Photoresist spin-coating process simulation method and computer equipment

Abstract

The invention relates to a photoresist spin-coating process simulation method and computer equipment, and the method comprises the steps: building a fan-shaped simulation grid based on the parameter information of a target wafer and the position information of a photoresist injection port; the fan-shaped simulation grid is a fan-shaped space area in the columnar space; the columnar space is a space area defined by space extension by taking the surface of the target wafer as the bottom surface and taking the plane where the photoresist injection port is located as the top surface; establishing a two-phase flow fluid mathematical model; through the target solver, the two-phase fluid mathematical model is iteratively solved according to the boundary condition of the fan-shaped simulation grid, the fluid attribute corresponding to the two-phase fluid and the initial condition of process simulation, and the photoresist spin-coating process simulation result is determined, so that the photoresist spin-coating process simulation efficiency is improved, and the photoresist spin-coating process simulation efficiency is improved. The problems of high cost and time consumption required by a traditional simulation method are avoided, and adjustment and optimization of process parameters are more efficient and flexible.

Description

Technical Field

[0001] The present application relates to the technical field of process simulation, and in particular to a method for simulating a photoresist spin coating process and a computer device. Background Art

[0002] In semiconductor manufacturing, photolithography is the core of integrated circuit planar technology. As a sub-process of photolithography, the uniformity of the photoresist process will affect the uniformity of key line widths, line width roughness uniformity, and overlay accuracy, which will further affect the yield of the chip. The uniformity of photoresist is crucial to the clarity and accuracy of the pattern, because uneven photoresist coating may cause pattern distortion or error. The simulation of photoresist spin coating process can provide important data support when process engineers design spin coating process parameters, laying the foundation for efficient and accurate optimization of the photoresist process.

[0003] However, the photoresist spin coating process simulation method in the prior art has the problem of low efficiency, and no effective solution has been proposed yet. Summary of the invention

[0004] Based on this, it is necessary to provide a photoresist spin coating process simulation method and computer equipment to address the above technical problems.

[0005] In a first aspect, the present application provides a method for simulating a photoresist spin coating process, the method comprising:

[0006] Based on the parameter information of the target wafer and the position information of the photoresist injection port, a fan-shaped simulation grid is established; the fan-shaped simulation grid is a fan-shaped space area in the cylindrical space; the cylindrical space is a space area enclosed by spatial extension with the surface of the target wafer as the bottom surface and the plane where the photoresist injection port is located as the top surface; the plane where the photoresist injection port is located is parallel to the surface of the target wafer;

[0007] Obtaining boundary conditions corresponding to the sector-shaped simulation grid, fluid properties corresponding to the two-phase fluid, and initial conditions for process simulation;

[0008] Establish a mathematical model of two-phase flow;

[0009] The target solver is used to iteratively solve the two-phase flow fluid mathematical model according to the boundary conditions, the fluid properties and the process simulation initial conditions to determine the photoresist spin coating process simulation results.

[0010] In one embodiment, the parameter information of the target wafer includes a radius; the position information of the photoresist injection port includes a height of the photoresist injection port; and the step of establishing a fan-shaped simulation grid based on the parameter information of the target wafer and the position information of the photoresist injection port includes:

[0011] Based on the parameter information of the target wafer, the position information of the photoresist injection port and the preset angle, the grid parameters corresponding to the fan-shaped simulation grid are determined; the grid parameters include length, height and center angle; the length of the fan-shaped simulation grid is equal to the radius of the target wafer; the height of the fan-shaped simulation grid is equal to the height of the photoresist injection port; the center angle of the fan-shaped simulation grid is equal to the preset angle;

[0012] Based on a right-handed Cartesian coordinate system and the grid parameters, an initial sector-shaped simulation grid is established;

[0013] According to a preset division rule, the initial sector-shaped simulation grid is grid-divided to obtain a sector-shaped simulation grid; the sector-shaped simulation grid includes a plurality of sub-grid units; the number of the sub-grid units gradually decreases along the positive direction of the x-axis of the right-handed Cartesian coordinate system.

[0014] In one embodiment, the parameter information of the target wafer includes center coordinates; the initial sector simulation grid is established based on a right-handed Cartesian coordinate system and the grid parameters, including:

[0015] Determining the origin of a right-handed Cartesian coordinate system according to the center coordinates of the target wafer;

[0016] Determine the rotational symmetry axis corresponding to the initial fan-shaped simulation grid according to the y-axis of the right-handed Cartesian coordinate system;

[0017] According to the grid parameters and the rotational symmetry axis, an initial fan-shaped simulation grid is generated along the positive direction of the x-axis of the right-handed Cartesian coordinate system; the initial fan-shaped simulation grid is symmetrically distributed along the xy plane of the right-handed Cartesian coordinate system; the photoresist injection port is arranged on a side of the initial fan-shaped simulation grid close to the rotational symmetry axis.

[0018] In one embodiment, in a right-handed Cartesian coordinate system, the fan-shaped simulation grid includes a bottom surface, a front surface, a rear surface, an upper surface, and a right side surface; and obtaining the boundary conditions corresponding to the fan-shaped simulation grid includes:

[0019] Using the solid wall boundary condition as the boundary condition corresponding to the bottom surface of the fan-shaped simulation grid;

[0020] Using wedge-shaped boundary conditions as boundary conditions corresponding to the front surface and the rear surface of the fan-shaped simulation grid;

[0021] The atmospheric boundary conditions are used as boundary conditions corresponding to the upper surface and the right side surface of the sector-shaped simulation grid.

[0022] In one embodiment, obtaining the fluid properties corresponding to the two-phase fluid includes:

[0023] Acquire a physical simulation model; the physical simulation model is a laminar flow model;

[0024] Based on the physical simulation model, the fluid properties corresponding to the two-phase fluid are determined; the two-phase fluid includes an air phase and a photoresist phase; the fluid properties corresponding to the air include a fluid viscosity model, a first dynamic viscosity and a first density; the fluid properties corresponding to the photoresist include a fluid viscosity model, a second dynamic viscosity, a second density and gravity.

