A negative developing photoresist model optimization method

Abstract

The application relates to the field of semiconductor technology, in particular to a negative developing photoresist model optimization method, which comprises the following steps: obtaining an initial negative developing photoresist model; based on the light field distribution in the initial negative developing photoresist model and the acid concentration in the photoresist, a distribution function S of the acid concentration in the photoresist based on the light field distribution is established; based on the distribution function S of the acid concentration in the photoresist, a concentration distribution function D of a developing solution is established; according to the concentration distribution function D of the developing solution, a developing solution concentration diffusion calculation formula R is constructed, which is used for calculating the diffusion results of the developing solution with different concentrations; the developing solution concentration diffusion calculation formula R is used to simulate the developing process, and a simulated negative developing photoresist pattern after developing is obtained; the simulated negative developing photoresist pattern is compared with related data in a preset pattern, and if the preset standard is met, the simulated negative developing photoresist pattern is taken as a formal negative developing photoresist pattern.

Description

[0001] The present application relates to the technical field of semiconductor technology, in particular to a negative developing photoresist model optimization method.

[0002] The photoetching process is the most important manufacturing process in modern very large scale integrated circuit manufacturing process, which is an important means of transferring the design pattern of integrated circuit on the mask to the silicon wafer by the photoetching machine. In the manufacturing process, as the feature size gradually decreases, the process window available for manufacturing will become smaller and smaller, but because the whole photoetching process needs to be accurately controlled, the requirement for calculating the photoetching accuracy is higher and higher. Accurately calculating the photoetching model can theoretically explore the way to increase the photoetching resolution and process window, and guide the optimization of process parameters.

[0003] In the current technical solution, the more advanced photoresist technology is to use negative development. The photoresist used in negative development has good adhesion and blocking effect, and fast photosensitivity, but it will deform and swell during development, so the thermal shrinkage effect of negative development is more intense than that of positive development. The thermal shrinkage effect will make the development solution distribution different from the light field distribution during development, resulting in a decrease in modeling accuracy; in addition, for a chip, the size of a chip can be up to 32mmx26mm, and the line width of the smallest pattern can be only 10nm, and the layout file of a photoetching layer can reach several hundred GB, so the model speed is also a very important technical index. However, the existing negative developing photoresist calculation model optimization method cannot balance the accuracy and speed.

[0004] To solve the problem that the existing negative developing photoresist calculation model optimization method cannot balance the accuracy and speed, the present application provides a negative developing photoresist calculation model optimization method.

[0005] The technical problem solved by the present application is to provide a negative developing photoresist model optimization method, which comprises the following steps:

[0006] An initial negative developing photoresist model is obtained;

[0007] Based on the light field distribution in the initial negative developing photoresist model and the acid concentration in the photoresist, a distribution function S of the acid concentration in the photoresist based on the light field distribution is established;

[0008] Based on the distribution function S of the acid concentration in the photoresist, a concentration distribution function D of the development solution is established;

[0009] According to the concentration distribution function D of the development solution, a development solution concentration diffusion calculation formula R is constructed, which is used to calculate the diffusion results of development solutions with different concentrations;​​​

[0010] The developing process is simulated by using the developing solution concentration diffusion calculation formula R to obtain a simulated negative developing photoresist pattern after development;

[0011] The simulated negative developing photoresist pattern is compared with related data in the preset pattern, and if a preset standard is met, the simulated negative developing photoresist pattern is taken as the formal negative developing photoresist pattern.

[0012] Preferably, the distribution function S of the acid concentration in the photoresist based on the light field distribution is established based on the light field distribution in the initial negative developing photoresist model and the acid concentration in the photoresist, and specifically includes the following steps:

[0013] The light field distribution data based on the mask pattern pixel points as the position basis is obtained from the initial negative developing photoresist model, and the light field distribution function E(x, y) related to the pixel point position information is constructed according to the obtained light field distribution data, E is a function related to (x, y), and (x, y) is the pixel point position information;

[0014] The acid concentration distribution function S(x, y) in the photoresist is established based on the light field distribution function E(x, y), and the acid concentration distribution function S(x, y) in the photoresist is a related function S(x, y) = F(E(x, y)) of the light field distribution function E(x, y).

[0015] Preferably, the expression of the acid concentration distribution function in the photoresist is S = 1 - G, wherein G is the concentration of the photoacid generator, and the instantaneous consumption rate expression of the concentration of the photoacid generator is Wherein c represents the exposure rate constant, and t represents time.

