A method, device, equipment and storage medium for determining semiconductor optical development evolution

Abstract

The present invention belongs to the technical field of semiconductor manufacturing, and provides a method, device, equipment and storage medium for determining semiconductor photolithography evolution. The method of the present invention includes: determining a calculation region for simulating photolithography development according to input parameters of a photoresist region and a mask region of a 3D semiconductor device structure, and determining an initial value of a level set equation; determining an evolution speed of the photoresist surface based on the input parameters; obtaining a discrete format of the level set equation; solving the discrete format of the level set equation based on the initial value of the level set equation and the evolution speed to obtain a three-dimensional discrete data field in the calculation region; and using the marching cubes method to extract a photolithography development surface region when the simulation time is reached. The present invention solves the problem that it is currently necessary to invest in actual production to determine the development status by introducing a level set equation to simulate and determine the evolution surface after the photolithography development reaches the simulation time, which is convenient for the subsequent development of the photolithography process.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor manufacturing technology, and particularly to a method, apparatus, device and storage medium for determining the evolution of semiconductor photolithography development. Background Art

[0002] The lithography process is a crucial link in integrated circuit manufacturing. Through a series of complex steps, including coating photoresist, exposure, development, etc., the designed circuit pattern is accurately transferred to the surface of the semiconductor wafer. After the wafer is aligned and exposed, the pattern of the device or circuit is recorded on the photoresist in the form of exposed and unexposed areas. The pattern is developed by chemically decomposing the unpolymerized photoresist. The development technology is designed to replicate the exact same mask pattern onto the photoresist.

[0003] Problems caused by poor development processes are insufficient development, which can lead to incorrect hole sizes or concave sides of the holes. In some cases, the development is not deep enough and a layer of photoresist remains in the holes. Sometimes there is also the problem of overdevelopment, which removes too much photoresist from the pattern edges or surfaces. It is a special challenge to maintain well-shaped holes while ensuring consistent diameters of vias with high aspect ratios and the difficulty of cleaning due to the inaccessibility of liquid during deep hole cleaning.

[0004] Currently, all development processes need to be put into actual production to determine the actual situation of development, lacking effective prediction of the development process. The ideal situation for the lithography process is that the development result is the pattern after exposure, but there are often significant differences in the actual situation. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method, apparatus, device and storage medium for determining the evolution of semiconductor photolithography development to solve the problem of the current lack of effective prediction of the development process.

[0006] In a first aspect, a method for determining the evolution of semiconductor photolithography development provided by the present invention includes:

[0007] Determine the calculation region for simulating photolithography development and determine the initial value of the level set equation according to the input parameters of the photoresist region and the mask region of the 3D semiconductor device structure ;

[0008] Determine the evolution speed of the photoresist surface based on the input parameters;

[0009] Obtain the discrete format of the level set equation;

[0010] Based on the initial value of the level set equation Solve the discrete format of the level set equation according to the evolution speed to obtain the three-dimensional discrete data field in the calculation region;

[0011] Use the marching cubes method to extract the optically developed surface region at the simulation time.

[0012] Optionally, the evolution speed of the photoresist surface is determined according to the following formula:

[0013] ;

[0014] where a, b, c, and d are input parameters, and a and d must be greater than 0.

[0015] a affects the reaction speed of the photoresist and the developer in the horizontal direction; b affects the uniformity of the reaction of the photoresist and the developer in the vertical direction; c affects the uniformity of the reaction of the photoresist and the developer in the horizontal direction; d affects the reaction speed of the photoresist and the developer in the vertical direction.

[0016] Variable 、 are the axis and axis coordinates of the center point of the photoresist region.

[0017] Optionally, the level set equation satisfies

[0018] ,

[0019] where is the surface evolution speed, and the velocity field is decomposed along the normal vector and the tangent vector of the evolution surface, that is ,

[0020] where 、 are the normal vector and the tangent vector of the evolution surface respectively, 、 are the normal and tangential components of the evolution speed along the evolution surface;

[0021] Substitute this expression into the level set equation to get:

[0022] ;

[0023] The calculation formula for the normal vector of the evolution surface is:

[0024] ,

[0025] Substitute the expression of the normal vector into the level set equation to get:

[0026] ;

[0027] In the optical lithography simulation, substitute the formula for the evolution speed of the photoresist surface into .