[0025] In one embodiment, the method of iteratively solving the two-phase flow fluid mathematical model according to the boundary conditions, the fluid properties and the process simulation initial conditions by a target solver to determine the photoresist spin coating process simulation result includes:

[0026] Get the target solver;

[0027] By means of the target solver, the two-phase flow fluid mathematical model is spatially discretized according to the boundary conditions, the fluid properties and the process simulation initial conditions to obtain a linear system;

[0028] Preprocessing the linear system by a preprocessor to obtain a target linear system;

[0029] The target linear system is iteratively solved by an iterative solver until the solution meets a preset convergence condition, thereby obtaining a simulation result of a photoresist spin coating process; the simulation result of the photoresist spin coating process includes a velocity field, a pressure field and a volume fraction.

[0030] In one embodiment, the method further comprises:

[0031] Determining a photoresist distribution image according to the photoresist spin coating process simulation result;

[0032] Performing contour extraction processing on the photoresist distribution image to obtain photoresist contour data;

[0033] A photoresist profile image is generated based on the photoresist profile data.

[0034] In a second aspect, the present application further provides a photoresist spin coating process simulation device, the device comprising:

[0035] A grid establishment module is used to establish a fan-shaped simulation grid based on parameter information of a target wafer and position information of a photoresist injection port; the fan-shaped simulation grid is a fan-shaped space region in a columnar space; the columnar space is a space region enclosed by spatial extension with the surface of the target wafer as the bottom surface and the plane where the photoresist injection port is located as the top surface; the plane where the photoresist injection port is located is parallel to the surface of the target wafer;

[0036] An acquisition module, used to acquire boundary conditions corresponding to the sector-shaped simulation grid, fluid properties corresponding to the two-phase fluid, and initial conditions for process simulation;

[0037] Model building module, used to build a two-phase flow fluid mathematical model;

[0038] The simulation result determination module is used to iteratively solve the two-phase flow fluid mathematical model through a target solver according to the boundary conditions, the fluid properties and the process simulation initial conditions to determine the photoresist spin coating process simulation results.

[0039] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method described in any one of the embodiments of the first aspect are implemented.

[0040] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method described in any one of the embodiments of the first aspect above are implemented.

[0041] In a fifth aspect, the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method described in any one of the embodiments of the first aspect above.

[0042] The above-mentioned photoresist spin coating process simulation method and computer equipment establish a fan-shaped simulation grid based on the parameter information of the target wafer and the position information of the photoresist injection port, avoiding the problem of high computational complexity caused by using a complete columnar space as the simulation grid, effectively saving computing resources, and at the same time, based on the fan-shaped simulation grid, it is helpful to quickly and accurately understand the photoresist flow phenomenon and trend, laying a foundation for improving the efficiency and accuracy of the photoresist spin coating process simulation. Further, through the target solver, according to the boundary conditions, fluid properties and process simulation initial conditions corresponding to the fan-shaped simulation grid, the two-phase flow fluid mathematical model is iteratively solved, and the photoresist spin coating process simulation results can be accurately and efficiently obtained, which improves the efficiency of the photoresist spin coating process simulation, avoids the high cost and time consumption required by the traditional simulation method, and makes the adjustment and optimization of process parameters more efficient and flexible. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A schematic diagram of a process flow of a photoresist spin coating process simulation method in one embodiment;

[0045] Figure 2 A schematic diagram of a flow chart of steps for establishing a fan-shaped simulation grid in one embodiment;

[0046] Figure 3 is a schematic diagram of a photoresist spin coating process in one embodiment;

[0047] Figure 4 A schematic diagram of a fan-shaped simulation grid in one embodiment;

[0048] Figure 5 A top view of a fan-shaped simulation grid in one embodiment;

[0049] Figure 6 A local schematic diagram of a fan-shaped simulation grid in an embodiment;

[0050] Figure 7 A schematic diagram of a process flow for determining a simulation result of a photoresist spin coating process in one embodiment;

[0051] Figure 8 A schematic diagram of a process for generating a photoresist profile image in one embodiment;

[0052] Fig. 9 is a schematic diagram of a photoresist distribution image in one embodiment;

[0053] Fig.10 is a schematic diagram of a photoresist profile image in one embodiment;

[0054] Fig.11 is a structural block diagram of a photoresist spin coating process simulation device in one embodiment;

[0055] Fig.12 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0057] In an exemplary embodiment, Figure 1 As shown, Figure 1 The schematic diagram of the process flow of a photoresist spin coating process simulation method in one embodiment; the photoresist spin coating process simulation method comprises the following steps:

[0058] Step S101 , establishing a fan-shaped simulation grid based on parameter information of a target wafer and position information of a photoresist injection port.

[0059] Among them, the fan-shaped simulation grid is a fan-shaped space area in the cylindrical space; the cylindrical space is a space area enclosed by spatial extension with the surface of the target wafer as the bottom surface and the plane where the photoresist injection port is located as the top surface; the plane where the photoresist injection port is located is parallel to the surface of the target wafer.

[0060] Among them, the parameter information of the target wafer may include but is not limited to the surface parameters and radius of the target wafer; wherein the surface parameters may include but are not limited to the surface flatness. The photoresist injection port refers to a dedicated port for introducing photoresist into the surface of the target wafer; the photoresist injection port may be a nozzle, a needle or other types of delivery devices, and it is only necessary to ensure that the photoresist can be coated on the surface of the target wafer with a uniform thickness, and no specific limitation is made here. The position information of the photoresist injection port includes the height of the photoresist injection port; the height of the photoresist injection port refers to the vertical distance of the photoresist injection port relative to the surface of the target wafer. It should be noted that the parameter information of the target wafer and the position information of the photoresist injection port need to be selected according to the actual simulation requirements, and no specific limitation is made here.

[0061] It should be noted that, since the photoresist has axial symmetry during the spin coating process, this embodiment uses the surface of the target wafer as the bottom surface and the plane where the photoresist injection port is located as the top surface, and a fan-shaped space area in the columnar space enclosed by spatial extension is used as the simulation grid, which makes full use of the axial symmetry, not only can it more effectively capture the flow characteristics of the rotating area, but also can effectively reduce the calculation complexity, thereby improving the calculation efficiency.