[0016] Preferably, the concentration distribution function D of the developing solution is established based on the distribution function S of the acid concentration in the photoresist, and specifically includes the following steps:

[0017] The consumption ratio of the acid in the photoresist and the developing solution is determined according to the chemical reaction formula of the acid in the photoresist and the developing solution;

[0018] The concentration distribution function D(x, y) of the developing solution is established according to the consumption ratio of the acid in the photoresist and the developing solution as F(S(x, y)).

[0019] Preferably, the expression of the concentration distribution function of the developing solution is Wherein K amp represents the cross-linking reaction rate constant, and t represents time.

[0020] Preferably, before the developing solution concentration diffusion calculation formula R is constructed according to the concentration distribution function D of the developing solution for calculating the diffusion results of the developing solution with different concentrations, the following steps are further included:

[0021] a concentration diffusion direction expression D1 of the developing solution is established;

[0022] a concentration diffusion intensity expression D2 of the developing solution is established.

[0023] The concentration diffusion direction expression of the developing solution is D1=D(x1, y1)*D(x2, y2), and the concentration diffusion intensity expression of the developing solution is D2=D(x1, y1)*(x1-x2, y1-y2).

[0024] Preferably, the concentration diffusion calculation formula R of the developing solution is constructed according to the concentration distribution function D of the developing solution, and is used to calculate the diffusion result of the developing solution with different concentrations, and specifically includes the following steps:

[0025] The concentration diffusion direction and intensity of the developing solution in each unit area are obtained according to the concentration diffusion direction expression D1 and the diffusion intensity expression D2 of the developing solution, and the diffusion result of the developing solution in each unit area is calculated based on the concentration distribution function D of the developing solution; the concentration diffusion calculation formula R(x, y) of the developing solution is constructed based on the concentration diffusion direction expression D1 and the diffusion intensity expression D2 of the developing solution, the diffusion results of the developing solution in each unit area are accumulated, and the diffusion of the developing solution is simulated.

[0026] Preferably, the total diffusion result calculation formula is The total diffusion result calculation formula is constructed based on the idea of calculus, wherein m belongs to a positive integer constant.

[0027] Preferably, the method further includes the following steps:

[0028] The factors for comparing the simulated negative developing photoresist pattern after development with the preset pattern include the root mean square size of the preset critical dimension and / or the grid point error size.

[0029] Compared with the prior art, the negative developing photoresist model optimization method has the following advantages:

[0030] 1. The negative development photoresist calculation model optimization method of the application is a negative development simulation method based on the calculation of the density distribution of the developing solution, the function correlation function S of the distribution of the acid concentration in the photoresist is established by the relevant data of the light field distribution in the initial negative development photoresist model; then, in the development process, the developing solution will chemically react with the acid in the photoresist, and the acid will be consumed in a corresponding proportion according to the chemical reaction formula, so it can be considered that the concentration consumption of the developing solution is proportional to the concentration consumption of the acid in the photoresist, and on this basis, the concentration distribution function D of the developing solution can be quickly established; the concentration distribution data of the developing solution can be obtained through the concentration distribution function D of the developing solution, and since the concentrations of the developing solutions distributed in different regions are different, diffusion effect will occur, so based on the concentration distribution function D of the developing solution, the developing solution concentration diffusion calculation formula R can be constructed; since the development process is actually the chemical reaction process of the photoresist and the developing solution, the concentration change of the developing solution is directly related to the image of the photoresist, and in negative development, the part of the photoresist that reacts with the developing solution will remain, therefore, according to the concentration change of the developing solution, we can know which area of the photoresist has reacted, and also can know the photoresist image after the reaction; therefore, we can accurately simulate the concentration distribution change of the developing solution in the development process to accurately simulate the change of the photoresist in the development process, so as to obtain the high-precision negative development photoresist pattern after development; this method can balance the modeling speed and accuracy, and can ensure the accuracy while making the modeling speed comparable to that of positive development.

[0031] 2. The light field distribution function E in the application is constructed according to the obtained light field distribution data, and the acid concentration distribution function S in the photoresist is constructed based on the light field distribution function E, so when the light field distribution function E is a function related to (x, y), the acid concentration distribution function S in the photoresist is also a function related to (x, y), this design is convenient for unified variables, makes it convenient for operation, and is beneficial to reduce the operation amount and improve the operation speed during optimization; and the light field distribution data in the application is obtained based on the pixel points of the mask pattern as the position basis, and the accuracy is high.