[0028] Optionally, the method for obtaining the discrete format of the level set equation includes:

[0029] Based on a preset discrete precision, obtain the discrete format of the level set equation according to the approximation format associated with the preset precision in the finite difference method.

[0030] Optionally, the approximation format associated with the preset discrete precision in the finite difference method includes:

[0031] The approximation format for the time derivative includes the first-order accurate forward Euler format, the second-order TVD Runge-Kutta format, and the third-order TVD Runge-Kutta format;

[0032] The approximation format for the spatial derivative includes the first-order accurate upwind format, the second-order accurate Runge-Kutta format, the second-order Hamilton-Jacobi ENO format, the third-order Hamilton-Jacobi ENO format, and the fifth-order Hamilton-Jacobi WENO format.

[0033] Optionally, based on the initial value of the level set equation and the evolution speed, solve the discrete format of the level set equation to obtain the three-dimensional discrete data field in the computational domain, including:

[0034] Based on a preset discrete precision, obtain the discrete format of the level set equation according to the approximation format associated with the preset precision in the finite difference method;

[0035] For the Cartesian grid of the computational domain, at each time level, use the sparse level set region method to screen out the grid points that meet the preset conditions;

[0036] Solve for the discrete values for the grid points that meet the preset conditions;

[0037] Advance the time level until the simulation time is reached to form a three-dimensional discrete data field.

[0038] Optionally, the method for using the marching cubes method to extract the optical lithography surface region at the simulation time includes:

[0039] Use the marching cubes method to extract the isosurface from the three-dimensional discrete data field to obtain a number of triangular patches; the triangular patches form the optical lithography surface at the simulation time.

[0040] In a second aspect, a semiconductor photolithography evolution determination device provided by the present invention includes:

[0041] A region determination module, configured to determine a calculation region for simulating photolithography based on input parameters of a photoresist region and a mask region of a 3D semiconductor device structure, and determine an initial value of a level set equation ;

[0042] A velocity determination module, configured to determine an evolution velocity of the photoresist surface based on the input parameters;

[0043] A discrete acquisition module, configured to acquire a discrete format of the level set equation;

[0044] A solution module, configured to solve the discrete format of the level set equation based on the initial value of the level set equation and the evolution velocity to obtain a three-dimensional discrete data field in the calculation region;

[0045] An extraction module, configured to extract a photolithography surface region at a simulation time using the marching cubes method.

[0046] Optionally, in the velocity determination module, the evolution velocity of the photoresist surface is determined according to the following formula:

[0047] ;

[0048] where a, b, c, and d are input parameters, and a and d must be greater than 0,

[0049] a is the reaction rate of the photoresist and the developer in the horizontal direction; b is the uniformity of the reaction of the photoresist and the developer in the vertical direction; c is the uniformity of the reaction of the photoresist and the developer in the horizontal direction; d is the reaction rate of the photoresist and the developer in the vertical direction;

[0050] Variables 、 are the axis and axis coordinates of the center point of the photoresist region.

[0051] Optionally, in the discrete acquisition module, the level set equation satisfies

[0052] ,

[0053] where is the surface evolution velocity, and the velocity field is decomposed along the normal vector and the tangent vector of the evolution surface, that is ,

[0054] where 、 They are the normal vector and the tangent vector of the evolving surface respectively, , They are the normal and tangential components of the evolving speed

[0055] Substituting this expression into the level set equation gives:

[0056] ;

[0057] The calculation formula for the normal vector of the evolving surface is:

[0058] ,

[0059] Substituting the expression of the normal vector into the level set equation gives:

[0060] ;

[0061] In the optical lithography simulation, substituting the formula for the evolving speed of the photoresist surface into .