[0062] Step S102, obtaining boundary conditions corresponding to the sector-shaped simulation grid, fluid properties corresponding to the two-phase fluid, and initial conditions for process simulation.

[0063] The boundary conditions corresponding to the sector simulation grid refer to the boundary conditions corresponding to each surface of the sector simulation grid, which are used to constrain the form of the solution during the simulation process; for example, during the simulation process, the boundary conditions are used to specify the value or change law of a physical quantity at the boundary, thereby limiting the solution space. It can be understood that boundary conditions can reduce the size of the computational domain and improve computational efficiency.

[0064] The two-phase fluid includes an air phase and a photoresist phase; the fluid properties corresponding to the two-phase fluid are used to characterize the behavior of the two-phase fluid; the fluid properties may include but are not limited to density, viscosity, and surface tension.

[0065] Among them, the initial conditions of the process simulation may include but are not limited to the initial speed of photoresist injection, the initial rotation speed of the target wafer and the process atmosphere; for example, the initial speed of photoresist injection is v1, the initial rotation speed of the target wafer is w1, and the process atmosphere is standard atmospheric pressure.

[0066] It should be noted that the boundary conditions corresponding to the sector-shaped simulation grid, the fluid properties corresponding to the two-phase fluid, and the initial conditions of the process simulation all need to be set according to actual simulation requirements and are not specifically limited here.

[0067] Step S103, establishing a two-phase flow mathematical model.

[0068] Among them, the mathematical model of two-phase flow fluid is used to describe the physical characteristics and behavior of the two-phase fluid with data. The mathematical model of two-phase flow fluid includes the continuity equation, momentum equation and interface tracking equation; among them, the continuity equation is used to describe the mass conservation principle of the fluid; the momentum equation includes the Navier-Stokes (NS) equation, which is used to describe the continuity and momentum conservation of the fluid; the interface tracking equation includes the volume fraction (VOF) equation, which is used to describe the interface position and shape between the two-phase fluid.

[0069] Exemplarily, the continuity equation is shown in formula (1).

[0070]

[0071] Among them, ρ represents the density of the fluid; t represents the time; u represents the velocity field of the fluid; Denotes the divergence operator. The continuity equation states that the rate of change of the fluid density over time plus the divergence of the product of the fluid density and velocity is equal to zero. This means that the mass of the fluid can neither be created nor destroyed in any volume. In the simulation of the photoresist spin coating process, for incompressible fluids, the density ρ is a constant and does not change with time and space. Therefore, the continuity equation is simplified to formula (2).

[0072]

[0073] Formula (2) shows that the divergence of the fluid velocity field must be zero to ensure that there is no accumulation or loss of mass.

[0074] Exemplarily, the momentum equation, i.e., the NS equation, is shown in formula (3).

[0075]

[0076] Among them, ρ represents the density of the fluid; u represents the velocity field of the fluid, which is a vector function; t represents time; p represents the pressure field of the fluid, which is a scalar function; u represents the dynamic viscosity of the fluid; represents the gradient operator, which is used to calculate the derivative of the velocity field; represents the Laplace operator, which is used to calculate the second-order derivative of the velocity field; f represents the external force, such as gravity or electromagnetic force.

[0077] It should be noted that the momentum equation, namely the NS equation, comprehensively describes the velocity field, pressure field of the fluid and their changes with time and space. It can be used to analyze and predict the behavior of photoresist fluid, including the velocity field, pressure field of the fluid and the interaction between the fluid and the solid boundary.

[0078] Exemplarily, the interface tracking equation, i.e., the VOF equation, is shown in formula (4).

[0079]

[0080] Among them, α i , represents the volume fraction of the i-th item; t, represents the time; u i , represents the velocity vector of the i-th term. The interface tracking equation, or VOF equation, can track and simulate the volume fractions of different fluid phases, thereby indirectly determining the position and shape of the photoresist interface. It can be understood that by solving the VOF equation, the distribution of photoresist, the dynamic behavior of the photoresist interface, and the complex flow phenomena caused by interfacial tension can be predicted.

[0081] Step S104, using a target solver, the two-phase flow fluid mathematical model is iteratively solved according to boundary conditions, fluid properties and process simulation initial conditions to determine the photoresist spin coating process simulation result.

[0082] Among them, the target solver can be but is not limited to the interFoam solver; it should be noted that the target solver can accurately simulate and track the interface between different fluid phases in multiphase flow, and this simulation capability is crucial for understanding and predicting the flow behavior of photoresist.

[0083] Optionally, in an exemplary embodiment, in terms of the algorithm selection corresponding to the target solver, the Pressure-Implicit with Splitting of Operators (PIMPLE) method is selected to solve the two-phase flow fluid mathematical model. In incompressible flow, the density of the fluid is constant, which leads to a strong coupling relationship between the continuity equation and the momentum equation. The PIMPLE algorithm allows the velocity field and the pressure field to be updated simultaneously in each time step by implicitly solving the pressure field. When processing multiphase flow, the PIMPLE algorithm can be combined with the interface tracking technology to effectively capture and update the interface between different fluid phases, which is crucial for accurately simulating the fluid interface dynamics during the photoresist spin coating process.

[0084] Exemplarily, through the target solver, the two-phase flow fluid mathematical model is iteratively solved according to the boundary conditions, fluid properties and initial conditions of the process simulation, and the solution is gradually approached until the convergence criteria are met to determine the simulation results of the photoresist spin coating process.