[0032] 3. The acid in the photoresist in the application is produced by the decomposition of a photoacid generator, so the expression of the acid concentration distribution function in the photoresist is S=1-G, and the concentration of the photoacid generator is consumed at a rate related to the exposure rate constant c and the light field distribution function E because the photoacid generator will decompose to produce acid under light.

[0033] 4、The concentration distribution function D of the developing solution in the application is established according to the consumption ratio of the acid in the developing solution and the photoresist, and is a function related to (x, y), which is convenient for unified variables, easy to operate, and beneficial to reduce the operation amount in optimization and improve the operation speed.

[0034] 5、As described in the first point, the developing solution will react with the acid in the photoresist during the developing process, and the acid will be consumed in a corresponding proportion according to the chemical reaction formula, so it can be considered that the concentration consumption of the developing solution is proportional to the concentration consumption of the acid in the photoresist; therefore, the concentration distribution function of the developing solution adopts the instantaneous consumption rate of the concentration of the photoacid generator which is highly related to the instantaneous consumption rate of the developing solution Then the concentration distribution function D of the developing solution is related to the acid concentration distribution function S in the photoresist through the cross-linking reaction rate constant K amp .

[0035] 6、In the application, because the concentrations of the developing solution are different between different positions, a strong diffusion effect will be generated, the developing solution in the area with high concentration of the developing solution diffuses back to the area with low concentration of the developing solution, and the diffusion effect will be strengthened when the concentration is greater than a certain intensity; and the technical solution of the application can effectively and quickly calculate the total of the reaction and greatly improve the modeling speed and accuracy by first establishing the concentration diffusion direction expression D1 of the developing solution and the concentration diffusion intensity expression D2 of the developing solution, and then establishing the concentration diffusion calculation formula R of the developing solution based on the calculus idea.

[0036] 7、In the application, the concentration diffusion direction expression D1 of the developing solution and the concentration diffusion intensity expression D2 of the developing solution are both expressions related to (x, y), the variables are unified, which is convenient for operation, can further reduce the operation amount in modeling, and improve the operation speed.

[0037] 8、In the application, the concentration diffusion calculation formula R of the developing solution is based on the calculus idea to accumulate the diffusion of the concentration, and does not need to perform pure brute force superposition calculation, which further reduces the operation amount in modeling and improves the overall operation speed.

[0038] 9、In the application, the developing state can be monitored through the concentration diffusion direction expression D1=D(x1,y1)*D(x2,y2) of the developing solution, when the concentration diffusion direction expression D1=D(x1,y1)*D(x2,y2) of the developing solution becomes a constant value, it indicates that the concentration distribution of the developing solution has entered a stable state and no longer diffuses.

[0039] 10. In this invention, the comparison factors include the root mean square size of the preset key dimensions and / or the grid error size, which makes the comparison comprehensive and can effectively avoid comparison errors. [Attached Image Description]

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a block diagram of the negative development photoresist calculation model optimization method provided in the first embodiment of the present invention.

[0042] Figure 2 This is the light field distribution diagram of the selected photoresist region in the negative development photoresist calculation model optimization method provided in the first embodiment of the present invention.

[0043] Figure 3 This is a light field distribution diagram after the developing solution has diffused completely in the selected photoresist region in the negative developing photoresist calculation model optimization method provided in the first embodiment of the present invention.

[0044] Figure 4 This is the light field distribution diagram of another photoresist region selected in the negative development photoresist calculation model optimization method provided in the first embodiment of the present invention.

[0045] Figure 5 This is a light field distribution diagram of the selected photoresist region after the developing solution has diffused completely in the negative developing photoresist calculation model optimization method provided in the first embodiment of the present invention.

Detailed Implementation Methods

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the invention 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 merely illustrative and not intended to limit the invention.

[0047] The terms “vertical,” “horizontal,” “left,” “right,” “up,” “down,” “upper left,” “upper right,” “lower left,” “lower right,” “lower left,” “lower right,” and similar expressions used in this article are for illustrative purposes only.

