticle requirement information;
[0019] Comparing the error between the reference lithography pattern and the target lithography pattern to obtain an error value;
[0020] When the error value does not belong to a preset error range, inputting the real wafer data into the OPC software to optimize the three-dimensional OPC model through the OPC software until the error value obtained based on the reticle requirement information of the optimized three-dimensional OPC model belongs to the preset error range.
[0021] In a second aspect, an embodiment of the present application provides a lithography pattern prediction device based on an OPC model with visible underlying three-dimensional structures, including:
[0022] A first data acquisition unit, configured to acquire first wafer data, lithography process parameters, and reticle data corresponding to a target wafer, wherein a target photoresist is coated on the surface of the target wafer, and the first wafer data is wafer data without bottom layer effects;
[0023] A first light intensity distribution information calculation unit, configured to calculate first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm in combination with the lithography process parameters and the reticle data;
[0024] A two-dimensional OPC model construction unit, configured to construct a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information;
[0025] A three-dimensional OPC model construction unit, configured to acquire bottom layer three-dimensional data and bottom layer material optical property parameters of the target wafer, and based on a ray tracing algorithm, construct a three-dimensional OPC model in combination with the bottom layer three-dimensional data, the bottom layer material optical property parameters, and the two-dimensional OPC model;
[0026] A lithography pattern prediction unit, configured to acquire reticle requirement information, and use the three-dimensional OPC model to predict a target lithography pattern that meets the reticle requirement.
[0027] In some embodiments, the two-dimensional OPC model construction unit includes:
[0028] An algorithm call unit, configured to call a differential genetic algorithm and a gradient descent algorithm through OPC software;
[0029] A first parameter fitting unit, configured to perform parameter fitting of chemical effects on the first wafer data and the first light intensity distribution information by using the differential genetic algorithm and the gradient descent algorithm, and construct the two-dimensional OPC model.
[0030] In some embodiments, the three-dimensional OPC model construction unit includes:
[0031] A second light intensity distribution information calculation unit, configured to calculate second light intensity distribution information including bottom layer effects inside the target photoresist based on a ray tracing algorithm in combination with simulation results of the bottom layer three-dimensional data, the bottom layer material optical property parameters, and the two-dimensional OPC model;
[0032] A second data acquisition unit, configured to acquire second wafer data, where the second wafer data is wafer data including bottom layer effects;
[0033] A second parameter fitting unit, configured to perform precise fitting on the second wafer data and the second light intensity distribution information by using a differential genetic algorithm and a gradient descent algorithm, and construct the three-dimensional OPC model.
[0034] In some embodiments, the lithography pattern prediction device based on the OPC model visible to the underlying three-dimensional structure of this embodiment further includes:
[0035] A third data acquisition unit, configured to acquire real wafer data, where the real wafer data includes a reference lithography pattern, and the reference lithography pattern is a lithography pattern actually produced on the production line corresponding to the reticle requirement information;
[0036] An error comparison unit, configured to compare the reference lithography pattern with the target lithography pattern to obtain an error value;
[0037] A model optimization unit, configured to, when the error value does not belong to a preset error range, input the real wafer data into the OPC software to optimize the three-dimensional OPC model through the OPC software until the error value obtained by the optimized three-dimensional OPC model based on the reticle requirement information belongs to the preset error range.
[0038] In a third aspect, an embodiment of the present application provides an electronic device, including at least one control processor and a memory communicatively connected to the at least one control processor; the memory stores instructions executable 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 pattern prediction method based on the OPC model visible to the underlying three-dimensional structure as described in the first aspect.
[0039] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, storing computer-executable instructions for executing the lithography pattern prediction method based on the OPC model visible to the underlying three-dimensional structure as described in the first aspect.
