OPC Model Optimization Method

Abstract

This application relates to the field of semiconductor integrated circuit manufacturing technology, and specifically relates to a method for determining an initial optical proximity effect model. The method includes: obtaining a mask correction data file and photoresist information of a photoresist layer covering a specific layer of a semiconductor; generating several groups of optical models based on the photoresist information; through each group of optical models, performing simulated exposure on dense patterns in the mask correction data file on the photoresist layer to obtain several groups of imaging light intensity distribution maps corresponding to each group of optical models; determining the best imaging light intensity distribution map in each group of imaging light intensity distribution maps; based on the best imaging light intensity distribution map in each group of optical models, determining the preferred optical model corresponding to the best imaging light intensity distribution map in each group of optical models; generating an OPC model based on each preferred optical model and the mask correction data file; respectively calculating the evaluation parameters of each OPC optimization model, and determining the OPC optimization model with the optimal evaluation parameters as the optimal OPC model.

Description

Technical Field

[0001] This application relates to the field of semiconductor integrated circuit manufacturing technology, and particularly relates to a method for determining an initial optical proximity effect model. Background Art

[0002] In the field of semiconductor integrated circuit manufacturing, with the continuous development of technology, the shape of the light source used in lithography projection exposure is also constantly changing, experiencing a rapid development from on-axis illumination to off-axis illumination, and from circular light sources to annular light sources. When the semiconductor technology node enters below 28nm, the conventional illumination light source shape can no longer meet the requirements of advanced exposure technology. Different chip design rules require closely related illumination light source shapes. Based on this, the world's major OPC (Optical Proximity Correction) software suppliers have developed a new technology - SMO technology (Source Mask Optimization), which can determine whether each pixel point on the light source is lit, thus enabling the complete liberalization of the shape of the illumination light source.

[0003] In related technologies, the necessary inputs for SMO technology include: mask data and an initial optical proximity correction model. Among them, the mask data includes dense patterns and ordinary patterns, and the dense patterns have different requirements for the process window of the lithography system compared to ordinary patterns. Therefore, it is necessary to take into account both dense patterns and ordinary patterns to select the most suitable optical model to establish the optimal initial optical proximity correction model.

[0004] However, in related technologies, the selection of the most suitable optical model is usually ignored, and the optimal initial optical proximity correction model is established, which is not conducive to improving the efficiency of SMO technology. Summary of the Invention

[0005] This application provides an OPC model optimization method, which can solve the problem in related technologies that the selection of the most suitable optical model is ignored, and the optimal initial optical proximity correction model is established, which is not conducive to improving the efficiency of SMO technology.

[0006] To solve the technical problems described in the background art, this application provides an OPC model optimization method. The optimization of the OPC initial model includes:

[0007] Step S1: Obtain a mask correction data file corresponding to a specific layer of a semiconductor device, and photoresist information of a photoresist layer covering the specific layer of the semiconductor;

[0008] Step S2: Generate several groups of optical models according to the photoresist information, and each group of optical models includes multiple optical models;

[0009] Step S3: Through each group of optical models, perform simulated exposure on the dense patterns in the mask correction data file on the photoresist layer to obtain a plurality of imaging light intensity distribution maps corresponding to each group of optical models; each group of imaging light intensity distribution maps includes multiple imaging light intensity distribution maps;

[0010] Step S4: Determine the optimal imaging light intensity distribution map in each group of imaging light intensity distribution maps;

[0011] Step S5: Based on the optimal imaging light intensity distribution map in each group of optical models, determine the preferred optical model corresponding to the optimal imaging light intensity distribution map in each group of optical models;

[0012] Step S6: Generate an OPC model based on each preferred optical model and the mask correction data file;

[0013] Step S7: Calculate the evaluation parameters of each of the OPC optimized models respectively, and determine the OPC optimized model with the optimal evaluation parameters as the optimal OPC model.

[0014] Optionally, the step S1: The step of obtaining the mask correction data file corresponding to a specific layer of the semiconductor device includes:

[0015] Step S11: Obtain the mask initial data file and the initial optical model;

[0016] Step S12: Based on the initial optical model and the mask initial data file, perform simulated exposure on the photoresist layer on the specific layer of the semiconductor device to obtain exposure pattern data;

[0017] Step S13: Generate an OPC initial model based on the exposure pattern data;

[0018] Step S14: Correct the mask initial data file through the OPC initial model to obtain the mask correction data file corresponding to a specific layer of the semiconductor device.