[0085] In this embodiment, based on the parameter information of the target wafer and the position information of the photoresist injection port, a fan-shaped simulation grid is established, which avoids the problem of high computational complexity caused by using a complete columnar space as a simulation grid, effectively saves computing resources, and at the same time, based on the fan-shaped simulation grid, it is helpful to quickly and accurately understand the photoresist flow phenomenon and trend, and lays a foundation for improving the efficiency and accuracy of the photoresist spin coating process simulation. Further, through the target solver, according to the boundary conditions, fluid properties and process simulation initial conditions corresponding to the fan-shaped simulation grid, the two-phase flow fluid mathematical model is iteratively solved, and the photoresist spin coating process simulation results can be accurately and efficiently obtained, which improves the efficiency of the photoresist spin coating process simulation, avoids the high cost and time consumption required by the traditional simulation method, and makes the adjustment and optimization of process parameters more efficient and flexible.

[0086] In one embodiment, the parameter information of the target wafer includes the radius; the position information of the photoresist injection port includes the height of the photoresist injection port; wherein the height of the photoresist injection port refers to the vertical distance of the photoresist injection port relative to the surface of the target wafer. Figure 2 As shown, Figure 2 The schematic diagram is a flow chart of the steps of establishing a fan-shaped simulation grid in one embodiment; based on the parameter information of the target wafer and the position information of the photoresist injection port, the fan-shaped simulation grid is established, including the following steps:

[0087] Step S201, determining grid parameters corresponding to the fan-shaped simulation grid based on parameter information of the target wafer, position information of the photoresist injection port, and a preset angle.

[0088] Among them, the grid parameters include length, height and center angle; the length of the fan-shaped simulation grid is equal to the radius of the target wafer; the height of the fan-shaped simulation grid is equal to the height of the photoresist injection port; and the center angle of the fan-shaped simulation grid is equal to the preset angle.

[0089] Among them, the preset angle needs to be set according to actual needs and is not specifically limited here. It is understandable that the preset angle will affect the thickness of the fan-shaped simulation grid, that is, the larger the preset angle, the thicker the fan-shaped simulation grid, so it is necessary to select a suitable preset angle to ensure that based on the fan-shaped simulation grid, the amount of calculation can be reduced as much as possible while ensuring the accuracy of the simulation results.

[0090] It should be noted that, see Figure 3 , Figure 3 This is a schematic diagram of the photoresist spin coating process. The photoresist injection port is located directly above the center of the target wafer. After the spin coating starts, the photoresist will be ejected from the photoresist injection port at a certain speed and fall onto the target wafer. The substrate corresponding to the target wafer will rotate around the central axis at a certain rotation speed and spin-coat the photoresist onto the entire target wafer surface. Based on this, the length of the fan-shaped simulation grid is set to the radius of the target wafer, and the height of the fan-shaped simulation grid is set to the height of the photoresist injection port, which can lay the foundation for accurately capturing the flow characteristics of the photoresist.

[0091] Step S202: establishing an initial sector-shaped simulation grid based on a right-handed Cartesian coordinate system and grid parameters.

[0092] The parameter information of the target wafer includes the center coordinates; the center coordinates are the exact center coordinates of the target wafer.

[0093] Preferably, step S202, based on a right-handed Cartesian coordinate system and grid parameters, establishing an initial sector-shaped simulation grid comprises the following steps:

[0094] Step 1: Determine the origin of the right-handed Cartesian coordinate system based on the center coordinates of the target wafer.

[0095] Exemplarily, the center of the target wafer is determined according to the center coordinates of the target wafer, and the center of the target wafer is determined as the origin of a right-handed Cartesian coordinate system.

[0096] Step 2: Determine the rotational symmetry axis corresponding to the initial fan-shaped simulation grid according to the y-axis of the right-handed Cartesian coordinate system.

[0097] For example, see Figure 4 , based on the right-handed Cartesian coordinate system, the y-axis of the right-handed Cartesian coordinate system is used as the rotational symmetry axis corresponding to the initial fan-shaped simulation grid.

[0098] Step 3: Generate an initial fan-shaped simulation grid along the positive direction of the x-axis of the right-handed Cartesian coordinate system according to the grid parameters and the rotational symmetry axis.

[0099] The initial sector-shaped simulation grid is symmetrically distributed along the xy plane of the right-handed Cartesian coordinate system; and the photoresist injection port is arranged on a side of the initial sector-shaped simulation grid close to the rotational symmetry axis.

[0100] For example, see Figures 4 to 6 , the length of the grid parameters corresponding to the fan-shaped simulation grid is recorded as x1, the height is recorded as h, and the center angle is recorded as θ, and the initial fan-shaped simulation grid is generated along the positive direction of the x-axis of the right-handed Cartesian coordinate system; Figure 4 It can be seen that the rotational symmetry axis is on the positive half of the y-axis of the right-handed Cartesian coordinate system; Figure 5 It can be seen that the initial fan-shaped simulation grid is symmetrically distributed along the xy plane of the right-handed Cartesian coordinate system; Figure 6 It can be seen that the photoresist injection port is set on the side of the initial fan-shaped simulation grid close to the rotational symmetry axis, and the target wafer is on the xz plane of the right-handed Cartesian coordinate system; based on the grid parameters corresponding to the fan-shaped simulation grid, namely the length x1, height h and center angle θ, it can be determined that the coordinates of point P1 are (x1, 0, -x1*tan(θ / 2)), the coordinates of point P2 are (x2, 0, -x2*tan(θ / 2)), and the coordinates of P3 are (0, h, 0).

[0101] Step S203, meshing the initial sector-shaped simulation grid according to a preset partitioning rule to obtain a sector-shaped simulation grid.

[0102] The fan-shaped simulation grid includes a plurality of sub-grid units; the number of the sub-grid units gradually decreases along the positive direction of the x-axis of the right-handed Cartesian coordinate system.

[0103] Among them, the preset division rule needs to be set according to actual needs and is not specifically limited here. The preset division rule can be: the closer to the rotational symmetry axis, the finer the sub-grid unit division. It should be noted that the sub-grid unit is divided more finely at a position close to the rotational symmetry axis, which can effectively save computing resources on the basis of ensuring the accuracy of the simulation results.

[0104] For example, see Figures 4 to 6 Based on the initial sector simulation grid, the initial sector simulation grid is divided according to the preset division rules to obtain the sector simulation grid. Figures 4 to 6 It can be seen that the number of sub-grid units in the fan-shaped simulation grid gradually decreases along the positive direction of the x-axis of the right-handed Cartesian coordinate system.