[0062] Optionally, the discrete acquisition module is specifically configured to:

[0063] Obtain the discrete format of the level set equation based on the approximation format associated with the preset progress in the finite difference method according to the preset discrete precision.

[0064] Optionally, in the discrete acquisition module, the approximation format associated with the preset discrete precision in the finite difference method includes:

[0065] The approximation formats for the time derivative include the first-order accurate forward Euler format, the second-order TVD Runge-Kutta format, and the third-order TVD Runge-Kutta format;

[0066] The approximation formats for the spatial derivative include the first-order accurate upwind format, the second-order accurate Runge-Kutta format, the second-order Hamilton-Jacobi ENO format, the third-order Hamilton-Jacobi ENO format, and the fifth-order Hamilton-Jacobi WENO format.

[0067] Optionally, the solving module is specifically configured to:

[0068] For the Cartesian grid of the calculation region, at each time level, use the sparse level set region method to screen out the grid points that meet the preset conditions;

[0069] Solve for the discrete values for the grid points that meet the preset conditions;

[0070] Advance the time layer until the simulation time is reached to form a three-dimensional discrete data field.

[0071] Optionally, the extraction module is specifically configured to:

[0072] Use the marching cubes method to extract an isosurface from the three-dimensional discrete data field to obtain a number of triangular patches; the triangular patches form the optical development surface when the simulation time is reached.

[0073] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of any of the above methods are implemented.

[0074] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the steps of any of the above methods are implemented.

[0075] Adopting the above technical solutions, the present application has the following beneficial effects:

[0076] (1) The present invention can predict the optical development evolution surface brought by the photoresist region and the mask region through the level set equation, facilitating the subsequent progress of the lithography process;

[0077] (2) The present invention can determine the optical development surface according to the preset discrete accuracy, and match the calculation accuracy and calculation efficiency according to requirements;

[0078] (3) The present invention only tracks and calculates the grid points near the optical development evolution surface, with fast calculation speed and less memory occupancy. Description of the Drawings

[0079] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0080] Figure 1 Shows a flowchart of a method for determining semiconductor optical development evolution provided by an embodiment of the present invention;

[0081] Figure 2 Shows a flowchart of step S4 provided by an embodiment of the present invention;

[0082] Figure 3 Shows a structural block diagram of a semiconductor optical development evolution determination provided by an embodiment of the present invention;

[0083] Figure 4 The structural block diagram of an electronic device provided by an embodiment of the present invention is shown. Detailed implementation manners

[0084] Hereinafter, embodiments of the technical solution of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and thus are only examples and cannot be used to limit the protection scope of the present invention.

[0085] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the ordinary meanings understood by those skilled in the art to which the present invention belongs.

[0086] As Figure 1 shown, this embodiment provides a method for determining the evolution of semiconductor optical lithography, including:

[0087] S1. Determine the calculation region of the simulated optical lithography according to the parameters of the photoresist region and the mask region of the 3D semiconductor device structure, and determine the initial value of the level set equation .

[0088] Optical lithography is a process in which the exposed photoresist surface reacts with the developer over a period of time, and is actually a process of the evolution of the photoresist surface over time. The level set method is a method for tracking the evolution process of a surface, so it can simulate the evolution of the photoresist surface. This embodiment determines the exposed photoresist surface according to the initial structure of the semiconductor device, the positive and negative properties of the mask, and the covered area.

[0089] According to the exposed photoresist surface, determine the calculation region of the level set method and the initial level set equation value, where the level set equation value is the signed Minkowski distance.

[0090] The following gives a specific example. In the initial device structure, the coordinate range of silicon is , and the coordinate range of the positive photoresist is , where the unit is um.

[0091] Set two positive masks, which are represented by two two-dimensional polygons on the plane, where the vertex sets of the polygons are and , where the unit is um.

[0092] It should be noted that for positive photoresist, the lithography region is the region covered by the positive photoresist; while for negative photoresist, the lithography region is the region not covered by the negative photoresist. Therefore, for negative photoresist, the optical lithography region is the region where lithography is not performed.

[0093] For a positive photoresist, the actual calculation area is the photoresist area covered (exposed) by the positive mask, that is . Based on this area range, the initial value of the level set equation is calculated .