[0019] Optionally, the step S11: The step of obtaining the mask initial data file includes:

[0020] Step S111: Predesign the target pattern of the specific layer of the semiconductor device according to the design rules;

[0021] Step S112: Generate the mask initial data file based on the target pattern.

[0022] Optionally, the step S11: The step of obtaining the initial optical model includes:

[0023] Step S121: Determine the defocus range and the projection position range according to the photoresist information;

[0024] Step S122: Select an initial defocus amount from the defocus range and select an initial projection position from the projection position range;

[0025] Step S123: Use the initial defocus amount and the initial projection position as a pair of initial optical parameters;

[0026] Step S124: Generate an initial optical model based on the initial optical parameters.

[0027] Optionally, the photoresist information includes the depth information of the photoresist;

[0028] The step S2: Generate a number of groups of optical models according to the photoresist information, and each group of optical models includes a plurality of optical models, including:

[0029] Step S21: Determine the defocus range and the projection position range based on the depth information in the photoresist information; both the defocus range and the projection position range are within the depth range of the photoresist;

[0030] Step S22: Combine any defocus amount in the defocus range with each projection position in the projection position range to form a number of pairs of optical parameters, and the number of pairs of optical parameters corresponding to the defocus amount is a group of optical parameters;

[0031] Step S23: Traverse all defocus amounts in the defocus range to form multiple groups of optical parameters;

[0032] Step S24: Generate a plurality of optical models corresponding to each pair of optical parameters based on each pair of optical parameters in a group of optical parameters, and the plurality of optical models corresponding to a group of optical parameters is a group of optical models;

[0033] Step S25: Traverse all groups of optical parameters to form a number of groups of optical models corresponding to each group of optical parameters.

[0034] Optionally, the defocus range includes a number of defocus values, and the projection position range includes a number of projection ranges;

[0035] The step S22: Combine any defocus amount in the defocus range with each projection position in the projection position range to form a number of pairs of optical parameters, and the number of pairs of optical parameters corresponding to the defocus amount is a group of optical parameters; step, including:

[0036] Obtain the first defocus amount L1 in the defocus range and each projection position D1, D2, D3... Dn in the projection position range;

[0037] Combining the first defocus amount L1 with each projection position D1, D2... Dn in the projection position range to form several pairs of optical parameters L1D1, L1D2, L1D3... L1Dn, and the several pairs of optical parameters L1D1, L1D2, L1D3... L1Dn corresponding to the first defocus amount L1 are the first set of optical parameters L1D.

[0038] Optionally, in step S24: Based on each pair of optical parameters in a set of optical parameters, generating multiple optical models corresponding to each pair of optical parameters, and the multiple optical models corresponding to a set of optical parameters being a set of optical models, includes:

[0039] Obtaining several pairs of optical parameters L1D1, L1D2, L1D3... L1Dn of the first set of optical parameters L1D;

[0040] Based on each pair of optical parameters L1D1, L1D2, L1D3... L1Dn of the first set of optical parameters L1D, generating multiple optical models Model11, Model12, Model13... Model1n corresponding to each pair of optical parameters L1D1, L1D2, L1D3... L1Dn, and the optical models Model11, Model12, Model13... Model1n corresponding to the first set of optical parameters L1D are the first set of optical models M1.

[0041] Optionally, in step S3: Passing each set of optical models to simulate the exposure of the dense patterns in the mask correction data file on the photoresist layer to obtain several sets of imaging light intensity distribution maps corresponding to each set of optical models; each set of imaging light intensity distribution maps including multiple imaging light intensity distribution maps, includes:

[0042] Obtaining all the optical models Model11, Model12, 3Model11... Model1n in the first set of optical models M1;

[0043] Causing each optical model Model11, Model12, Model13... Model1n to respectively simulate the exposure of the dense patterns in the mask correction data file on the photoresist layer to obtain several imaging light intensity distribution maps x11, x12, x13... x1n corresponding to the first set of optical models M1, and the several imaging light intensity distribution maps x11, x12, x13... x1n are the first set of light intensity distribution maps X[1];

[0044] Traversing all the optical models in each set of optical models, and passing each of the optical models to simulate the exposure of the dense patterns in the mask correction data file on the photoresist layer to obtain several sets of imaging light intensity distribution maps X[1], [2], X[3]... X[m] corresponding to each set of optical models.