[0105] In the present embodiment, based on the parameter information of the target wafer, the position information of the photoresist injection port and the preset angle, the grid parameters corresponding to the fan-shaped simulation grid can be accurately determined; then based on the grid parameters and the right-handed Cartesian coordinate system, the initial fan-shaped simulation grid can be accurately established; further, according to the preset division rules, the initial fan-shaped simulation grid is grid-divided to obtain the fan-shaped simulation grid, thereby avoiding the problem of high computational complexity caused by using a complete columnar space as a simulation grid, and effectively saving computing resources. At the same time, based on the fan-shaped simulation grid, it is helpful to quickly and accurately understand the photoresist flow phenomenon and trend, laying a foundation for improving the efficiency and accuracy of the photoresist spin coating process simulation.

[0106] In one embodiment, Figure 4 As shown, in the right-handed Cartesian coordinate system, the fan-shaped simulation grid includes a bottom surface, a front surface, a rear surface, an upper surface, and a right surface; the boundary conditions corresponding to the fan-shaped simulation grid are obtained, including:

[0107] The solid wall boundary condition is used as the boundary condition corresponding to the bottom surface of the sector-shaped simulation grid;

[0108] The wedge-shaped boundary conditions are used as the boundary conditions corresponding to the front and back surfaces of the fan-shaped simulation grid;

[0109] The atmospheric boundary conditions are used as the boundary conditions corresponding to the upper and right surfaces of the fan-shaped simulation grid.

[0110] Among them, the solid wall boundary condition is used to describe the behavior of the photoresist fluid when it contacts the solid wall, that is, the surface of the target wafer; the wedge boundary condition is applicable to axisymmetric problems and is used to simulate geometric structures with axisymmetry; the atmospheric boundary condition is used to simulate the situation where the fluid flows into or out of the calculation domain.

[0111] In this embodiment, by setting corresponding boundary conditions for each surface of the fan-shaped simulation grid, a data foundation is laid for realizing the photoresist spin coating process simulation.

[0112] In one embodiment, obtaining fluid properties corresponding to the two-phase fluid includes the following steps:

[0113] Step 1: Obtain a physical simulation model.

[0114] The physical simulation model is a laminar flow model. Laminar flow refers to the flow state of a fluid under low Reynolds number conditions, in which the fluid flow is orderly and smooth, and each fluid particle flows in a direction parallel to the boundary without obvious mixing or vortexing.

[0115] Step 2: Determine the fluid properties corresponding to the two-phase fluid based on the physical simulation model.

[0116] The two-phase fluid includes an air phase and a photoresist phase; the fluid properties corresponding to the air include a fluid viscosity model, a first dynamic viscosity, and a first density; the fluid properties corresponding to the photoresist include a fluid viscosity model, a second dynamic viscosity, a second density, and gravity. It can be understood that the first dynamic viscosity, the first density, the second dynamic viscosity, the second density, and gravity are all related to the fluid involved in the actual simulation, and the specific data need to be determined according to the actual results, and are not specifically limited here.

[0117] The fluid viscosity model includes a constant viscosity model; the constant viscosity model means that in the simulation of the photoresist spin coating process, the dynamic viscosity of the fluid is regarded as a constant and does not change with changes in temperature or pressure.

[0118] It should be noted that the photoresist spin coating process simulation method can be but is not limited to being implemented based on OpenFOAM software.

[0119] Exemplarily, when the photoresist spin coating process simulation is implemented based on OpenFOAM software, the physical property files required by the program are contained in the constant folder in OpenFOAM. In the momentumTransport file in OpenFOAM, the physical simulation model can be set to a laminar flow model; and then through the physical simulation model, the fluid properties corresponding to the two-phase fluid can be determined; for example, for the air phase: the fluid viscosity model is a constant viscosity model, that is, viscosityModel is constant, the first dynamic viscosity is α1, and the second density is β1; for the photoresist phase, the fluid viscosity model is a constant viscosity model, the second dynamic viscosity is α2, and the value of the second density is set to β2. At the same time, since the rotational symmetry axis is the y-axis of the right-handed Cartesian coordinate system, the gravity can be determined to be (0g 0); further, the surface tension coefficient between the two-phase fluid can also be determined to be γ.

[0120] In this embodiment, based on the physical simulation model, the fluid properties corresponding to the two-phase fluid are determined, which lays a data foundation for realizing the simulation of the photoresist spin coating process.

[0121] In one embodiment, Figure 7 As shown, Figure 7 The present invention is a flow chart of the steps of determining the simulation result of the photoresist spin coating process in one embodiment; the mathematical model of the two-phase flow fluid is iteratively solved according to the boundary conditions, fluid properties and the initial conditions of the process simulation by the target solver to determine the simulation result of the photoresist spin coating process, including the following steps:

[0122] Step S701, obtaining a target solver.

[0123] The target solver may be, but is not limited to, an interFoam solver.

[0124] Step S702, through the target solver, according to the boundary conditions, fluid properties and initial conditions of the process simulation, the two-phase flow fluid mathematical model is spatially discretized to obtain a linear system.

[0125] Step S703: preprocessing the linear system through a preprocessor to obtain a target linear system.

[0126] The preprocessor may be, but is not limited to, a geometricalgebraic multigrid solver (GAMG). GAMG is an efficient algorithm for accelerating the solution of linear equations, which combines the methods of geometrical multigrid and algebraic multigrid. This algorithm is particularly effective in solving large-scale linear systems because it can gradually reduce the residual error at different levels of grids, thereby reaching convergence faster.

[0127] Step S704, iteratively solving the target linear system through an iterative solver until the solution meets a preset convergence condition, thereby obtaining a simulation result of the photoresist spin coating process.

[0128] The iterative solver may be, but is not limited to, a preconditioned conjugate gradient solver (PCG); an iterative solver is a numerical method for solving a linear or nonlinear system of equations, and finds a solution by stepwise approximation.

[0129] Among them, the preset convergence conditions need to be set according to the actual solution requirements and are not specifically limited here.