[0040] The embodiment of the present application provides a lithography pattern prediction method based on an OPC model with visible underlying three-dimensional structure. The method includes: obtaining first wafer data, lithography process parameters, and reticle data corresponding to a target wafer, where a target photoresist is coated on the surface of the target wafer, and the first wafer data is wafer data without underlying effects; calculating first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm in combination with the lithography process parameters and the reticle data; constructing a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information; obtaining the underlying three-dimensional data and underlying material optical property parameters of the target wafer, and constructing a three-dimensional OPC model based on the ray tracing algorithm in combination with the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model; obtaining reticle requirement information, and predicting a target lithography pattern that meets the reticle requirement information using the three-dimensional OPC model. According to the solution provided by the embodiment of the present application, a three-dimensional OPC model with visible underlying structure of the wafer is constructed based on the ray tracing algorithm, taking into account the influence of the underlying structure of the lithography pattern, and improving the prediction accuracy of the lithography pattern. Description of the Drawings
[0041] Figure 1 is a flowchart of the steps of the lithography pattern prediction method based on the OPC model with visible underlying three-dimensional structure provided by an embodiment of the present application;
[0042] Figure 2 is a schematic diagram of the modules of the lithography pattern prediction device based on the OPC model with visible underlying three-dimensional structure provided by another embodiment of the present application;
[0043] Figure 3 is a structural diagram of an electronic device provided by another embodiment of the present application. Detailed Embodiments
[0044] In order to make the objectives, technical solutions, and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0045] It can be understood that although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the device or the order in the flowchart. Terms such as "first" and "second" in the specification, claims, or the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to be used to describe a specific order or sequence.
[0046] The pattern distortion caused by the interference and diffraction effects of the laser light source passing through the mask in the lithography process cannot be ignored. Through simulation, OPC establishes a lithography model and then uses software algorithms to correct the mask and the light source, thus offsetting the interference and diffraction effects when the laser light source passes through the mask. However, the existing OPC models can only consider the interference and diffraction behaviors between the patterns of the current layer and cannot simulate the reflected light from the underlying structure (especially the underlying structure with complex geometry). Naturally, it is impossible to accurately correct the influence of the underlying structure on the exposure result by modifying the photomask in advance, resulting in a large deviation between the final lithography pattern and the expected pattern and affecting the accuracy and reliability of the lithography process.
[0047] To solve the above problems, the embodiments of the present application provide a method for predicting a lithography pattern based on an OPC model with visible underlying three-dimensional structure. The method includes: obtaining first wafer data, lithography process parameters, and mask data corresponding to a target wafer, where the surface of the target wafer is coated with a target photoresist, and the first wafer data is wafer data without underlying effects; calculating first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm in combination with the lithography process parameters and the mask data; constructing a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information; obtaining the underlying three-dimensional data and underlying material optical property parameters of the target wafer, and constructing a three-dimensional OPC model based on the ray tracing algorithm in combination with the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model; obtaining mask requirement information and predicting a target lithography pattern that meets the mask requirement using the three-dimensional OPC model. According to the solution provided by the embodiments of the present application, a three-dimensional OPC model with visible underlying structure of the wafer is constructed based on the ray tracing algorithm, taking into account the influence of the underlying structure of the lithography pattern and improving the prediction accuracy of the lithography pattern.
[0048] The following further elaborates on the embodiments of the present application in conjunction with the accompanying drawings.
[0049] Reference Figure 1 , Figure 1 is a flowchart of the steps of a method for predicting a lithography pattern based on an OPC model with visible underlying three-dimensional structure provided by an embodiment of the present application. The embodiments of the present application provide a method for predicting a lithography pattern based on an OPC model with visible underlying three-dimensional structure, and the method includes but is not limited to the following steps:
[0050] Step S10, obtaining first wafer data, lithography process parameters, and mask data corresponding to a target wafer, where the surface of the target wafer is coated with a target photoresist, and the first wafer data is wafer data without underlying effects.
[0051] Specifically, the first wafer data, lithography process parameters, and reticle data in this embodiment are actual measurement data for the target wafer, which serve as the modeling data for the subsequent two-dimensional OPC model. The steps of obtaining these data ensure that the physical information related to the lithography process for the target wafer is accurately captured, providing an effective data basis for subsequent model construction and obtaining accurate lithography patterns.
[0052] Step S20: Calculate the first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm, in combination with the lithography process parameters and reticle data.
[0053] Specifically, the optical imaging algorithm in this embodiment is Abbe's optical imaging theory.
[0054] Specifically, the way this embodiment executes step S20 is to input the first wafer data, lithography process parameters, and reticle data obtained in step S10 into the OPC software. Then, the OPC software calls the optical imaging algorithm corresponding to Abbe's optical imaging theory, combines the input lithography process parameters and reticle data, and calculates the first light intensity distribution information inside the target photoresist, providing an effective data basis for constructing the two-dimensional OPC model.
[0055] Step S30: Construct a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information.