[0045] The technical solution of this application has at least the following advantages: By establishing several groups of optical models, the dense patterns in the reticle correction data file are simulated and exposed on the photoresist layer to select the optical model that can form the best imaging light intensity distribution diagram in each group of optical models as the preferred optical model, and based on this preferred optical model, the corresponding OPC optimization model is generated. Finally, the optimal OPC model is selected in the OPC optimization model. This solution can accurately determine the optimal OPC model, laying a foundation for enabling this optimal OPC model and performing SMO technology (Source Mask Optimization) to improve the SMO efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific embodiments of this application or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0047] Figure 1 Shows the flowchart of the OPC model optimization method provided by an embodiment of this application;

[0048] Figure 1a Shows a schematic cross-sectional structure diagram of a semiconductor device with a photoresist layer formed on a specific layer;

[0049] Figure 2 Shows several groups of optical model schematic diagrams generated according to the photoresist information in step S2;

[0050] Figure 2a Shows a schematic diagram of the projection position range along the depth direction of the photoresist layer;

[0051] Figure 2b Shows a schematic diagram of the defocus range along the depth direction of the photoresist layer;

[0052] Figure 2c Shows based on Figure 2a the projection position range shown and Figure 2b the defocus range shown, a schematic diagram of multiple groups of optical parameters determined;

[0053] Figure 2d Shows based on Figure 2c the schematic diagram of multiple groups of optical parameters shown, a schematic diagram of several groups of optical models corresponding to each group of optical parameters determined;

[0054] Figure 3Shows several schematic diagrams of the imaging light intensity distribution maps corresponding to each group of optical models generated in step S3;

[0055] Figure 4 Shows based on Figure 3 The several schematic diagrams of the imaging light intensity distribution maps shown;

[0056] Figure 5 Shows based on Figure 4 The best imaging light intensity distribution map shown, and selects the schematic diagrams of the preferred optical models in each group of optical models;

[0057] Figure 6 Shows based on Figure 5 The preferred optical models selected from each group of optical models, and generates a schematic diagram of the OPC optimization model. Detailed implementation manners

[0058] Next, the technical solutions in the present application will be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without making creative efforts belong to the scope of protection of the present application.

[0059] In the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation to the present application. In addition, the terms "first", "second", "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0060] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and can also be the communication inside two elements. It can be a wireless connection or a wired connection. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific situations.

[0061] In addition, the technical features involved in different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0062] Figure 1The figure shows a flowchart of an OPC model optimization method provided by an embodiment of the present application. Referring to Figure 1 , the OPC model optimization method includes the following steps S1 to S7 carried out in sequence:

[0063] Step S1: Obtain a mask correction data file corresponding to a specific layer of a semiconductor device and photoresist information of a photoresist layer covering the specific layer of the semiconductor.

[0064] Referring to Figure 1a , it shows a schematic cross-sectional structure diagram of a semiconductor device with a photoresist layer formed on a specific layer. It can be seen from Figure 1a that a photoresist layer 102 is formed on the specific layer 101 of the semiconductor device 100. Optionally, the photoresist layer 102 includes a photoresist layer and a top anti-reflection layer covering the photoresist layer.

[0065] Step S2: Generate a number of groups of optical models according to the photoresist information, and each group of optical models includes a plurality of optical models.

[0066] Referring to Figure 2 , it shows a schematic diagram of a number of groups of optical models generated according to the photoresist information in step S2. It can be seen from Figure 2 that a number of groups of optical models M1, M2, M3... Mm including a first group of optical models M1, a second group of optical models M2, a third group of optical models M3... an mth group of optical models Mm are generated according to the photoresist information, and each group of optical models includes a plurality of optical models.

[0067] Taking the first group of optical models M1 and the mth group of optical models Mm as an example, it can be seen from Figure 2 that the first group of optical models M1 includes a plurality of optical models Model11, Model12, Model13... Model1n, and the mth group of optical models Mm includes a plurality of optical models Modelm1, Modelm2, Modelm3... Modelmn.