[0094] S2. Determine the evolution speed of the photoresist surface based on the input parameters in step S1.

[0095] Specifically, the evolution speed of the photoresist surface is determined according to the following formula:

[0096] ;

[0097] where a, b, c, d are input parameters, and a and d must be greater than 0;

[0098] a affects the reaction speed of the photoresist and the developer in the horizontal direction;

[0099] b affects the uniformity of the reaction of the photoresist and the developer in the vertical direction;

[0100] c affects the uniformity of the reaction of the photoresist and the developer in the horizontal direction;

[0101] d affects the reaction speed of the photoresist and the developer in the vertical direction;

[0102] The variables , are the axis and axis coordinates of the center point of the photoresist area, which are calculated according to the structure input by the user.

[0103] In a possible implementation manner, , then the evolution speed of the photoresist surface is specifically determined by the following formula:

[0104]

[0105] The specific values of a, b, c, d need to be determined according to the actual production conditions, and those skilled in the art can reasonably select them according to the actual production needs.

[0106] where the variable is the axis and axis coordinates of the center point of the photoresist area, that is, in the area , , and in the area , .

[0107] S3. Obtain the discrete format of the level set equation.

[0108] Specifically: According to the preset discrete precision, the discrete format of the level set equation is obtained based on the approximation format associated with the preset progress in the finite difference method.

[0109] The level set equation satisfies ,

[0110] where is the surface evolution velocity, and the velocity field is decomposed along the normal vector and the tangent vector of the evolving surface, that is ,

[0111] where , are the normal vector and the tangent vector of the evolving surface respectively, and , are the normal and tangential components of the evolution velocity along the evolving surface respectively;

[0112] Substituting this expression into the level set equation gives:

[0113] ;

[0114] The calculation formula for the surface normal vector is:

[0115] ,

[0116] Substituting the expression of the normal vector into the level set equation gives:

[0117] ;

[0118] In the photolithography simulation, the formula for the evolution velocity of the photoresist surface is substituted into .

[0119] Among them, the approximation formats associated with the preset progress in the finite difference method include:

[0120] The approximation formats for the time derivative include the first-order accurate forward Euler format, the second-order TVD Runge-Kutta format, and the third-order TVD Runge-Kutta format;

[0121] The approximation formats for the spatial derivative include the first-order accurate upwind format, the second-order accurate Runge-Kutta format, the second-order Hamilton-Jacobi ENO format, the third-order Hamilton-Jacobi ENO format, and the fifth-order Hamilton-Jacobi WENO format.

[0122] The user can set the spatial discretization step size according to actual needs and select the discretization accuracy, that is, the discretization accuracy for spatial derivatives and time derivatives; when the discretization step size is smaller, the grid is denser, the computational amount is larger, and the finally solved evolution surface is closer to the actual situation. The discretization accuracy and the discretization step size affect the computational accuracy in the discretization format. The discretization accuracy affects the convergence of solving the level set equation, that is, when the discretization step size is the same, the higher the accuracy, the higher the accuracy of the level set equation value at the calculated grid points, and the finally solved evolution surface is closer to the actual situation.

[0123] In one embodiment, the discretization accuracy is selected as second order, and the simulation time is 60 s. The approximation format of the time derivative is the first-order accurate forward Euler format:

[0124] ,

[0125] The second-order accurate TVD Runge-Kutta format:

[0126] First, apply the forward Euler format once to advance the simulation time to ,

[0127] ,

[0128] Then, combine the obtained Apply the forward Euler format once again to advance the simulation time to ,

[0129] , ,

[0130] Then, combine the initial data and the result after two forward Euler steps to obtain

[0131] .

[0132] There is also a higher-precision third-order accurate TVD Runge-Kutta format, which is the result of combining the initial data and the data combined after two forward Euler steps.

