A simulation method for thermal and mechanical characteristics of semiconductor devices under multi-physical field action

Abstract

The application discloses a kind of simulation methods for the thermal characteristics of semiconductor device under the action of multiple physical fields, and relates to the field of semiconductor simulation.By obtaining the process structure parameters and material parameters of the semiconductor device, a two-dimensional cell structure model is constructed in the simulation software to simulate the heat source, then a three-dimensional multi-finger structure model of the semiconductor device is constructed according to the structural characteristics of the semiconductor device, the simulation object is expanded from a two-dimensional cell structure to a more complex three-dimensional multi-finger structure, the heat source obtained by simulating the two-dimensional cell structure is imported into the three-dimensional model for multi-physical field simulation, and the multi-physical field simulation results are analyzed thermodynamically.The application can simulate the interaction of multiple physical fields such as thermal field and stress field, and is used for multi-field coupling analysis under complex structure and environment, which can more comprehensively analyze the thermal characteristics of semiconductor device under the action of multiple physical fields, and provide more accurate simulation basis for optimizing device design, improving its performance and reliability in high voltage, high temperature and radiation environment.

Description

Technical Field

[0001] This invention relates to the field of semiconductor device technology, and more specifically to a method for simulating the thermodynamic characteristics of semiconductor devices under the influence of multiple physics fields. Background Technology

[0002] In modern power electronic devices, power semiconductor devices play a crucial role, with widespread applications in aerospace, communications, radar, and other fields. The application environment of semiconductors is typically very complex; devices are subjected to the combined effects of multiple physical fields during operation, including electric fields, temperature fields, and radiation fields. The coupling effects of these physical fields often lead to complex thermal distributions within the device, which has become a significant factor affecting its reliability and long-term stability. Currently, research on the thermodynamic core performance of semiconductor devices mainly relies on experimental and simulation methods. Experimental methods can provide a direct understanding of their thermodynamic performance, but the testing cycle is long, and it is difficult to understand changes in the thermal field at the microscopic level of the device. Therefore, simulation of semiconductor devices has become a major research direction.

[0003] Currently, many studies focus on the simulation of single physical fields of semiconductor devices, such as considering only electric or thermal fields. However, the application environment of semiconductors is usually very complex, and the simulation of single physical fields cannot fully reflect the complex thermo-mechanical coupling phenomena inside the device, nor can it fully analyze the thermal distribution of semiconductor devices under multi-physical field coupling conditions. In particular, the complex thermo-mechanical coupling phenomena inside the device are not accurately simulated in high-pressure, high-temperature and radiation environments.

[0004] Traditional simulation methods, such as using semiconductor simulation software like TCAD to analyze semiconductor devices, can perform detailed simulations of the device's electrical characteristics, such as electric field distribution, carrier transport, and electrothermal effects. Researchers can accurately analyze the electrical behavior of semiconductor devices under different operating conditions, especially for performance optimization under high voltage and radiation conditions. However, a significant limitation of TCAD is that it can only simulate the cellular structure of the device and cannot obtain the overall thermal distribution at the device level. Furthermore, TCAD's mechanical simulation capabilities are limited. In multi-field coupling simulations, it cannot simulate the distribution of stress and strain. For example, under the combined effects of high temperature, high pressure, or radiation, complex stress distributions may occur inside the semiconductor, and these mechanical properties cannot be directly simulated. It is difficult to reflect the thermo-mechanical coupling phenomena of the device under multi-physics fields, and it lacks simulation of the overall force field distribution of complex gate finger structures. These problems can lead to biases in the assessment of the long-term stability and reliability of the device. Summary of the Invention

[0005] To address the limitations of cellular model simulation under multi-physics environments, this invention provides a simulation method for the thermodynamic characteristics of semiconductor devices under multi-physics environments. This method can more comprehensively analyze the thermodynamic characteristics of semiconductor devices under multi-physics environments, providing more accurate simulation data for optimizing device design and improving their performance and reliability under high pressure, high temperature, and radiation environments.

[0006] To achieve the above objectives, the technical solution proposed in this invention is: a method for simulating the thermodynamic characteristics of semiconductor devices under the influence of multiple physics fields, comprising the following steps:

[0007] S1 constructs a meshed two-dimensional structural model using the semiconductor simulation software TCAD;

[0008] S2 adds an electrical simulation model to construct the electrical model of the device, and applies a bias voltage to the model to obtain the electrical characteristic curves.