[0130] It should be noted that GAMG, as a preprocessor, can improve the condition number of linear systems, thereby reducing the number of iterations of the iterative solver and speeding up the solution. After the PCG solver is combined with the preprocessor, it can process linear systems more stably and is suitable for large-scale problem processing.

[0131] The simulation results of the photoresist spin coating process include velocity field, pressure field and volume fraction. The velocity field is used to describe the velocity distribution of the photoresist at each point in space; the pressure field is used to describe the pressure distribution of the photoresist at each point in space; the volume fraction is used to describe the proportion of one phase in a two-phase fluid at a certain point in space.

[0132] Exemplarily, when the target solver is the interFoam solver, the two-phase flow fluid mathematical model is spatially discretized based on the interFoam solver using the finite volume method according to the boundary conditions, fluid properties, and initial conditions of the process simulation to obtain a linear system; the PIMPLE algorithm is used to couple the pressure and velocity fields to ensure that the momentum conservation and incompressibility conditions are met. Further, the GAMG preprocessor is used to preprocess the linear system to obtain the target linear system to improve the solution characteristics of the linear system and reduce the condition number of the system; further, the PCG iterative solver is used to solve the target linear system until the solution meets the preset convergence conditions to obtain the photoresist spin coating process simulation results.

[0133] Optionally, in another exemplary embodiment, a parallel computing method is adopted to iteratively solve the two-phase flow fluid mathematical model according to boundary conditions, fluid properties and initial conditions of process simulation through a target solver to determine the simulation results of the photoresist spin coating process, so as to further improve the efficiency of the photoresist spin coating process simulation.

[0134] In another exemplary embodiment, before obtaining the target solver, it is necessary to complete the parameter configuration of the target solver; the parameters may include but are not limited to the solver type, solution time step, output interval, time precision, and maximum Courant number; wherein the solution time step needs to be small enough to ensure numerical stability and precision; the output interval is used to determine the saving frequency of the simulation results; the time precision is used to control the convergence criterion of the solver within the time step; the maximum Courant number is used to control the relative size of the time step and the space step to ensure numerical stability.

[0135] In this embodiment, based on the target solver, the preprocessor and the iterative solver, the two-phase flow fluid mathematical model is iteratively solved until the solution meets the preset convergence conditions, and the simulation results of the photoresist spin coating process are obtained. This not only improves the calculation efficiency and shortens the calculation time, but also based on the preset convergence conditions, it can ensure the reliability and stability of the solution process, thereby obtaining accurate simulation results of the photoresist spin coating process.

[0136] In one embodiment, Figure 8 As shown, Figure 8 The schematic diagram of the process of generating a photoresist profile image in one embodiment; the photoresist spin coating process simulation method further includes the following steps:

[0137] Step S801, determining a photoresist distribution image according to a photoresist spin coating process simulation result.

[0138] In an exemplary embodiment, assuming that the initial rotation speeds of the target wafer are ω1, ω2, ω3, and ω4, four photoresist spin coating process simulations are performed to obtain four groups of photoresist spin coating process simulation results, respectively, to compare the performance of photoresist spin coating at different initial rotation speeds; further, according to the photoresist spin coating process simulation results, the corresponding photoresist distribution image can be determined, such as Fig. 9 shown.

[0139] It should be noted that the photoresist distribution image can be, but is not limited to, displayed after processing based on ParaView software. When ParaView software displays the photoresist distribution image, it is mainly completed through automated scripts. These scripts not only have powerful visualization functions, but also contain certain computing capabilities, which can effectively simplify the data processing process.

[0140] Step S802, performing contour extraction processing on the photoresist distribution image to obtain photoresist contour data.

[0141] Among them, the method for contour extraction processing of the photoresist distribution image can be: converting the photoresist distribution image into a grayscale image; performing image segmentation processing on the grayscale image according to a preset threshold to obtain a binary image; wherein the binary image includes a photoresist area and a background area; wherein the grayscale value corresponding to the pixel of the photoresist area is higher than the preset threshold; the grayscale value corresponding to the pixel of the background area is lower than or equal to the preset threshold; performing boundary pixel scanning processing on the binary image to determine the boundary data between the photoresist and the background; wherein the boundary data includes the coordinate values ​​of each pixel of the boundary; finally, the boundary data is used as the photoresist contour data. Among them, the preset threshold needs to be set according to actual needs and is not specifically limited here.

[0142] Step S803: generating a photoresist profile image based on the photoresist profile data.

[0143] Among them, the photoresist contour image can clearly show the distribution range and morphology of the photoresist on the wafer.

[0144] For example, for Fig. 9 The photoresist distribution images shown are respectively converted into four groups of corresponding grayscale images; the four groups of grayscale images are respectively subjected to image segmentation processing according to a preset threshold value to obtain binary images corresponding to each group; further, the four groups of binary images are respectively subjected to boundary pixel scanning processing to determine the boundary data between the photoresist and the background corresponding to each group; the boundary data is used as the photoresist contour data of the corresponding group; finally, based on the four groups of corresponding photoresist contour data, that is, the coordinate values ​​of each pixel at the boundary, a photoresist contour image is generated, as shown in FIG. Fig.10 shown.

[0145] It should be noted that the photoresist profile data can also be used for further analysis, such as calculating key parameters such as photoresist coverage area, thickness distribution, and uniformity, which are crucial for evaluating the quality of the spin coating process.

[0146] In this embodiment, by visualizing the corresponding photoresist spin-coating process simulation results, the corresponding photoresist distribution image can be obtained, so as to more intuitively understand the performance of photoresist spin-coating; then, by performing contour extraction processing on the photoresist distribution image, photoresist contour data is obtained; and based on the photoresist contour data, a photoresist contour image is generated, which intuitively presents the morphological transformation and distribution of the photoresist during the spin-coating process.