[0133] In one embodiment, the approximation format of the spatial derivative has a first-order accurate upwinding format. Taking the derivative with respect to the direction as an example:

[0134] The forward difference derivative format is ;

[0135] The backward difference derivative format is ;

[0136] When the velocity in the direction is greater than 0, a backward difference scheme is adopted; otherwise, a forward difference scheme is adopted.

[0137] There are also higher-precision second-order Hamilton-Jacobi ENO schemes, third-order Hamilton-Jacobi ENO schemes, and fifth-order Hamilton-Jacobi WENO schemes, which utilize interpolation polynomials.

[0138] S4. Solve the discrete format of the level set equation based on the initial value and the evolution velocity of the level set equation to obtain a three-dimensional discrete data field in the computational domain.

[0139] Specifically, as Figure 2 shown, step S4 includes:

[0140] S401. For the Cartesian grid of the computational domain, at each time level, use the sparse level set region method to screen out the grid points that meet the preset conditions;

[0141] S402. Solve the discrete values for the grid points that meet the preset conditions;

[0142] S403. Advance the time level until the simulation time is reached to form a three-dimensional discrete data field.

[0143] Numerical solution method of the level set equation combined with the sparse level set region method:

[0144] Generate a Cartesian grid on the computational domain, and use the finite difference method to obtain the discrete format of the equation; at each time level, use the sparse level set region method to screen out the grid points that meet the conditions, and solve the discrete values for these grid points, thereby advancing the time level until the simulation time is reached.

[0145] The specific steps of the sparse level set region method are as follows: On the corresponding Cartesian grid of the computational domain, screen out the grid points with a sufficiently small Minkowski distance, and prepare the Minkowski distance values of the neighbor grid points required for solving the finite difference for these grid points. For the grid points that do not meet the conditions, set fixed values according to their distance signs.

[0146] Among them, the Minkowski distance is the distance from the grid point to the evolving surface, and the screened grid points are all grid points with a Minkowski distance less than a fixed value.

[0147] S5. Use the marching cubes method to extract the optically developed surface area at the simulation time.

[0148] In one embodiment, the marching cubes method is used to extract an isosurface from a three-dimensional discrete data field, obtaining a number of triangular patches; the number of triangular patches forms the optically developed surface at the simulation time.

[0149] After the solution of the level set equation is completed, a three-dimensional discrete data field in the calculation region described in S1 after simulation optical development is obtained. Then, the marching cubes method is used to extract an isosurface from this data field, obtaining a set of triangular patches. This set of triangular patches represents the photoresist surface at the simulation time, and thus the result of the simulation of 3D semiconductor optical development is obtained. The isosurface mentioned above is the surface with the same value of the level set equation value.

[0150] Therefore, the user can adjust the process conditions of 3D semiconductor optical development according to the simulation results.

[0151] Based on the technical solutions of the above embodiments, there are at least the following technical effects:

[0152] (1) The present invention can predict the optically developed evolution surface brought by the photoresist region and the mask region through the level set equation, facilitating the progress of subsequent lithography processes;

[0153] (2) The present invention can determine the optically developed surface according to the preset discrete precision, and match the calculation precision and calculation efficiency according to the requirements;

[0154] (3) The present invention only tracks and calculates the grid points near the optically developed evolution surface, with a fast calculation speed and less memory occupation.

[0155] In one embodiment, as Figure 3 shown, a semiconductor optical development evolution determination device 60 is provided, including:

[0156] A region determination module 601, configured to determine the calculation region of the simulation optical development according to the input parameters of the photoresist region and the mask region of the 3D semiconductor device structure, and determine the initial value of the level set equation ;

[0157] A speed determination module 602, configured to determine the evolution speed of the photoresist surface based on the input parameters;

[0158] A discrete acquisition module 603, configured to acquire the discrete format of the level set equation;

[0159] A solution module 604, configured to solve the discrete format of the level set equation based on the initial value of the level set equation and the evolution speed to obtain the three-dimensional discrete data field in the calculation region;

[0160] An extraction module 605 is configured to extract the optically developed surface area at the simulation time using the marching cubes method.