[0009] The electrical characteristic curves of the S3 simulation model are compared with those in the actual device product manual to optimize the model;

[0010] S4 sets up a collision ionization model and sets the incident particle information parameters to construct a single-particle burn-up effect simulation model, and performs simulation.

[0011] Add a lattice heating model to S5 and input physical parameters to perform thermal effect analysis;

[0012] S6 constructs a three-dimensional multi-gate finger structure model of a semiconductor device in the finite element simulation software COMSOL based on the structural characteristics of the actual device, sets the corresponding material properties, and performs mesh generation on the three-dimensional structure model.

[0013] S7 sets boundary conditions in the thermal conduction and structural mechanics modules of the finite element simulation software COMSOL, adds a thermal expansion model in the multiphysics field, and simulates the thermal distribution of the device.

[0014] S8 performs thermodynamic analysis based on multiphysics simulation results.

[0015] Furthermore, step S1 specifically includes:

[0016] S11 obtains the process structure parameters of the actual semiconductor device;

[0017] S12 constructs a cellular structure model in TCAD based on the parameters of the actual semiconductor device;

[0018] S13 divides each region into grids to construct a gridded two-dimensional simulation structure model;

[0019] S14 defines the process structure and material parameters of each region and matches them with the structure of the device.

[0020] Specifically, the electrical simulation model in step S2 includes a mobility model, a carrier statistical model, and a recombination model, and the electrical characteristic curves include transfer characteristics, output characteristics, and breakdown characteristics.

[0021] Furthermore, in step S3, the electrical characteristic curves of the simulation model are compared with the electrical characteristic curves in the actual device product manual. The comparison results are obtained through the following steps:

[0022] If the error in the comparison results is within 20%, proceed to the next simulation step;

[0023] If the error of the comparison result exceeds 20%, the parameters of the two-dimensional simulation structure model in step S1 are optimized so that the electrical characteristic curve of the two-dimensional structure model matches the electrical characteristic curve of the actual device, and then the next step is carried out.

[0024] Specifically, the optimization includes key process parameters such as the substrate of the calibration device, the size of the epitaxial layer, and the doping concentration.

[0025] Specifically, in step S4, the incident particle information includes the incident position, incident angle, track width, linear charge deposition (LCD), peak time and width of the charge generation pulse.

[0026] Specifically, in step S5, the physical parameters include lattice thermal conductivity and specific heat capacity; the thermal effect analysis involves generating data on the change of thermal power density with time and location, and fitting this data to a Gaussian distribution function.

[0027] Specifically, the formula for the Gaussian distribution function is:

[0028] Where: Q(t) is a function of heat power density as a function of time, x is the abscissa of the heat source location, x(t) is a function of the abscissa of the heat source location as a function of time, and R is the radius of the heat source.

[0029] Specifically, in step S6, the three-dimensional model includes the gate, drain, source, channel layer, and substrate; the material properties include the density, thermal conductivity, specific heat capacity, Young's modulus, and coefficient of thermal expansion of GaN, AlGaN, and Si materials.

[0030] Specifically, step S7 includes: in the structural mechanics module, applying fixed constraints to the bottom of the model to limit the displacement of the bottom of the device; setting the initial temperature in the heat conduction module and inputting a Gaussian distribution function to simulate the heat distribution during the single-particle burn-out process of the device; simulating the stress distribution changes caused by a single-particle impact in the thermal expansion multiphysics field; observing the temperature and stress changes of each layer of material by setting multiple probes; and recording the dynamic evolution of temperature and stress during the single-particle burn-out process using a transient solver with a time step of picoseconds during the transient simulation.

[0031] Specifically, in step S8, the thermal effect analysis uses the temperature field distribution map, stress field distribution map, local overheating area and stress concentration area inside the device output by multiphysics simulation to analyze the thermal field distribution at the time of burn-out, the stress distribution during the temperature rise process, and the temperature and stress changes of different material layers.

[0032] The beneficial effects of this invention are:

[0033] 1. The range of thermal simulation has been expanded. By combining semiconductor simulation software TCAD with finite element simulation software COMSOL, the thermal distribution of semiconductor devices under the combined action of multiple physical fields (electric field, thermal field, stress field, etc.) can be accurately simulated, extending the simulation range from two-dimensional cellular structures to more complex three-dimensional multi-gate finger structures, thus improving the comprehensiveness of the simulation.

[0034] 2. The stress field analysis has been improved. By introducing the finite element simulation software COMSOL, the stress distribution of semiconductor devices under high temperature, high pressure and radiation conditions can be analyzed in detail. This solves the problem that the traditional semiconductor simulation software TCAD tool cannot handle the stress field distribution inside the device. This improvement provides technical support for avoiding potential failure problems caused by thermo-coupling effects.