[0048] Please combine Figures 1 to 5 The first embodiment of the present invention provides a method for optimizing a negative development photoresist model, comprising the following steps:

[0049] Step S1: Obtain the initial negative development photoresist model;

[0050] Step S2: based on the light field distribution in the initial negative development photoresist model and the acid concentration in the photoresist, a distribution function S of the acid concentration in the photoresist based on the light field distribution is established;

[0051] Step S3: based on the distribution function S of the acid concentration in the photoresist, a concentration distribution function D of the development solution is established;

[0052] Step S4: according to the concentration distribution function D of the development solution, a development solution concentration diffusion calculation formula R is constructed for calculating the diffusion results of the development solution with different concentrations;

[0053] Step S5: the development solution concentration diffusion calculation formula R is used to simulate the development process to obtain the simulated negative development photoresist pattern after development;

[0054] Step S6: the simulated negative development photoresist pattern is compared with the related data in the preset pattern, and if the preset standard is met, the simulated negative development photoresist pattern is taken as the formal negative development photoresist pattern.

[0055] It can be understood that the negative development photoresist calculation model optimization method of the present application is a negative development simulation method based on the density distribution of the development solution. The function correlation function S of the distribution of the acid concentration in the photoresist is established by the related data of the light field distribution in the initial negative development photoresist model. Then, since in the development process, the development solution will react with the acid in the photoresist, and the proportion of the acid consumed will be proportional to the concentration of the development solution, the concentration distribution function D of the development solution can be quickly established based on this. The concentration distribution data of the development solution can be obtained through the concentration distribution function D of the development solution. Since the concentration of the development solution distributed in different areas will produce diffusion effect, the development solution concentration diffusion calculation formula R is constructed based on the concentration distribution function D of the development solution. Since the photoresist reacts with the development solution in the development process, the change of the concentration of the development solution is directly related to the image of the photoresist. In negative development, the part of the photoresist that reacts with the development solution will remain. Therefore, according to the change of the concentration of the development solution, we can know which area of the photoresist has reacted, and also know the image of the photoresist after reaction. Therefore, we can accurately simulate the change of the photoresist in the development process by accurately simulating the concentration distribution change of the development solution in the development process, so as to obtain the high-precision negative development photoresist pattern after development. This method can balance the modeling speed and accuracy, and ensure the accuracy while making the modeling speed comparable to that of positive development.

[0056] Further, step S1 specifically comprises the following steps:

[0057] Step S11: Selecting at least one region of the photoresist as a target region, and generating a mask image of a predetermined size;

[0058] Specifically, in this embodiment, a mask image of 512*512 pixels is generated. It can be understood that the pixel size of the template image can be adjusted according to actual needs.

[0059] Step S12: Establishing an initial negative development photoresist model by using the generated mask image of a predetermined size and an existing modeling method.

[0060] Further, step S2 specifically includes the following steps:

[0061] Step S21: Obtaining light field distribution data based on the pixel points of the mask pattern from the initial negative development photoresist model, and constructing a light field distribution function E(x, y) related to the pixel point position information based on the obtained light field distribution data, E is a function related to (x, y), and (x, y) is the pixel point position information;

[0062] Specifically, the light field distribution function is a statistical distribution function result of different light intensities of light at different positions due to transmission, reflection or refraction, etc. It can be understood that different optical models will have different light field distributions, and therefore the light field distribution function E(x, y) established according to different optical models will also be different.

[0063] Step S22: Establishing an acid concentration distribution function S(x, y) in the photoresist based on the light field distribution function E(x, y), and the acid concentration distribution function S(x, y) in the photoresist is a related function S(x, y) = F(E(x, y)) of the light field distribution function E(x, y).

[0064] It can be understood that the light field distribution function E in the present application is constructed according to the obtained light field distribution data, and the acid concentration distribution function S in the photoresist is constructed based on the light field distribution function E, so when the light field distribution function E is a function related to (x, y), the acid concentration distribution function S in the photoresist is also a function related to (x, y). This design facilitates the unification of variables, makes it convenient to operate, reduces the amount of calculation during optimization, and improves the operation speed. Moreover, the light field distribution data in the present application is obtained based on the pixel points of the mask pattern, which has high accuracy.

[0065] Further, the expression of the acid concentration distribution function in the photoresist is S = 1-G, where G is the concentration of the photoacid generator, and the instantaneous consumption rate expression of the concentration of the photoacid generator is Where c represents the exposure rate constant, and t represents time.

[0066] It can be understood that in mathematics, represents the derivative of G with respect to t, G is the concentration of the photoacid generator, and t represents time, so according to the definition of the derivative, represents the instantaneous consumption rate of the concentration of the photoacid generator.

[0067] It can be understood that in the present application, the acid in the photoresist is generated by the decomposition of the photoacid generator, so the expression of the acid concentration distribution function in the photoresist is S = 1 - G, and the photoacid generator will decompose to generate acid under light, so the instantaneous consumption rate of the concentration of the photoacid generator will be related to the exposure rate constant c and the light field distribution function E.