[0068] Step S3: Through each group of optical models, perform simulated exposure on the dense patterns in the mask correction data file on the photoresist layer to obtain a number of groups of imaging light intensity distribution diagrams corresponding to each group of optical models; each group of imaging light intensity distribution diagrams includes a plurality of imaging light intensity distribution diagrams.

[0069] Referring to Figure 3 , it shows a schematic diagram of a number of groups of imaging light intensity distribution diagrams corresponding to each group of optical models generated in step S3. It can be seen from Figure 3It can be seen that based on the first set of optical models M1, the first set of imaging light intensity distribution maps X[1] can be obtained. Based on the second set of optical models M2, the second set of imaging light intensity distribution maps X[2] can be obtained. Based on the third set of optical models M3, the third set of imaging light intensity distribution maps X[3]... Based on the m-th set of optical models Mm, the m-th set of imaging light intensity distribution maps X[m] can be obtained. Each set of imaging light intensity distribution maps includes multiple imaging light intensity distribution maps. Each imaging light intensity distribution map in a set of imaging light intensity distribution maps corresponds one-to-one with each optical model in its corresponding set of optical models.

[0070] Taking the first set of imaging light intensity distribution maps X[1] as an example, from Figure 3 it can be seen that the first set of imaging light intensity distribution maps X[1] includes multiple imaging light intensity distribution maps x11, x12, x13... x1n. The imaging light intensity distribution map x11 is formed based on the optical model Model11 in the first set of optical models M1... The imaging light intensity distribution map x1n is formed based on the optical model Model1n in the first set of optical models M1.

[0071] Taking the m-th set of imaging light intensity distribution maps X[m] as an example, from Figure 3 it can be seen that the m-th set of imaging light intensity distribution maps X[m] includes multiple imaging light intensity distribution maps xm1, xm2, xm3... xmn. The imaging light intensity distribution map xm1 is formed based on the optical model Modelm1 in the m-th set of optical models Mm... The imaging light intensity distribution map xmn is formed based on the optical model Modelmn in the m-th set of optical models Mm.

[0072] Step S4: Determine the best imaging light intensity distribution map in each set of imaging light intensity distribution maps.

[0073] Optionally, an imaging light intensity distribution map that satisfies the symmetry condition can be selected as the best imaging light intensity distribution map. It should be noted that if the imaging light intensity distribution map satisfies the symmetry condition, the exposure of dense patterns can meet the required exposure process window.

[0074] Referring to Figure 4 , which shows the schematic diagrams of several sets of imaging light intensity distribution maps based on Figure 3 shown, to complete step S4, the schematic diagram of determining the best imaging light intensity distribution map in each set of imaging light intensity distribution maps.

[0075] From Figure 4It can be seen that the imaging intensity distribution map x12 in the first set of imaging intensity distribution maps X[1] is the best imaging intensity distribution map in the first set of imaging intensity distribution maps X[1]; the imaging intensity distribution map x23 in the second set of imaging intensity distribution maps X[2] is the best imaging intensity distribution map in the second set of imaging intensity distribution maps X[2]; the imaging intensity distribution map x33 in the third set of imaging intensity distribution maps X[3] is the best imaging intensity distribution map in the third set of imaging intensity distribution maps X[3]; the imaging intensity distribution map xmn in the m-th set of imaging intensity distribution maps X[m] is the best imaging intensity distribution map in the m-th set of imaging intensity distribution maps X[m].

[0076] Step S5: Based on the best imaging intensity distribution maps in each group of optical models, determine the preferred optical models corresponding to the best imaging intensity distribution maps in each group of optical models.

[0077] Referring to Figure 5 , which shows the schematic diagrams of the preferred optical models selected from each group of optical models based on the best imaging intensity distribution maps shown in Figure 4 .

[0078] From Figure 5 it can be seen that the imaging intensity distribution map x12 is the best imaging intensity distribution map in the first set of imaging intensity distribution maps X[1], and the imaging intensity distribution map x12 corresponds to the optical model Model12 in the first group of optical models M1. Therefore, the optical model Model12 is used as the preferred optical model in the first group of optical models M1.