[0035] 3. It can accurately simulate transient thermodynamic changes. In the process of transient thermodynamic changes caused by single-event effects, it can accurately simulate the heat distribution and stress changes of the device, and better show the instantaneous overheating and stress concentration phenomena in the single-event burn-off process. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation of the present invention. For those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0037] Figure 1This is a flowchart of the simulation method for the thermodynamic characteristics of semiconductor devices under the action of multiple physics fields according to the present invention;

[0038] Figure 2 This is a schematic diagram of the GaN HEMT device unit structure according to an embodiment of the present invention;

[0039] Figure 3 This is a simulated cell structure diagram of a GaN HEMT device according to an embodiment of the present invention;

[0040] Figure 4 This is a comparison chart of the transfer characteristic curves of GaN HEMT devices according to embodiments of the present invention;

[0041] Figure 5 The electric field distribution of the TCAD electrothermal distribution two-dimensional cloud map is shown in the embodiment of the present invention.

[0042] Figure 6 This is a two-dimensional cloud map of the electrothermal distribution and temperature field distribution in TCAD according to an embodiment of the present invention.

[0043] Figure 7 This is a Gaussian heat source according to an embodiment of the present invention;

[0044] Figure 8 This is a simulation model of the gate finger structure in an embodiment of the present invention;

[0045] Figure 9 The thermal field distribution and temperature field distribution at the moment of burnout in this embodiment of the invention;

[0046] Figure 10 This is the stress field distribution at the moment of burnout in an embodiment of the present invention;

[0047] Figure 11 The temperature variations of different material layers in embodiments of the present invention;

[0048] Figure 12 This illustrates the stress variations in different material layers in embodiments of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] like Figure 1 As shown, a specific embodiment of the simulation method for the thermodynamic characteristics of semiconductor devices under multiphysics fields according to the present invention includes the following steps:

[0051] Step S1: Construct a meshed two-dimensional structural model in the semiconductor simulation software TCAD:

[0052] First, obtain the process structure parameters of the actual semiconductor device;

[0053] Then, a cellular structure model is constructed in TCAD based on the parameters of the actual semiconductor device;

[0054] Then, the various regions are divided into grids to construct a gridded two-dimensional simulation structure model;

[0055] Finally, the process structure and material parameters of each region are defined and matched with the structure of the device.

[0056] Step S2: Add an electrical simulation model to the constructed two-dimensional simulation mechanism model to construct the electrical model of the device. Apply a bias voltage to the model to obtain the electrical characteristic curves. The electrical simulation model includes a mobility model, a carrier statistical model, and a recombination model. The electrical characteristic curves include transfer characteristics, output characteristics, and breakdown characteristics.

[0057] Step S3: Compare the electrical characteristic curves of the simulation model with those in the actual device's product manual to optimize the model. This is done by comparing the electrical characteristic curves of the simulation model with those in the actual device's product manual. If the error is within 20%, proceed to the next simulation step. If the error exceeds 20%, optimize the parameters of the two-dimensional simulation structure model from Step S1, including optimizing key process parameters such as the substrate, epitaxial layer size, and doping concentration of the calibration device, so that the electrical characteristic curves of the two-dimensional structure model match those of the actual device before proceeding to the next step.

[0058] Step S4: Set up the collision ionization model and set the incident particle information parameters to construct a single-particle burn-up effect simulation model for simulation. The incident particle information includes the incident position, incident angle, track width, linear charge deposition (LCD), peak time and width of the charge generation pulse.

[0059] Step S5: Add a lattice heating model to the two-dimensional structure model, input physical parameters for thermal effect analysis, including lattice thermal conductivity and specific heat capacity; the thermal effect analysis generates data on the variation of heat power density with time and location, and fits this data to a Gaussian distribution function to represent the Gaussian heat source distribution, with the formula:

[0060] Where: Q(t) is a function of heat power density as a function of time, x is the abscissa of the heat source location, x(t) is a function of the abscissa of the heat source location as a function of time, and R is the radius of the heat source.

[0061] Step S6: Based on the structural characteristics of the actual device, construct a three-dimensional model of the semiconductor device with a multi-gate finger structure in the finite element simulation software COMSOL, set the corresponding material properties, and mesh the three-dimensional model.

[0062] The three-dimensional model includes the gate, drain, source, channel layer, and substrate; the material properties include the density, thermal conductivity, specific heat capacity, Young's modulus, and coefficient of thermal expansion of GaN, AlGaN, and Si materials.