[0056] Specifically, in some embodiments, Figure 1 Step S30 includes but is not limited to the following steps:
[0057] Step S31: Call the differential genetic algorithm and the gradient descent algorithm through the OPC software;
[0058] Step S32: Use the differential genetic algorithm and the gradient descent algorithm to perform parameter fitting of chemical effects on the first wafer data and the first light intensity distribution information, and construct a two-dimensional OPC model.
[0059] It can be understood that after executing step S30, this embodiment calls the differential genetic algorithm and the gradient descent algorithm through the OPC software to perform parameter fitting of chemical effects on the first wafer data without the bottom layer effect, thereby constructing a high-precision two-dimensional OPC model to provide an effective basis for subsequent construction of the three-dimensional OPC model.
[0060] Step S40: Obtain the bottom layer three-dimensional data and the bottom layer material optical property parameters of the target wafer, and construct a three-dimensional OPC model based on the ray tracing algorithm, in combination with the bottom layer three-dimensional data, the bottom layer material optical property parameters, and the two-dimensional OPC model.
[0061] Specifically, in some embodiments, Figure 1The construction of the 3D OPC model based on the underlying 3D data, the optical property parameters of the underlying material, and the 2D OPC model in step S40 includes, but is not limited to, the following steps:
[0062] Step S41, based on the ray tracing algorithm, calculate the second light intensity distribution information including the underlying effect inside the target photoresist by combining the underlying 3D data, the optical property parameters of the underlying material, and the simulation results of the 2D OPC model;
[0063] Step S42, obtain the second wafer data, where the second wafer data is the wafer data including the underlying effect;
[0064] Step S43, perform precise fitting on the second wafer data and the second light intensity distribution information through the differential genetic algorithm and the gradient descent algorithm to construct the 3D OPC model.
[0065] Specifically, the underlying 3D data in this embodiment is the topography information of the bottom layer of the target wafer. For example, it includes the 2D topography, thickness, and taper angle of the bottom layer of the target wafer. The optical property parameters of the underlying material include the optical absorption rate and refractive index corresponding to the bottom layer of the target wafer.
[0066] Specifically, the ray tracing algorithm in this embodiment can simulate the complex interaction behaviors of light in the real world, including reflection, refraction, shadow, and indirect illumination, etc. By using the ray tracing algorithm to process in combination with the underlying 3D data, the optical property parameters of the underlying material, and the simulation results of the 2D OPC model, the three-dimensional propagation process of light under and around the underlying layer can be accurately restored, and then the light intensity distribution inside the photoresist including the underlying effect, that is, the second light intensity distribution information, can be calculated, providing an effective data basis for constructing a high-precision 3D OPC model with visible underlying layer.
[0067] It can be understood that the 2D OPC model cannot achieve the dynamic simulation of the influence of the underlying layer on the pattern size of the photoresist after development. Based on this, in this embodiment, on the basis of the 2D OPC model, the underlying 3D data and the optical property parameters of the underlying material are used as the input data of the OPC software, and the ray tracing method is used to calculate the light intensity distribution information (that is, the second light intensity distribution information including the underlying effect) of the underlying material and the three-dimensional topography during the development process. Then, through the differential genetic algorithm and the gradient descent algorithm, precise fitting is performed on the second wafer data and the second light intensity distribution information to construct a 3D OPC model with visible underlying layer, realizing the accurate prediction of the lithography pattern affected by the underlying structure.
[0068] Step S50, obtain the mask requirement information, and use the 3D OPC model to predict the target lithography pattern that meets the mask requirement.
[0069] It can be understood that, compared with the limitations of the prior art that only relies on two-dimensional simulation and cannot comprehensively consider the influence of the reflected light of the underlying structure, in this embodiment, based on the two-dimensional OPC model, ray tracing technology is introduced to deeply integrate and analyze the underlying three-dimensional topography and material properties, and a three-dimensional OPC model with visible underlying layer is constructed. Through this three-dimensional OPC model, the influence of these factors on the pattern size after lithography and development of the current layer can be more accurately evaluated, and then a more precise mask correction scheme can be provided to ensure that the pattern after lithography and development is highly consistent with the design target, significantly improving the yield of the product. In addition, by reducing the repeated experiments and adjustments caused by pattern distortion, the cost and time investment in process research and development are effectively reduced.
[0070] Furthermore, after obtaining the target lithography pattern that meets the mask requirements, an OPC mask that meets the design requirements can be designed based on the target lithography pattern, and this OPC mask will be used in the actual lithography process to ensure the accuracy and quality of the final product.