[0079] The imaging intensity distribution map x23 is the best imaging intensity distribution map in the second set of imaging intensity distribution maps X[2], and the imaging intensity distribution map x23 corresponds to the optical model Model23 in the second group of optical models M2. Therefore, the optical model Model23 is used as the preferred optical model in the second group of optical models M2.

[0080] The imaging intensity distribution map x33 is the best imaging intensity distribution map in the third set of imaging intensity distribution maps X[3], and the imaging intensity distribution map x33 corresponds to the optical model Model33 in the third group of optical models M3. Therefore, the optical model Model33 is used as the preferred optical model in the third group of optical models M3.

[0081] The imaging intensity distribution map xmn is the best imaging intensity distribution map in the m-th set of imaging intensity distribution maps X[m], and the imaging intensity distribution map xmn corresponds to the optical model Modelmn in the m-th group of optical models Mm. Therefore, the optical model Modelmn is used as the preferred optical model in the m-th group of optical models Mm.

[0082] Step S6: Generate an OPC optimization model based on each preferred optical model and the mask template correction data file.

[0083] Refer to Figure 6 , which shows the preferred optical models among the selected groups of optical models based on Figure 5 to generate a schematic diagram of the OPC optimization model.

[0084] From Figure 6 it can be seen that based on the preferred optical model Model12 in the first group of optical models M1, the first OPC optimization model OPC1 can be generated; based on the preferred optical model Model23 in the second group of optical models M2, the second OPC optimization model OPC2 can be generated; based on the preferred optical model Model33 in the third group of optical models M3, the third OPC optimization model OPC3 can be generated... Based on the preferred optical model Modelmn in the mth group of optical models Mm, the mth OPC optimization model OPCm can be generated.

[0085] Step S7: Calculate the evaluation parameters of each of the OPC optimization models respectively, and determine the OPC optimization model with the optimal evaluation parameter as the optimal OPC model.

[0086] Calculate respectively Figure 6 the evaluation parameters of each of the OPC optimization models shown, and determine the OPC optimization model with the optimal evaluation parameter as the optimal OPC model.

[0087] In this embodiment, through a number of established groups of optical models, the dense patterns in the mask correction data file are simulated and exposed on the photoresist layer to select the optical model that can form the best imaging light intensity distribution diagram among the groups of optical models as the preferred optical model, and generate the corresponding OPC optimization model based on this preferred optical model. Finally, the optimal OPC model is selected from the OPC optimization models. This solution can accurately determine the optimal OPC model, laying a foundation for making this optimal OPC model and performing SMO technology (Source Mask Optimization) to improve the SMO efficiency.

[0088] In addition, in step S1: The step of obtaining the mask correction data file corresponding to a specific layer of the semiconductor device may include the following successive steps S11 to S14:

[0089] Step S11: Obtain the mask initial data file and the initial optical model;

[0090] The process of obtaining the mask initial data file includes: First, according to the design rules, pre-design the target pattern of the specific layer of the semiconductor device; then generate the mask initial data file based on the target pattern.

[0091] Step S12: Based on the initial optical model and the initial data file of the mask, perform simulated exposure on the photoresist layer on the specific layer of the semiconductor device to obtain exposure pattern data.

[0092] Step S13: Generate an initial OPC model based on the exposure pattern data.

[0093] Step S14: Correct the initial data file of the mask through the initial OPC model to obtain a corrected data file of the mask corresponding to the specific layer of the semiconductor device.

[0094] Among them, the step of obtaining the initial data file of the mask in step S11 includes the following steps S111 and S112 that are carried out in sequence:

[0095] S111: According to the design rules, pre-design the target pattern of the specific layer of the semiconductor device.

[0096] The design rules design the required functions of the specific layer and make the design of the required functions of the specific layer comply with the conventional integrated circuit specifications.

[0097] S112: Generate an initial data file of the mask based on the target pattern.

[0098] Among them, the step of obtaining the initial optical model in step S11 includes the following steps S121 to S124 that are carried out in sequence:

[0099] Step S121: Determine the defocus range and the projection position range according to the photoresist information;

[0100] Step S122: Select an initial defocus amount from the defocus range and select an initial projection position from the projection position range;

[0101] Step S123: Make the initial defocus amount and the initial projection position be a pair of initial optical parameters;

[0102] Step S124: Generate an initial optical model based on the initial optical parameters.