[0161] The semiconductor optical development evolution determination device 60 provided by the embodiments of the present application and the above-mentioned semiconductor optical development evolution determination method adopt the same inventive concept and can achieve the same beneficial effects, which will not be elaborated herein.

[0162] Optionally, in the speed determination module, the evolution speed of the photoresist surface is determined according to the following formula:

[0163] ;

[0164] where a, b, c, and d are input parameters, and a and d must be greater than 0.

[0165] a affects the reaction speed of the photoresist and the developer in the horizontal direction; b affects the uniformity of the reaction of the photoresist and the developer in the vertical direction; c affects the uniformity of the reaction of the photoresist and the developer in the horizontal direction; d affects the reaction speed of the photoresist and the developer in the vertical direction.

[0166] Variable 、 are the axis and axis coordinates of the center point of the photoresist area.

[0167] Optionally, in the discrete acquisition module, the level set equation satisfies

[0168] ,

[0169] where is the surface evolution speed, and the velocity field is decomposed along the normal vector and the tangent vector of the evolution surface, that is ,

[0170] where 、 are the normal vector and the tangent vector of the evolution surface respectively, 、 are the normal and tangential components of the evolution speed along the normal and tangent directions of the evolution surface;

[0171] Substituting this expression into the level set equation gives:

[0172] ;

[0173] The calculation formula for the normal vector of the evolution surface is:

[0174] ,

[0175] Substitute the expression of the normal vector into the level set equation to obtain:

[0176] ;

[0177] In the optical lithography simulation, substitute the formula for the evolution speed of the photoresist surface into .

[0178] Optionally, the discrete acquisition module is specifically configured to:

[0179] According to a preset discrete precision, obtain the discrete format of the level set equation based on the approximation format associated with the preset progress in the finite difference method.

[0180] Optionally, in the discrete acquisition module, the approximation format associated with the preset discrete precision in the finite difference method includes:

[0181] The approximation format of the time derivative includes the forward Euler format with first-order accuracy, the second-order TVD Runge-Kutta format, and the third-order TVD Runge-Kutta format;

[0182] The approximation format of the spatial derivative includes the upwind format with first-order accuracy, the second-order Runge-Kutta format, the second-order Hamilton-Jacobi ENO format, the third-order Hamilton-Jacobi ENO format, and the fifth-order Hamilton-Jacobi WENO format.

[0183] Optionally, the solving module is specifically configured to:

[0184] For the Cartesian grid of the calculation region, at each time level, use the sparse level set region method to screen out the grid points that meet the preset conditions;

[0185] Solve for the discrete value;

[0186] Advance the time level until the simulation time is reached to form a three-dimensional discrete data field.

[0187] Optionally, the extraction module is specifically configured to:

[0188] Use the marching cubes method to extract the isosurface from the three-dimensional discrete data field to obtain a number of triangular patches; the triangular patches form the optical lithography surface at the simulation time.

[0189] Based on the same inventive concept as the above semiconductor optical lithography evolution determination method, an embodiment of the present application also provides an electronic device 70, such as Figure 4As shown, the electronic device 70 may include a processor 701 and a memory 702.

[0190] The processor 701 may implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The steps of the method disclosed in combination with the embodiments of the present invention may be directly embodied as being executed and completed by a hardware processor, or may be executed and completed by a combination of hardware and software modules in the processor.

[0191] The memory 702, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The memory 702 in the embodiments of the present invention may also be a circuit or any other device capable of implementing a storage function, for storing program instructions and / or data.

[0192] The embodiments of the present invention provide a computer-readable storage medium for storing computer program instructions used for the above-mentioned electronic device, which includes a program for executing the above-mentioned semiconductor photolithography evolution determination method.

[0193] The above-mentioned computer storage medium may be any available medium or data storage device accessible by a computer, including but not limited to magnetic memories (such as floppy disks, hard disks, magnetic tapes, magneto-optical discs (MO), etc.), optical memories (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor memories (such as ROMs, EPROMs, EEPROMs, non-volatile memories (NAND FLASH), solid-state drives (SSD)).