[0071] In addition, in some embodiments, after performing Figure 1 the step S40 shown, the lithography pattern prediction method based on the OPC model with visible underlying three-dimensional structure provided by the embodiments of the present application includes but is not limited to the following steps:
[0072] Step S61, obtaining real wafer data, where the real wafer data includes a reference lithography pattern, and the reference lithography pattern is a lithography pattern corresponding to the mask requirement information actually produced on the production line;
[0073] Step S62, comparing the error between the reference lithography pattern and the target lithography pattern to obtain an error value;
[0074] Step S63, when the error value does not belong to the preset error range, inputting the real wafer data into the OPC software to optimize the three-dimensional OPC model through the OPC software until the error value obtained from the optimized three-dimensional OPC model based on the mask requirement information belongs to the preset error range.
[0075] It can be understood that after constructing the 3D OPC model, in order to verify the reliability and accuracy of the 3D OPC model, in this embodiment, the OPC wafer data actually produced on the production line, that is, the real wafer data, is compared with the model simulation data. The real wafer data includes the reference lithography pattern, and the reference lithography pattern is the lithography pattern actually produced on the production line corresponding to the reticle requirement information. In this embodiment, the comparison result between the reference lithography pattern and the target lithography pattern is used as the judgment index for the performance of the 3D OPC model. When the error value belongs to the preset error range, it indicates that the 3D OPC model constructed in this embodiment meets the standard and can be directly applied to the actual production of customer products; when the error value does not belong to the preset error range, it indicates that it has not met the standard. In this case, the real wafer data is input into the OPC software to iteratively optimize the 3D OPC model through the OPC software until the error value obtained by the optimized 3D OPC model based on the reticle requirement information belongs to the preset error range. That is to say, the optimization mechanism of the 3D OPC model provided in this embodiment ensures the reliability and accuracy of the 3D OPC model, thereby effectively ensuring the accuracy of predicting the size of the lithography pattern after developing the edge of the underlying device, and further improving the accuracy and reliability of the lithography process.
[0076] In addition, referring to Figure 2 , in some embodiments, this embodiment also discloses a lithography pattern prediction device based on an OPC model with visible underlying three-dimensional structure. The device includes:
[0077] A first data acquisition unit 210, configured to acquire first wafer data, lithography process parameters, and reticle data corresponding to a target wafer. Wherein, the surface of the target wafer is coated with a target photoresist, and the first wafer data is wafer data that does not include underlying effects;
[0078] A first light intensity distribution information calculation unit 220, configured to calculate first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm in combination with the lithography process parameters and the reticle data;
[0079] A two-dimensional OPC model construction unit 230, configured to construct a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information;
[0080] A three-dimensional OPC model construction unit 240, configured to acquire the underlying three-dimensional data and underlying material optical property parameters of the target wafer, and construct a three-dimensional OPC model based on the ray tracing algorithm in combination with the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model;
[0081] A lithography pattern prediction unit 250, configured to acquire reticle requirement information and predict a target lithography pattern that meets the reticle requirement information by using the three-dimensional OPC model.
[0082] Specifically, in some embodiments, the two-dimensional OPC model construction unit 230 includes:
[0083] An algorithm call unit 231, configured to call a differential genetic algorithm and a gradient descent algorithm through OPC software;
[0084] A first parameter fitting unit 232, configured to perform parameter fitting of chemical effects on the first wafer data and the first light intensity distribution information by using the differential genetic algorithm and the gradient descent algorithm, and construct a two-dimensional OPC model.
[0085] Specifically, in some embodiments, the three-dimensional OPC model construction unit 240 includes:
[0086] A second light intensity distribution information calculation unit 241, configured to calculate second light intensity distribution information including underlying effects inside a target photoresist based on a ray tracing algorithm, in combination with underlying three-dimensional data, underlying material optical property parameters, and simulation results of the two-dimensional OPC model;
[0087] A second data acquisition unit 242, configured to acquire second wafer data, where the second wafer data is wafer data including underlying effects;
[0088] A second parameter fitting unit 243, configured to perform precise fitting on the second wafer data and the second light intensity distribution information by using the differential genetic algorithm and the gradient descent algorithm, and construct a three-dimensional OPC model.