[0063] Step S7: Set boundary conditions in the thermal conduction and structural mechanics modules of the finite element simulation software COMSOL, add a thermal expansion model in the multiphysics field, and simulate the thermal distribution of the device. Specifically: in the structural mechanics module, apply fixed constraints to the bottom of the model to limit the displacement of the bottom of the device; in the thermal conduction module, set the initial temperature and input a Gaussian distribution function to simulate the thermal distribution of the device during single-particle burn-out; simulate the stress distribution changes caused by single-particle impact in the thermal expansion multiphysics field; observe the temperature and stress changes of each layer of material by setting multiple probes; in the transient simulation, the time step is on the picosecond level, and the dynamic evolution of temperature and stress during single-particle burn-out is recorded by the transient solver.

[0064] Step S8: Perform thermodynamic analysis based on the multiphysics simulation results. Specifically, the thermal effect analysis uses the temperature field distribution map, stress field distribution map, local overheating area and stress concentration area output by the multiphysics simulation to analyze the thermal field distribution at the time of burn-out, the stress distribution during the temperature rise process, and the temperature and stress changes of different material layers.

[0065] This invention provides a specific simulation implementation example to describe the simulation process in detail.

[0066] In this embodiment, the semiconductor device is a p-GaN gate structure GaN-based HEMT device, such as... Figure 2 The p-GaN gate structure GaN-based HEMT device shown is a lateral planar structure, with its gate, source, and drain located on the same plane.

[0067] like Figure 3 The cell structure shown is used for simulating GaN HEMT devices. The lateral width of the cell structure is 11 μm, the thickness of p-GaN is 0.07 μm, the thickness of AlGaN layer is 15 nm, the thickness of channel layer is 0.2 μm, and the thickness of buffer layer is 2 μm.

[0068] Based on the design and process parameters of the GaN HEMT device mentioned above, a two-dimensional modeling tool for semiconductor devices (semiconductor simulation software TCAD) is used to model the GaN HEMT device to be simulated, thereby obtaining a two-dimensional model of the device. Then, the established two-dimensional model is meshed to generate a meshed device structure. The process structure and material parameters of each region in the two-dimensional model are defined, and the mesh structure is matched with the structure of the device to effectively ensure the accuracy and computational efficiency of the simulation.

[0069] An electrical simulation model, including a mobility model, a carrier statistical model, and a recombination model, is added to the constructed two-dimensional structure model of the GaN HEMT device. A suitable bias voltage is applied to the device structure model for TCAD device electrical simulation. Appropriate voltages are applied to the source and drain of the device model to obtain typical electrical parameters or curves such as the transfer characteristic curve and the output characteristic curve of the device. The device electrical simulation results are then compared with the electrical parameters or curves measured experimentally. If the deviation is within 20%, it is considered to be consistent, and the next simulation can be carried out directly. If the deviation exceeds 20%, it is considered to be inconsistent. In this case, the parameters defined when constructing the two-dimensional structure model of the device are optimized, and key process parameters such as the substrate, epitaxial layer size, and concentration are optimized and calibrated. Finally, the electrical simulation results are made consistent with the experimental measurements before the next simulation is carried out.

[0070] like Figure 4 The comparison between the simulated and actual measured values ​​of the GaN HEMT device transfer characteristic curves shown indicates that the electrical simulation curves and the measured curves are in good agreement, with a deviation of less than 20%, ensuring the accuracy of the model and the reliability of subsequent simulation results.

[0071] The optimized GaN HEMT device electrical simulation model is used to establish a collision ionization model. Information parameters of the incident particles are defined using assembly language, including the particle's incident position, angle, track width, linear charge deposition (LCD), peak time and width of the charge generation pulse. A single-event burn-out (SEB) model is then established for the GaN HEMT device, with the device's bias voltage V... GS Set to 0V, drain-source voltage V DS The voltage was set to 220V, the heavy ion LCD value was 0.8pC / μm, and the operating temperature was set to 300K. Single-event burn-off simulation was performed by vertically incident light through the entire device from the part most sensitive to single-event burn-off (gate-drain spacing 0.5μm).

[0072] like Figure 5 and Figure 6 As shown, the distribution of electric and temperature fields at different times was obtained through simulation, demonstrating the electrothermal distribution cloud map during single-particle burn-up.

[0073] A lattice heating model is introduced into the simulation of single-event burn-off effects. This model simulates the thermal effects on the lattice of the device material when a particle is incident. By inputting appropriate physical parameters, including lattice thermal conductivity and specific heat capacity, the heat conduction process inside the device during single-event burn-off can be described more realistically.