[0194] The above embodiments are only used to introduce the technical solutions of the present application in detail, but the descriptions of the above embodiments are only used to help understand the method of the embodiments of the present invention and should not be construed as a limitation to the embodiments of the present invention. Any changes or substitutions that can be easily thought of by those skilled in the art should be covered within the protection scope of the embodiments of the present invention.

Claims

1. A method for determining semiconductor light development evolution, characterized in that: include: According to the input parameters of the photoresist area and mask area of ​​the 3D semiconductor device structure, the calculation area of ​​the simulated light development is determined, and the initial value of the level set equation is determined ; determining an evolution rate of the photoresist surface based on the input parameters; Get the discretized form of the level set equation; Based on the initial value of the level set equation and the evolution speed to solve the discrete format of the level set equation to obtain a three-dimensional discrete data field in the calculation area; The light-developed surface area up to the simulation time is extracted using the marching cube method.

2. The method according to claim 1, characterized in that The evolution rate of the photoresist surface is determined according to the following formula: ； Among them, a, b, c, and d are input parameters. a and d must be greater than 0. a affects the reaction speed of the photoresist and the developer in the horizontal direction; b affects the uniformity of the reaction of the photoresist and the developer in the vertical direction; c is the influence on the uniformity of the reaction between the photoresist and the developer in the horizontal direction; d is the speed of the reaction between the photoresist and the developer in the vertical direction; variable , is the center point of the photoresist area Axis and Axis coordinates.

3. The method according to claim 2, characterized in that The level set equation satisfies ， in is the surface evolution velocity, and the velocity field The normal and tangent vectors along the evolving surface are decomposed into , in , are the normal vector and tangent vector of the evolving surface, , The evolution speed normal and tangential components along the evolving surface; Substituting this expression into the level set equation, we get: ； The calculation formula of the evolving surface normal vector is: ， Substituting the expression of the normal vector into the level set equation, we get: ； In the photodevelopment simulation, the photoresist surface evolution rate formula is Substitution .

4. The method according to claim 3, characterized in that: The discrete format for obtaining the level set equation includes: According to the preset discrete precision, the discrete format of the level set equation is obtained based on an approximation format associated with the preset discrete precision in a finite difference method.

5. The method according to claim 4, characterized in that The approximation format associated with the preset discrete precision in the finite difference method includes: The approximation formats of time derivatives include the first-order accurate forward Euler format, the second-order TVD Runge-Kutta format, and the third-order TVD Runge-Kutta format; The approximation schemes for spatial derivatives include the first-order upwind scheme, the second-order Runge-Kutta scheme, the second-order Hamilton-Jacobi ENO scheme, the third-order Hamilton-Jacobi ENO scheme, and the fifth-order Hamilton-Jacobi WENO scheme.

6. The method according to claim 4, characterized in that The initial value based on the level set equation and the evolution speed to solve the discrete format of the level set equation to obtain a three-dimensional discrete data field in the calculation area, including: For the Cartesian grid of the calculation area, at each time layer, a sparse level set region method is used to screen out grid points that meet preset conditions; Solve for grid points that meet preset conditions Discrete values; The time layer is advanced until the simulation time is reached, forming a three-dimensional discrete data field.

7. The method according to claim 6, characterized in that The method of extracting the light-developed surface area when the simulation time is reached by using the marching cube method comprises: The marching cubic method is used to extract isosurfaces for the three-dimensional discrete data field to obtain a plurality of triangular facets; the triangular facets form a light-developed surface when the simulation time is reached.

8. A semiconductor light development evolution determination device, characterized in that: include: The region determination module is used to determine the calculation region of the simulated light development and the initial value of the level set equation according to the input parameters of the photoresist region and the mask region of the 3D semiconductor device structure. ; A speed determination module, for determining the evolution speed of the photoresist surface based on the input parameters; Discrete acquisition module, used to obtain the discrete format of the level set equation; Solver module for initial value of the level set equation based on and the evolution speed to solve the discrete format of the level set equation to obtain a three-dimensional discrete data field in the calculation area; Extraction module for extracting the light-developed surface area up to simulation time using the marching cube method.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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