[0103] The initial data file of the mask is used to generate an initial mask pattern on the initial mask. The initial mask pattern is used to transfer the initial mask pattern to the photoresist layer when performing photolithographic exposure on the photoresist layer on the specific layer according to the initial mask.

[0104] Ideally, the exposure pattern formed after the initial mask pattern is transferred to the photoresist layer is consistent with the pre-designed target pattern.

[0105] However, since the light emitted by the lithography system undergoes optical proximity effects when passing through the initial mask, there is a deviation between the exposed pattern and the target pattern. Therefore, it is necessary to correct the mask data file through the OPC initial model so that the corrected mask correction data file can offset the optical proximity effects, thereby improving the consistency between the exposed pattern formed after the light emitted by the lithography system passes through the corrected mask correction data file and reaches the photoresist layer of the specific layer and the target pattern.

[0106] The optical parameters include some optical constant parameters such as the wavelength of the lithography machine, numerical aperture, photoresist layer parameters, and optical diameter that can be provided by the manufacturer or measured before lithography. The optical parameters of the lithography system also include optical adjustment parameters, and such optical adjustment parameters need to be selected based on the data actually measured after lithography and development. The above defocus amount and projection position are both optical adjustment parameters.

[0107] The optical constant parameters of a specific lithography system and a specific semiconductor node are usually unchanged, and the selection of optical adjustment parameters (defocus amount and projection position) has an important impact on whether the finally formed optimal OPC model can better balance dense patterns and initial mask patterns.

[0108] Therefore, for several groups of optical models in the above embodiments, a group of optical models is formed based on the same defocus amount, and the projection positions of the respective optical models in each group of optical models are different, and the defocus amounts of different groups of optical models are different. Among them, the photoresist information includes the depth information of the photoresist. Based on the photoresist with a specific depth, different groups of optical models can have different defocus ranges and projection position ranges, and both the defocus range and the projection position range are within the depth range of the photoresist.

[0109] Exemplarily, the above step S2: generating several groups of optical models according to the photoresist information, and each group of optical models includes multiple optical models, includes the following steps S21 to S25 that are carried out in sequence:

[0110] Step S21: Determine the defocus range and the projection position range based on the depth information in the photoresist information.

[0111] Taking Figure 1a the upper surface of the photoresist layer in as the origin of the photoresist depth, and the direction indicated by the arrow as the depth direction of the photoresist layer.

[0112] Referring to Figure 2a , which shows a schematic diagram of the projection position range along the depth direction of the photoresist layer. Exemplarily, Figure 2aThe total depth of the photoresist layer shown is 100 nm. Along the depth direction of the photoresist, that is, within the photoresist depth range of 0 nm to 100 nm, there is a projection position at every 5 nm step. A plurality of projection positions D1, D2, D3... Dn within the photoresist depth range of 0 nm to 100 nm form a projection position range D.

[0113] Refer to Figure 2b , which shows a schematic diagram of the defocus range along the depth direction of the photoresist layer. Exemplarily, Figure 2b The total depth of the photoresist layer shown is 100 nm. Along the depth direction of the photoresist, that is, within the photoresist depth range of 0 nm to 100 nm, a plurality of defocus amounts L1, L2, L3... Lm are formed, and the plurality of defocus amounts L1, L2, L3... Lm form a defocus range L.

[0114] Step S22: Make any defocus amount in the defocus range be respectively combined with each projection position in the projection position range to form several pairs of optical parameters. The several pairs of optical parameters corresponding to the defocus amount are a set of optical parameters.

[0115] Step S23: Traverse all the defocus amounts in the defocus range to form multiple sets of optical parameters.

[0116] Refer to Figure 2c , which shows a schematic diagram of multiple sets of optical parameters determined based on Figure 2a the projection position range shown and Figure 2b the defocus range shown.

[0117] From Figure 2c it can be seen that the number of sets of optical parameters corresponds to the number of defocus amounts in the defocus range. One defocus amount corresponds to one set of optical parameters.

[0118] Refer to Figure 2c , taking the formation of the first set of optical parameters L1D as an example.

[0119] The steps for forming the first set of optical parameters L1D include the following steps S221 to S222 carried out in sequence:

[0120] Step S221: Obtain the first defocus amount L1 in the defocus range L, and each projection position D1, D2, D3... Dn in the projection position range D.