[0089] Specifically, in some embodiments, the lithography pattern prediction device of the OPC model visible based on the underlying three-dimensional structure in this embodiment further includes:
[0090] A third data acquisition unit 260, configured to acquire real wafer data, where the real wafer data includes a reference lithography pattern, and the reference lithography pattern is a lithography pattern actually fabricated on the production line corresponding to the reticle requirement information;
[0091] An error comparison unit 270, configured to compare the reference lithography pattern with the target lithography pattern to obtain an error value;
[0092] A model optimization unit 280, configured to, when the error value does not belong to a preset error range, input the real wafer data into the OPC software to perform optimization processing on the three-dimensional OPC model through the OPC software until the error value obtained based on the reticle requirement information by the optimized three-dimensional OPC model belongs to the preset error range.
[0093] It should be noted that the specific implementation of the lithography pattern prediction device based on the OPC model visible from the underlying three-dimensional structure is basically the same as the specific embodiments of the lithography pattern prediction method based on the OPC model visible from the underlying three-dimensional structure, and will not be elaborated here.
[0094] As Figure 3 shown, Figure 3 is a structural diagram of an electronic device provided by an embodiment of the present application. The present invention also provides a control device 300, including:
[0095] A processor 310, which can be implemented by using a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided by the embodiments of the present application;
[0096] A memory 320, which 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), etc. The memory 320 can store an operating system and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 320 and are called by the processor 310 to execute the XXX method of the embodiments of the present application;
[0097] An input / output interface 330, which is used to implement information input and output;
[0098] A communication interface 340, which is used to implement communication interaction between this device and other devices, and can implement communication through a wired method (such as USB, network cable, etc.) or through a wireless method (such as mobile network, WIFI, Bluetooth, etc.);
[0099] A bus 350, which transmits information between various components of the device (such as the processor 310, the memory 320, the input / output interface 330, and the communication interface 340);
[0100] Among them, the processor 310, the memory 320, the input / output interface 330, and the communication interface 340 are communicatively connected to each other inside the device through the bus 350.
[0101] In addition, an embodiment of the present application further provides a storage medium, which is a computer-readable storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned lithography pattern prediction method based on the OPC model visible in the underlying three-dimensional structure.
[0102] As a non-transitory computer-readable storage medium, a memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory, and can also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0103] Those of ordinary skill in the art can understand that all or some of the steps and systems in the methods 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 can be implemented as hardware, or can be implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include but are not limited to RAM, ROM, EEPROM, flash memory, or other memory technologies, CD-ROM, digital versatile disk (DVD), or other optical disk storage, magnetic cassette, tape, magnetic disk storage, or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, a communication medium generally includes computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.
[0104] The above is a specific description of the preferred embodiment of the present invention. However, the present invention is not limited to the above-mentioned embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without violating the spirit of the present invention. These equivalent deformations or substitutions are all included within the scope defined by the claims of the present invention.
Claims
1. A lithography pattern prediction method based on an OPC model with visible underlying three-dimensional structure, characterized in that, Including: Obtain the first wafer data, lithography process parameters, and reticle data corresponding to the target wafer. Wherein, the surface of the target wafer is coated with a target photoresist, and the first wafer data is wafer data without bottom layer effects; Calculate the first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm in combination with the lithography process parameters and the reticle data; Construct a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information; Obtain the three-dimensional data of the bottom layer of the target wafer and the optical property parameters of the bottom layer material. Based on the ray tracing algorithm, construct a three-dimensional OPC model in combination with the three-dimensional data of the bottom layer, the optical property parameters of the bottom layer material, and the two-dimensional OPC model; Obtain the reticle requirement information, and use the three-dimensional OPC model to predict the target lithography pattern that meets the reticle requirement information.
2. The lithography pattern prediction method for an OPC model with visible underlying three-dimensional structure according to claim 1, wherein Constructing a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information includes: Call the differential genetic algorithm and the gradient descent algorithm through OPC software; Use the differential genetic algorithm and the gradient descent algorithm to perform parameter fitting of chemical effects on the first wafer data and the first light intensity distribution information, and construct the two-dimensional OPC model.
3. The lithography pattern prediction method for an OPC model based on the visibility of the underlying three-dimensional structure according to claim 1, wherein, Constructing a three-dimensional OPC model based on the ray tracing algorithm in combination with the three-dimensional data of the bottom layer, the optical property parameters of the bottom layer material, and the two-dimensional OPC model includes: Based on the ray tracing algorithm, calculate the second light intensity distribution information including bottom layer effects inside the target photoresist in combination with the simulation results of the three-dimensional data of the bottom layer, the optical property parameters of the bottom layer material, and the two-dimensional OPC model; Obtain the second wafer data, and the second wafer data is wafer data including bottom layer effects; Perform precise fitting on the second wafer data and the second light intensity distribution information through the differential genetic algorithm and the gradient descent algorithm, and construct the three-dimensional OPC model.