[0068] Photoacid generator is a kind of compound which can decompose to generate specific acid under the radiation of light, ray, plasma and the like, and the generated acid can cause the acid sensitive resin to decompose or crosslinking reaction.

[0069] Further, step S3 specifically includes the following steps:

[0070] Step S31: determining the consumption proportion of the acid in the photoresist and the developing solution according to the chemical reaction formula of the acid in the photoresist and the developing solution;

[0071] It can be understood that since the developing solution will react with the acid in the photoresist during the developing process, the developing solution will consume the corresponding proportion of acid according to the chemical reaction formula, so it can be considered that the concentration consumption of the developing solution is proportional to the concentration consumption of the acid in the photoresist; Therefore, the consumption proportion of the acid in the photoresist and the developing solution can be determined according to the chemical reaction formula of the acid in the photoresist and the developing solution.

[0072] Step S32: establishing the concentration distribution function of the developing solution as D(x, y) = F(S(x, y)) according to the consumption proportion of the acid in the photoresist and the developing solution.

[0073] Further, the expression of the concentration distribution function of the developing solution is where K amp represents the crosslinking reaction rate constant, and t represents time.

[0074] As described above, since the developing solution will react with the acid in the photoresist during the developing process, the developing solution will consume the corresponding proportion of acid according to the chemical reaction formula, so it can be considered that the concentration consumption of the developing solution is proportional to the concentration consumption of the acid in the photoresist; Therefore, the concentration distribution function of the developing solution established adopts the instantaneous consumption rate of the concentration of the photoacid generator which is highly related to the instantaneous consumption rate of the developing solution Then through the crosslinking reaction rate constant K ampThe concentration distribution function D of the developing solution is related to the acid concentration distribution function S in the photoresist.

[0075] Further, the step S4 specifically comprises the following steps:

[0076] Step S31: establishing a concentration diffusion direction expression D1 of the developing solution;

[0077] Step S32: establishing a concentration diffusion intensity expression D2 of the developing solution.

[0078] It can be understood that, in the present application, due to the different concentrations of the developing solution between different positions, a strong diffusion effect will be generated, the developing solution in the area with higher concentration of the developing solution diffuses back to the area with lower concentration of the developing solution, and when the concentration is greater than a certain intensity, the diffusion effect will be strengthened; and the technical scheme of the present application can effectively and quickly calculate the total of the reaction by first establishing the concentration diffusion direction expression D1 of the developing solution and the concentration diffusion intensity expression D2 of the developing solution, and then establishing the concentration diffusion calculation formula R of the developing solution based on the calculus idea, thereby greatly improving the modeling speed and accuracy.

[0079] Further, the concentration diffusion direction expression of the developing solution is D1=D(x1, y1)*D(x2, y2), and the concentration diffusion intensity expression of the developing solution is D2=D(x1, y1)*(x1-x2, y1-y2). In the present application, the concentration diffusion direction expression D1 of the developing solution and the concentration diffusion intensity expression D2 of the developing solution are both expressions related to (x, y), the variables are unified, and the operation can be facilitated, thereby further reducing the operation amount during modeling and improving the operation speed.

[0080] Further, the step S4 specifically comprises the following steps:

[0081] According to the concentration diffusion direction expression D1 and the diffusion intensity expression D2 of the developing solution, the concentration diffusion direction and intensity of the developing solution in each unit area are obtained, and the diffusion result of the developing solution in each unit area is calculated based on the concentration distribution function D of the developing solution; and the concentration diffusion calculation formula R(x, y) of the developing solution is constructed based on the concentration diffusion direction expression D1 and the diffusion intensity expression D2 of the developing solution, the diffusion results of the developing solution in each unit area are accumulated, and the diffusion of the developing solution is simulated.

[0082] It can be understood that the developing solution concentration diffusion calculation formula R can accumulate the diffusion results of the developing solution in each unit area of the selected area, so as to obtain the total diffusion results of the developing solution. According to the total diffusion results of the developing solution obtained by calculation, the existing calculation lithography model can be optimized to obtain a high-accuracy negative developing photoresist model. This method can balance the modeling speed and accuracy, ensure the accuracy, and make the modeling speed comparable to the positive development. In addition, the developing solution concentration diffusion calculation formula R is based on the idea of calculus to accumulate the diffusion of the concentration, without pure brute force superposition calculation, further reducing the operation amount during modeling, and improving the overall operation speed.