[0121] Step S222: Make the first defocus amount L1 be respectively combined with each projection position D1, D2... Dn in the projection position range D to form several pairs of optical parameters L1D1, L1D2, L1D3... L1Dn. The several pairs of optical parameters L1D1, L1D2, L1D3... L1Dn corresponding to the first defocus amount L1 are the first set of optical parameters L1D.

[0122] The second set of optical parameters L2D, the third set of optical parameters L3D... the m-th set of optical parameters L1D are respectively formed by combining each projection position in the projection position range D with the second defocus amount L2, the third defocus amount L3... the m-th defocus amount Lm. The formation steps are the same as those of the first set of optical parameters L1D and will not be elaborated here.

[0123] Step S24: Based on each pair of optical parameters in a set of optical parameters, generate multiple optical models corresponding to each pair of optical parameters. The multiple optical models corresponding to a set of optical parameters are a set of optical models.

[0124] Step S25: Traverse all sets of optical parameters to form several sets of optical models corresponding to each set of optical parameters.

[0125] Refer to Figure 2d which shows a schematic diagram of multiple sets of optical parameters shown in Figure 2c to determine schematic diagrams of several sets of optical models corresponding to each set of optical parameters.

[0126] Taking the formation of the first set of optical models M1 as an example, the formation of the first set of optical models M1 includes the following steps S241 to S241 in sequence:

[0127] Step S241: Obtain several pairs of optical parameters L1D1, L1D2, L1D3... L1Dn of the first set of optical parameters L1D.

[0128] Step S242: Based on each pair of optical parameters L1D1, L1D2, L1D3... L1Dn of the first set of optical parameters L1D, generate multiple optical models Model11, Model12, Model13... Model1n corresponding to each pair of optical parameters L1D1, L1D2, L1D3... L1Dn. The optical models Model11, Model12, Model13... Model1n corresponding to the first set of optical parameters L1D are the first set of optical models M1.

[0129] The second set of optical models M2, the third set of optical models M3... the m-th set of optical models Mm are respectively formed corresponding to the second set of optical parameters L2D, the third set of optical parameters L3D... the m-th set of optical parameters L1D. The formation steps are the same as those of the first set of optical models M1 and will not be elaborated here.

[0130] Obviously, the above embodiments are only examples for clear illustration and not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or variations can be made based on the above description. It is not necessary and impossible to list all implementation manners here. And the obvious changes or variations derived therefrom are still within the protection scope of this application.

Claims

1. An OPC model optimization method, characterized in that, The OPC model optimization method includes: Step S1: Obtain a mask correction data file corresponding to a specific layer of a semiconductor device and photoresist information of a photoresist layer covering the specific layer of the semiconductor device, where the photoresist information includes depth information of the photoresist; Step S2: Generate several groups of optical models according to the photoresist information, and each group of optical models includes multiple optical models; Step S3: Through each group of optical models, perform simulated exposure on the dense patterns in the mask correction data file on the photoresist layer to obtain several groups of imaging light intensity distribution maps corresponding to each group of optical models; each group of imaging light intensity distribution maps includes multiple imaging light intensity distribution maps; Step S4: Determine the optimal imaging light intensity distribution map in each group of imaging light intensity distribution maps; Step S5: Based on the optimal imaging light intensity distribution map in each group of optical models, determine the preferred optical model corresponding to the optimal imaging light intensity distribution map in each group of optical models; Step S6: Generate an OPC optimization model based on each preferred optical model and the mask correction data file; Step S7: Calculate the evaluation parameters of each of the OPC optimization models respectively, and determine the OPC optimization model with the optimal evaluation parameters as the optimal OPC model.

2. The OPC model optimization method according to claim 1, characterized in that The step S1: The step of obtaining a mask correction data file corresponding to a specific layer of a semiconductor device includes: Step S11: Obtain a mask initial data file and an initial optical model; Step S12: Based on the initial optical model and the mask initial data file, perform simulated exposure on the photoresist layer on the specific layer of the semiconductor device to obtain exposure pattern data; Step S13: Generate an OPC initial model based on the exposure pattern data; Step S14: Correct the mask initial data file through the OPC initial model to obtain a mask correction data file corresponding to a specific layer of the semiconductor device.