4. The lithography pattern prediction method for the OPC model based on the visibility of the underlying three-dimensional structure according to claim 1, wherein, After constructing the three-dimensional OPC model based on the three-dimensional data of the bottom layer, the optical property parameters of the bottom layer material, and the two-dimensional OPC model, the method further includes: Obtain the real wafer data, and the real wafer data includes a reference lithography pattern, and the reference lithography pattern is a lithography pattern corresponding to the reticle requirement information actually manufactured on the production line; Compare the error between the reference lithography pattern and the target lithography pattern to obtain an error value; When the error value does not belong to a preset error range, input the real wafer data into the OPC software to optimize the three-dimensional OPC model through the OPC software until the error value obtained by the optimized three-dimensional OPC model based on the reticle requirement information belongs to the preset error range.
5. A lithography pattern prediction device based on an OPC model with visible underlying three-dimensional structure, characterized in that, Including: The first data acquisition unit is used to obtain the first wafer data, lithography process parameters, and reticle data corresponding to the target wafer. Wherein, the surface of the target wafer is coated with a target photoresist, and the first wafer data is wafer data without bottom layer effects; A first light intensity distribution information calculation unit, configured to calculate first light intensity distribution information inside the target photoresist based on a preset optical imaging algorithm in combination with the lithography process parameters and the reticle data; A two-dimensional OPC model construction unit, configured to construct a two-dimensional OPC model based on the first wafer data and the first light intensity distribution information; A three-dimensional OPC model construction unit, configured to obtain underlying three-dimensional data of the target wafer and underlying material optical property parameters, and based on a ray tracing algorithm, construct a three-dimensional OPC model in combination with the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model; A lithography pattern prediction unit, configured to obtain reticle requirement information and predict a target lithography pattern that meets the reticle requirement information by using the three-dimensional OPC model.
6. The lithography pattern prediction device based on the OPC model with visible underlying three-dimensional structure according to claim 5, wherein, The two-dimensional OPC model construction unit includes: An algorithm call unit, configured to call a differential genetic algorithm and a gradient descent algorithm through OPC software; A first parameter fitting unit, configured to perform parameter fitting of chemical effects on the first wafer data and the first light intensity distribution information by using the differential genetic algorithm and the gradient descent algorithm, and construct the two-dimensional OPC model.
7. The lithography pattern prediction apparatus for an OPC model with visible underlying three-dimensional structure according to claim 5, wherein The three-dimensional OPC model construction unit includes: A second light intensity distribution information calculation unit, configured to calculate second light intensity distribution information including underlying effects inside the target photoresist based on a ray tracing algorithm in combination with simulation results of the underlying three-dimensional data, the underlying material optical property parameters, and the two-dimensional OPC model; A second data acquisition unit, configured to acquire second wafer data, where the second wafer data is wafer data including underlying effects; A second parameter fitting unit, configured to perform precise fitting on the second wafer data and the second light intensity distribution information by using a differential genetic algorithm and a gradient descent algorithm, and construct a three-dimensional OPC model.
8. The lithography pattern prediction device based on the OPC model with visible underlying three-dimensional structure according to claim 5, characterized in that, It further includes: A third data acquisition unit, configured to acquire real wafer data, where the real wafer data includes a reference lithography pattern, and the reference lithography pattern is a lithography pattern corresponding to the reticle requirement information actually fabricated on the production line; An error comparison unit, configured to compare the reference lithography pattern with the target lithography pattern to obtain an error value; A model optimization unit, configured to, when the error value does not belong to a preset error range, input the real wafer data into the OPC software to optimize the three-dimensional OPC model through the OPC software until the error value obtained by the optimized three-dimensional OPC model based on the reticle requirement information belongs to the preset error range.
9. An electronic device, characterized in that, It includes at least one control processor and a memory for communicatively connecting with the at least one control processor; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the lithography pattern prediction method of the OPC model visible based on the underlying three-dimensional structure according to 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 for causing a computer to execute the lithography pattern prediction method of the OPC model visible based on the underlying three-dimensional structure according to any one of claims 1 to 4.