[0083] Further, the total diffusion result calculation formula is m belongs to a positive integer constant.

[0084] It can be understood that the total diffusion result calculation formula is based on the idea of calculus to construct, which can quickly simulate the diffusion of the developing solution, so as to obtain the total diffusion results of the developing solution.

[0085] Further, in step S5, the change of the photoresist in the developing process is accurately simulated by accurately simulating the concentration distribution change of the developing solution in the developing process, so as to obtain the high-precision negative developing photoresist pattern after development.

[0086] Further, when the concentration diffusion direction expression D1=D(x1, y1)*D(x2, y2) becomes a constant, i.e. there is no difference in concentration, it means that the concentration distribution of the developing solution has entered a stable state and no longer diffuses.

[0087] Further, in step S6, if the comparison result of the related data of the negative developing photoresist pattern and the preset pattern cannot meet the preset standard, the high-precision photoresist pattern is continuously optimized until it meets the preset standard. It can be understood that the specific preset standard can be set according to the type of the compared data.

[0088] Specifically, in the embodiment, the preset pattern in step S6 is a model design pattern; the comparison of the high-precision negative developing photoresist pattern after development and the related data of the preset pattern includes the comparison of the deformation / error of the critical dimension, and the method of comparing the deformation / error of the critical dimension includes comparing the root mean square size of the critical dimension; in addition, the grid error of the critical dimension can also be compared; it can be understood that the root mean square size of the critical dimension and the grid error are both better.

[0089] In other embodiments, other comparison factors can also be added during comparison.

[0090] It can be understood that, in the present application, the high-precision negative developing photoresist pattern after development is compared with the preset pattern, and if the preset standard cannot be met, the modeling result is continuously optimized, which is beneficial to ensure the accuracy of the negative developing photoresist model.

[0091] Specifically, in the present embodiment, the preset standard includes whether the root mean square of the optimized model is less than 2; in other embodiments, the standard can also be other numerical values that are larger or smaller.

[0092] Further, the continuous optimization of the model includes further optimization of the formulas S(x, y), D(x, y) and the like.

[0093] Please refer to Figures 2 to 5 , Figure 2 represents the light field distribution in the initially selected photoresist region, Figure 3 represents the light field distribution after the development effect of the photoresist caused by different densities of the developing solution, and different gray blocks represent different light field intensities, and by comparing Figure 2 and Figure 3 , it can be clearly seen that the image has changed a lot after the diffusion of the developing solution; similarly, Figure 4 and Figure 5 represent another set of controls, including the light field distribution in the initially selected photoresist region Figure 4 and the light field distribution after the development effect of the photoresist caused by different densities of the developing solution Figure 5 ; and the existing negative developing photoresist model cannot simulate the changes from Figures 2 to 3 or Figures 4 to 5 , but the negative developing photoresist model optimization method of the present application can optimize this, simulate the development process through the developing solution concentration diffusion formula R, accurately simulate the concentration distribution change of the developing solution in the development process to accurately simulate the change of the photoresist in the development process, and thus obtain the high-precision negative developing photoresist pattern after development.

[0094] Compared with the prior art, the negative developing photoresist calculation model optimization method of the present application has the following advantages:

[0095] 1. The negative development photoresist calculation model optimization method of the application is a negative development simulation method based on the calculation of the density distribution of the developing solution, the function correlation function S of the distribution of the acid concentration in the photoresist is established by the relevant data of the light field distribution in the initial negative development photoresist model; then, in the developing process, the developing solution will chemically react with the acid in the photoresist, and the proportion of the acid consumed according to the chemical reaction formula will be proportional to the concentration consumption of the developing solution, so the concentration distribution function D of the developing solution can be quickly established based on this, the concentration distribution data of the developing solution can be obtained through the concentration distribution function D of the developing solution, and the concentration of the developing solution distributed in different areas will produce a diffusion effect, so the concentration diffusion calculation formula R of the developing solution is constructed based on the concentration distribution function D of the developing solution; in the developing process, the photoresist chemically reacts with the developing solution, so the concentration change of the developing solution is directly related to the image of the photoresist, and in negative development, the part of the photoresist that reacts with the developing solution will remain, therefore, according to the concentration change of the developing solution, we can know which area of the photoresist has reacted, and also can know the image of the photoresist after the reaction; therefore, the change of the photoresist in the developing process can be accurately simulated by accurately simulating the concentration distribution change of the developing solution in the developing process, so that the high-precision negative development photoresist pattern after development is obtained; this method can balance the modeling speed and accuracy, and can ensure the accuracy while making the modeling speed comparable to that of positive development.