3. The OPC model optimization method according to claim 2, wherein The step S11: The step of obtaining a mask initial data file includes: Step S111: Predesign the target pattern of the specific layer of the semiconductor device according to the design rules; Step S112: Generate a mask initial data file based on the target pattern.

4. The OPC model optimization method according to claim 2, wherein The step S11: The step of obtaining the initial optical model includes: Step S121: Determine the defocus range and projection position range according to the photoresist information; Step S122: Select an initial defocus amount from the defocus range and an initial projection position from the projection position range; Step S123: Use the initial defocus amount and the initial projection position as a pair of initial optical parameters; Step S124: Generate an initial optical model based on the initial optical parameters.

5. The OPC model optimization method according to claim 1, characterized in that The step S2: The step of generating several groups of optical models according to the photoresist information, and each group of optical models includes multiple optical models includes: Step S21: Determine the defocus range and projection position range based on the depth information in the photoresist information; both the defocus range and the projection position range are within the depth range of the photoresist; Step S22: Combine any defocus amount within the defocus range with each projection position within the projection position range to form a number of pairs of optical parameters. The number of pairs of optical parameters corresponding to the defocus amount forms a set of optical parameters. Step S23: Traverse all defocus amounts within the defocus range to form multiple sets of optical parameters. Step S24: Based on each pair of optical parameters in a set of optical parameters, generate multiple optical models corresponding to each pair of optical parameters. The multiple optical models corresponding to a set of optical parameters form a set of optical models. Step S25: Traverse all sets of optical parameters to form several sets of optical models corresponding to each set of optical parameters.

6. The OPC model optimization method according to claim 5, wherein, The defocus range includes several defocus values, and the projection position range includes several projection ranges. The step S22: Combine any defocus amount within the defocus range with each projection position within the projection position range to form a number of pairs of optical parameters. The number of pairs of optical parameters corresponding to the defocus amount forms a set of optical parameters. The step includes: Obtain the first defocus amount L1 within the defocus range and each projection position D1, D2, D3... Dn within the projection position range. Combine the first defocus amount L1 with each projection position D1, D2... Dn within the projection position range to form a number of pairs of optical parameters L1D1, L1D2, L1D3... L1Dn. The number of pairs of optical parameters L1D1, L1D2, L1D3... L1Dn corresponding to the first defocus amount L1 forms the first set of optical parameters L1D.

7. The OPC model optimization method according to claim 6, characterized in that, The step S24: Based on each pair of optical parameters in a set of optical parameters, generate multiple optical models corresponding to each pair of optical parameters. The multiple optical models corresponding to a set of optical parameters form a set of optical models. The step includes: Obtain the several pairs of optical parameters L1D1, L1D2, L1D3... L1Dn in the first set of optical parameters L1D. Based on each pair of optical parameters L1D1, L1D2, L1D3... L1Dn in the first set of optical parameters L1D, generate multiple optical models Model11, Model12, Model13... Model1n corresponding to each pair of optical parameters L1D1, L1D2, L1D3... L1Dn. The optical models Model11, Model12, Model13... Model1n corresponding to the first set of optical parameters L1D form the first set of optical models M1.

8. The OPC model optimization method according to claim 7, characterized in that The step S3: Use each set of optical models to correct the dense patterns in the mask correction data file and perform simulated exposure on the photoresist layer to obtain several sets of imaging light intensity distribution diagrams corresponding to each set of optical models. The step that each set of imaging light intensity distribution diagrams includes multiple imaging light intensity distribution diagrams includes: Obtain all the optical models Model11, Model12, Model13... Model1n in the first set of optical models M1. Cause each optical model Model11, Model12, Model13…Model1n to perform simulated exposure on the dense patterns in the reticle correction data file on the photoresist layer respectively, and obtain a number of imaging light intensity distribution maps x11, x12, x13…x1n corresponding to the first group of optical models M1. The number of imaging light intensity distribution maps x11, x12, x13…x1n are the first group of light intensity distribution maps X[1]; Traverse all the optical models in each group of optical models. Through each of the optical models, perform simulated exposure on the dense patterns in the reticle correction data file on the photoresist layer, and obtain a number of groups of imaging light intensity distribution maps X[1], [2], X[3]…X[m] corresponding to each group of optical models.

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