[0147] The above-mentioned photoresist spin coating process simulation method establishes a fan-shaped simulation grid based on the parameter information of the target wafer and the position information of the photoresist injection port, thereby avoiding the problem of high computational complexity caused by using a complete columnar space as a simulation grid, effectively saving computing resources, and at the same time, based on the fan-shaped simulation grid, it is helpful to quickly and accurately understand the photoresist flow phenomenon and trend, laying a foundation for improving the efficiency and accuracy of the photoresist spin coating process simulation. Furthermore, through the target solver, according to the boundary conditions, fluid properties and process simulation initial conditions corresponding to the fan-shaped simulation grid, the two-phase flow fluid mathematical model is iteratively solved, and the simulation results of the photoresist spin coating process can be accurately and efficiently obtained, which can greatly reduce the high cost and time consumption required by the traditional simulation method, making the adjustment and optimization of process parameters more efficient and flexible.

[0148] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0149] Based on the same inventive concept, the embodiment of the present application also provides a photoresist spin coating process simulation device for implementing the above-mentioned photoresist spin coating process simulation method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more photoresist spin coating process simulation device embodiments provided below can refer to the limitations of the photoresist spin coating process simulation method above, and will not be repeated here.

[0150] In an exemplary embodiment, Fig.11 As shown, a photoresist spin coating process simulation device is provided, including: a grid establishment module 1101, an acquisition module 1102, a model establishment module 1103 and a simulation result determination module 1104;

[0151] The grid establishment module 1101 is used to establish a fan-shaped simulation grid based on the parameter information of the target wafer and the position information of the photoresist injection port; the fan-shaped simulation grid is a fan-shaped space area in the cylindrical space; the cylindrical space is a space area enclosed by spatial extension with the surface of the target wafer as the bottom surface and the plane where the photoresist injection port is located as the top surface; the plane where the photoresist injection port is located is parallel to the surface of the target wafer;

[0152] An acquisition module 1102 is used to acquire boundary conditions corresponding to the sector simulation grid, fluid properties corresponding to the two-phase fluid, and initial conditions for process simulation;

[0153] Model building module 1103, used to build a two-phase flow fluid mathematical model;

[0154] The simulation result determination module 1104 is used to iteratively solve the two-phase flow fluid mathematical model according to the boundary conditions, fluid properties and process simulation initial conditions through the target solver to determine the photoresist spin coating process simulation results.

[0155] The above-mentioned photoresist spin coating process simulation device establishes a fan-shaped simulation grid based on the parameter information of the target wafer and the position information of the photoresist injection port, avoiding the problem of high computational complexity caused by using a complete columnar space as a simulation grid, effectively saving computing resources, and at the same time, based on the fan-shaped simulation grid, it helps to quickly and accurately understand the photoresist flow phenomenon and trend, laying a foundation for improving the efficiency and accuracy of the photoresist spin coating process simulation. Further, through the target solver, according to the boundary conditions, fluid properties and process simulation initial conditions corresponding to the fan-shaped simulation grid, the two-phase flow fluid mathematical model is iteratively solved, and the photoresist spin coating process simulation results can be accurately and efficiently obtained, which can greatly reduce the high cost and time consumption required by the traditional simulation method, making the adjustment and optimization of process parameters more efficient and flexible.

[0156] In one embodiment, the parameter information of the target wafer includes the radius; the position information of the photoresist injection port includes the height of the photoresist injection port; the grid establishment module 1101 is also used to

[0157] Based on the parameter information of the target wafer, the position information of the photoresist injection port and the preset angle, the grid parameters corresponding to the fan-shaped simulation grid are determined; the grid parameters include length, height and center angle; the length of the fan-shaped simulation grid is equal to the radius of the target wafer; the height of the fan-shaped simulation grid is equal to the height of the photoresist injection port; the center angle of the fan-shaped simulation grid is equal to the preset angle;

[0158] Based on the right-handed Cartesian coordinate system and grid parameters, an initial fan-shaped simulation grid is established;

[0159] According to a preset division rule, the initial sector simulation grid is grid-divided to obtain a sector simulation grid; the sector simulation grid includes a plurality of sub-grid units; the number of the sub-grid units gradually decreases along the positive direction of the x-axis of the right-handed Cartesian coordinate system.

[0160] In one embodiment, the parameter information of the target wafer includes the center coordinates; the grid establishment module 1101 is also used to

[0161] According to the center coordinates of the target wafer, the origin of the right-handed Cartesian coordinate system is determined;

[0162] According to the y-axis of the right-handed Cartesian coordinate system, the rotational symmetry axis corresponding to the initial fan-shaped simulation grid is determined;

[0163] According to the grid parameters and the rotational symmetry axis, an initial sector-shaped simulation grid is generated along the positive direction of the x-axis of the right-handed Cartesian coordinate system; the initial sector-shaped simulation grid is symmetrically distributed along the xy plane of the right-handed Cartesian coordinate system; and the photoresist injection port is set on a side of the initial sector-shaped simulation grid close to the rotational symmetry axis.

[0164] In one embodiment, in a right-handed Cartesian coordinate system, the fan-shaped simulation grid includes a bottom surface, a front surface, a rear surface, an upper surface, and a right side surface; the acquisition module 1102 is also used to

[0165] The solid wall boundary condition is used as the boundary condition corresponding to the bottom surface of the sector-shaped simulation grid;

[0166] The wedge-shaped boundary conditions are used as the boundary conditions corresponding to the front and back surfaces of the fan-shaped simulation grid;

[0167] The atmospheric boundary conditions are used as the boundary conditions corresponding to the upper and right surfaces of the fan-shaped simulation grid.

[0168] In one embodiment, the acquisition module 1102 is further configured to

[0169] Obtain a physical simulation model; the physical simulation model is a laminar flow model;

[0170] Based on the physical simulation model, the fluid properties corresponding to the two-phase fluid are determined; the two-phase fluid includes an air phase and a photoresist phase; the fluid properties corresponding to the air include a fluid viscosity model, a first dynamic viscosity, and a first density; the fluid properties corresponding to the photoresist include a fluid viscosity model, a second dynamic viscosity, a second density, and gravity.