[0096] 2. The light field distribution function E in the application is constructed according to the obtained light field distribution data, and the acid concentration distribution function S in the photoresist is constructed based on the light field distribution function E, so when the light field distribution function E is a function related to (x, y), the acid concentration distribution function S in the photoresist is also a function related to (x, y), this design is convenient for unified variables, makes the operation convenient, is beneficial to reduce the operation amount during optimization, and improves the operation speed; and the light field distribution data in the application is obtained based on the pixel points of the mask pattern as the position basis, and the accuracy is high.

[0097] 3. The acid in the photoresist in the application is produced by the decomposition of a photoacid generator, so the expression of the acid concentration distribution function in the photoresist is S=1-G, and the concentration of the photoacid generator is consumed at a rate related to the exposure rate constant c and the light field distribution function E because the photoacid generator will decompose to produce acid under light.

[0098] 4. The concentration distribution function D of the developing solution in the application is established according to the consumption proportion of the developing solution and the acid in the photoresist, which is a function related to (x, y), this design is convenient for unified variables, makes the operation convenient, is beneficial to reduce the operation amount during optimization, and improves the operation speed.

[0099] 5. As mentioned in point 1 above, during the development process, the developing solution reacts chemically with the acid in the photoresist. The amount of developing solution consumed corresponds to the amount of acid consumed according to the chemical reaction formula. Therefore, it can be considered that the concentration consumption of the developing solution is directly proportional to the concentration consumption of the acid in the photoresist. Thus, the concentration distribution function of the developing solution incorporates the instantaneous consumption rate relative to the concentration of the photoacid-generating agent. Immediate consumption rate of highly correlated developing solution Then through the crosslinking reaction rate constant K amp We will correlate the concentration distribution function D of the developing solution with the acid concentration distribution function S in the photoresist.

[0100] 6. In this invention, due to the different concentrations of the developing solution at different locations, a strong diffusion effect occurs. The developing solution in areas with higher concentrations diffuses back to areas with lower concentrations, and the diffusion effect is enhanced when the concentration exceeds a certain level. The technical solution of this application first establishes the expression for the diffusion direction of the developing solution concentration D1 and the expression for the diffusion intensity of the developing solution concentration D2, and then establishes the calculation formula R for the diffusion of the developing solution concentration based on the concept of calculus. This can effectively and quickly calculate the sum of the reactions, greatly improving the speed and accuracy of modeling.

[0101] 7. In this invention, the expression D1 for the concentration diffusion direction of the developing solution and the expression D2 for the concentration diffusion intensity of the developing solution are both expressions related to (x, y). The variables are unified, which facilitates calculation and can further reduce the amount of calculation during modeling and improve the calculation speed.

[0102] 8. In this invention, the diffusion calculation formula R of the developing solution concentration is based on the concept of calculus to accumulate the diffusion of concentration, without the need for pure brute-force superposition calculation, which further reduces the amount of computation during modeling and improves the overall calculation speed.

[0103] 9. In this invention, the developing state can be monitored by the expression of the concentration diffusion direction of the developing solution as D1 = D(x1, y1) * D(x2, y2). When the expression of the concentration diffusion direction of the developing solution as D1 = D(x1, y1) * D(x2, y2) becomes a constant value, it indicates that the concentration distribution of the developing solution has entered a stable state and no longer diffuses.

[0104] 10. The comparison factors in this invention include the root mean square size of the preset key dimensions and / or the grid error size, which makes the comparison comprehensive and can effectively avoid comparison errors.

[0105] The above has carried out the detailed introduction to the negative development photoresist model optimization method disclosed in the embodiment of the application, the principle and implementation mode of the application are described by applying specific examples in this paper, the above embodiment is only used for helping understanding the method of the application and its core idea; meanwhile, for the general technical personnel in the art, according to the idea of the application, the specific implementation mode and application range will have changes, and the above is described, the content of the specification should not be understood as the limitation of the application, any modification, equivalent replacement and improvement within the principle of the application should be included in the protection scope of the application.

Claims

1. A method for negative tone developing photoresist model optimization, the method comprising: Includes the following steps: Obtain the initial negative development photoresist model; Based on the light field distribution and acid concentration in the initial negative development photoresist model, a distribution function S of acid concentration in the photoresist based on the light field distribution is established. The concentration distribution function D of the developing solution is established based on the function S of the acid concentration distribution in the photoresist; Based on the concentration distribution function D of the developing solution, a diffusion calculation formula R for the concentration of the developing solution is constructed to calculate the diffusion results of developing solutions of different concentrations. The development process was simulated using the diffusion calculation formula R of the developer solution concentration to obtain the simulated negative development photoresist pattern after development. The simulated negative development photoresist pattern is compared with the relevant data in the preset pattern. If the preset standard is met, the simulated negative development photoresist pattern is used as the official negative development photoresist pattern.

2. The negative tone development photoresist computational model optimization method of claim 1, wherein, The establishment of the distribution function S of acid concentration in the photoresist based on the light field distribution and acid concentration in the photoresist in the initial negative development photoresist model specifically includes the following steps: Light field distribution data based on the mask pattern pixels are obtained from the initial negative development photoresist model. A light field distribution function E(x,y) based on the pixel position information is constructed based on the obtained light field distribution data. E is a function related to (x,y), and (x,y) is the pixel position information. Based on the light field distribution function E(x,y), the acid concentration distribution function S(x,y) in the photoresist is established. The acid concentration distribution function S(x,y) in the photoresist is the correlation function of the light field distribution function E(x,y) S(x,y)=F(E(x,y)).

3. The method for optimizing the computational model of negative developing photoresist as described in claim 2, characterized in that: The expression for the acid concentration profile function in the photoresist is S = 1 - G, where G is the concentration of photoacid generator, and the instantaneous rate of consumption of the photoacid generator concentration is where c represents the exposure rate constant and t represents time.

4. The negative tone development photoresist computational model optimization method of claim 1, wherein, The establishment of the concentration distribution function D of the developing solution based on the function S of acid concentration distribution in the photoresist specifically includes the following steps: The consumption ratio of the developing solution and the acid in the photoresist is determined based on the chemical reaction formula between the acid in the photoresist and the developing solution. Based on the consumption ratio of acid in the photoresist and developer solution, the concentration distribution function of the developer solution is established as D(x,y)=F(S(x,y)).

5. The method for optimizing the computational model of negative developing photoresist as described in claim 4, characterized in that: The concentration profile function of the developing solution is expressed as where K amp represents the cross-linking reaction rate constant, and t represents time.

6. The method for optimizing the computational model of negative developing photoresist as described in claim 1, characterized in that, Before constructing the diffusion calculation formula R for the developer solution concentration based on the concentration distribution function D of the developer solution to calculate the diffusion results of developer solutions of different concentrations, the following steps are also included: Establish the expression D1 for the concentration diffusion direction of the developing solution; Establish the expression D2 for the concentration diffusion intensity of the developing solution.

7. The method for optimizing the computational model of negative developing photoresist as described in claim 6, characterized in that: The direction of concentration diffusion of the developing solution is expressed as D1 = D(x1,y1)*D(x2,y2), and the intensity of concentration diffusion of the developing solution is expressed as D2 = D(x1,y1)*(x1-x2,y1-y2).

8. The method for optimizing the computational model of negative developing photoresist as described in claim 7, characterized in that, The step of constructing a diffusion calculation formula R for the concentration of the developing solution based on the concentration distribution function D of the developing solution, and using it to calculate the diffusion results of developing solutions of different concentrations, specifically includes the following steps: The diffusion direction and intensity of the developing solution within each unit area are obtained based on the diffusion direction expression D1 and diffusion intensity expression D2 of the developing solution. The diffusion result of the developing solution within each unit area is calculated based on the concentration distribution function D of the developing solution. Then, based on the diffusion direction expression D1 and diffusion intensity expression D2 of the developing solution, the diffusion calculation formula R(x, y) of the developing solution concentration is constructed. The diffusion results of the developing solution within each unit area are accumulated to simulate the diffusion of the developing solution.

9. The method for optimizing the computational model of negative developing photoresist as described in claim 8, characterized in that: The formula for calculating the total diffusion result is as follows: Formula for calculating total diffusion results It is constructed based on the ideas of calculus, where m is a positive integer constant.

10. The method for optimizing the computational model of negative development photoresist as described in claim 7, characterized in that: When comparing the high-precision negative-developed photoresist pattern after development with the preset pattern, the comparison factors include the root mean square size of the preset key dimensions and / or the grid error.

Images