[0171] In one embodiment, the simulation result determination module 1104 is further used to

[0172] Get the target solver;

[0173] Through the target solver, the mathematical model of two-phase flow is spatially discretized according to boundary conditions, fluid properties and initial conditions of process simulation to obtain a linear system;

[0174] The linear system is preprocessed by a preprocessor to obtain a target linear system;

[0175] The target linear system is iteratively solved by an iterative solver until the solution meets the preset convergence condition, and the simulation result of the photoresist spin coating process is obtained; the simulation result of the photoresist spin coating process includes velocity field, pressure field and volume fraction.

[0176] In one embodiment, the simulation result determination module 1104 is further used to

[0177] Determine a photoresist distribution image according to a photoresist spin coating process simulation result;

[0178] Performing contour extraction processing on the photoresist distribution image to obtain photoresist contour data;

[0179] A photoresist profile image is generated based on the photoresist profile data.

[0180] Each module in the above-mentioned photoresist spin coating process simulation device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0181] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.12As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Wherein, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Wherein, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data related to the simulation of the photoresist spin coating process. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for simulating the photoresist spin coating process is implemented.

[0182] Those skilled in the art will understand that Fig.12 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0183] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0184] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0185] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0186] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0187] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0188] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for simulating a photoresist spin coating process, characterized in that: The method comprises: Based on the parameter information of the target wafer and the position information of the photoresist injection port, a fan-shaped simulation grid is established; the fan-shaped simulation grid is a fan-shaped space area in the cylindrical space; the cylindrical space is a space area enclosed by spatial extension with the surface of the target wafer as the bottom surface and the plane where the photoresist injection port is located as the top surface; the plane where the photoresist injection port is located is parallel to the surface of the target wafer; Obtaining boundary conditions corresponding to the sector-shaped simulation grid, fluid properties corresponding to the two-phase fluid, and initial conditions for process simulation; Establish a mathematical model of two-phase flow; The target solver is used to iteratively solve the two-phase flow fluid mathematical model according to the boundary conditions, the fluid properties and the process simulation initial conditions to determine the photoresist spin coating process simulation results.

2. The method according to claim 1, characterized in that The parameter information of the target wafer includes a radius; the position information of the photoresist injection port includes a height of the photoresist injection port; and the sector-shaped simulation grid is established based on the parameter information of the target wafer and the position information of the photoresist injection port, including: Based on the parameter information of the target wafer, the position information of the photoresist injection port and the preset angle, the grid parameters corresponding to the fan-shaped simulation grid are determined; the grid parameters include length, height and center angle; the length of the fan-shaped simulation grid is equal to the radius of the target wafer; the height of the fan-shaped simulation grid is equal to the height of the photoresist injection port; the center angle of the fan-shaped simulation grid is equal to the preset angle; Based on a right-handed Cartesian coordinate system and the grid parameters, an initial sector-shaped simulation grid is established; According to a preset division rule, the initial sector-shaped simulation grid is grid-divided to obtain a sector-shaped simulation grid; the sector-shaped simulation grid includes a plurality of sub-grid units; the number of the sub-grid units gradually decreases along the positive direction of the x-axis of the right-handed Cartesian coordinate system.

3. The method according to claim 2, characterized in that The parameter information of the target wafer includes the center coordinates; the initial sector simulation grid is established based on the right-handed Cartesian coordinate system and the grid parameters, including: Determining the origin of a right-handed Cartesian coordinate system according to the center coordinates of the target wafer; Determine the rotational symmetry axis corresponding to the initial fan-shaped simulation grid according to the y-axis of the right-handed Cartesian coordinate system; According to the grid parameters and the rotational symmetry axis, an initial fan-shaped simulation grid is generated along the positive direction of the x-axis of the right-handed Cartesian coordinate system; the initial fan-shaped simulation grid is symmetrically distributed along the xy plane of the right-handed Cartesian coordinate system; the photoresist injection port is arranged on a side of the initial fan-shaped simulation grid close to the rotational symmetry axis.

4. The method according to claim 1, characterized in that: In a right-handed Cartesian coordinate system, the fan-shaped simulation grid includes a bottom surface, a front surface, a rear surface, an upper surface, and a right surface; and obtaining the boundary conditions corresponding to the fan-shaped simulation grid includes: Using the solid wall boundary condition as the boundary condition corresponding to the bottom surface of the fan-shaped simulation grid; Using wedge-shaped boundary conditions as boundary conditions corresponding to the front surface and the rear surface of the fan-shaped simulation grid; The atmospheric boundary conditions are used as boundary conditions corresponding to the upper surface and the right side surface of the sector-shaped simulation grid.

5. The method according to claim 1, characterized in that The obtaining of fluid properties corresponding to the two-phase fluid includes: Acquire a physical simulation model; the physical simulation model is a laminar flow model; Based on the physical simulation model, the fluid properties corresponding to the two-phase fluid are determined; the two-phase fluid includes an air phase and a photoresist phase; the fluid properties corresponding to the air include a fluid viscosity model, a first dynamic viscosity and a first density; the fluid properties corresponding to the photoresist include a fluid viscosity model, a second dynamic viscosity, a second density and gravity.

6. The method according to claim 1, characterized in that The method of iteratively solving the two-phase flow fluid mathematical model according to the boundary conditions, the fluid properties and the process simulation initial conditions by the target solver to determine the photoresist spin coating process simulation result includes: Get the target solver; By means of the target solver, the two-phase flow fluid mathematical model is spatially discretized according to the boundary conditions, the fluid properties and the process simulation initial conditions to obtain a linear system; Preprocessing the linear system by a preprocessor to obtain a target linear system; The target linear system is iteratively solved by an iterative solver until the solution meets a preset convergence condition, thereby obtaining a simulation result of a photoresist spin coating process; the simulation result of the photoresist spin coating process includes a velocity field, a pressure field and a volume fraction.

7. The method according to claim 1, characterized in that The method further comprises: Determining a photoresist distribution image according to the photoresist spin coating process simulation result; Performing contour extraction processing on the photoresist distribution image to obtain photoresist contour data; A photoresist profile image is generated based on the photoresist profile data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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