[0074] like Figure 7 As shown, after the single-event burn-out effect simulation, the data on the change of thermal power density with time and location are output from TCAD and fitted to a Gaussian distribution function to represent the Gaussian heat source distribution. The formula is as follows:

[0075] Where: Q(t) is a function of heat power density as a function of time, x is the abscissa of the heat source location, x(t) is a function of the abscissa of the heat source location as a function of time, and R is the radius of the heat source.

[0076] The Gaussian distribution function acts as a heat source load in transient simulations, which can more accurately reproduce the thermal diffusion behavior after particle impact.

[0077] like Figure 8 As shown, a three-dimensional model of a GaN HEMT device with a multi-gate structure was constructed in the finite element simulation software COMSOL. The model consists of five cells intersected by an interpolation structure, and the overall size of the model is 53μm×260μm×3.415μm. The multi-gate structure can better reflect the heat conduction path of the device when it is subjected to local particle impacts, which helps to analyze the local burn-out characteristics and stress changes of the GaNHEMT device when a single-event burn-out effect occurs.

[0078] In this embodiment, the channel layer and buffer layer are combined during the modeling process. Both layers are made of GaN material and have similar physical properties. Material parameters are set for each component of the GaN HEMT device, including density, specific heat capacity, thermal conductivity, coefficient of thermal expansion, and elastic modulus (Young's modulus). The established three-dimensional model is meshed. The AlGaN barrier layer, GaN layer, and SiC substrate layer of the model are divided into hexahedral meshes by sweeping, with a maximum cell size of 0.15 μm. The remaining parts use free tetrahedral meshes. The average cell mass of the mesh is 0.8138, which achieves a high quality and meets the simulation accuracy requirements.

[0079] Boundary conditions were added to the heat conduction and structural mechanics modules to perform single-particle burn-off thermal simulation. Specifically, in the heat conduction module, the initial temperature was set to 300K, corresponding to the starting temperature in TCAD, and the Gaussian distribution function obtained from the analysis was applied as a heat source load to the intermediate cell between the gate and drain to simulate the heat distribution during the single-particle burn-off effect. In the structural mechanics module, a fixed constraint was applied to the bottom of the model to limit the displacement of the bottom of the device, ensuring that there would be no free expansion or structural deformation at the bottom during heat conduction, so as to accurately simulate the thermal stress distribution under the single-particle burn-off effect. At the same time, a thermal expansion multiphysics field was added to the 3D model to simulate the stress distribution change caused by the single-particle impact, ensuring accurate coupling between the multiphysics fields. Multiple probes were added to observe the temperature and stress change process of each layer of material. During the transient simulation, a picosecond-level time step was used to record the dynamic evolution of temperature and stress during the single-particle burn-off process through the transient solver, which can capture the heat diffusion path and the formation of stress concentration areas, ensuring that the simulation data fully reflects the transient response characteristics inside the device.

[0080] After the multiphysics simulation is completed, the temperature field and stress field distribution maps of the GaN HEMT device are output based on the multiphysics simulation results, especially the local overheating area and stress concentration area inside the device. The thermal field distribution at the time of burn-out is analyzed, including the temperature field distribution and stress field distribution. The temperature and stress changes of different material layers are also analyzed, including temperature changes and stress changes.

[0081] like Figure 9 The temperature field distribution at the moment of burnout is shown. A transient high-temperature region is generated at the point of single-particle impact. Initially, the temperature is concentrated near the gate, and then the high-temperature region moves towards the drain, and the temperature continues to rise.

[0082] like Figure 10 The stress field distribution at the moment of burning is shown. As the temperature gradually rises, due to the different thermal expansion coefficients of the materials, stress first appears near the channel, and then the stress concentrates in the high-temperature area until it burns out.

[0083] like Figure 11 The temperature change curves of the different material layers are shown. Figure 12 The stress variation curves of different material layers shown indicate that GaN and AlGaN have the highest temperatures during single-particle burn-out, followed by the drain metal electrode, while the Si substrate has the lowest temperature. The maximum stress occurs in AlGaN, followed by the metal electrode, and then GaN.

[0084] This embodiment constructs a simulation model of a GaN HEMT device with a multi-gate finger structure by combining the semiconductor simulation software TCAD and the finite element simulation software COMSOL. COMSOL simulates the interaction of multiple physical fields, including thermal and stress fields, for multi-field coupling analysis under complex structures and environments. By importing the electrothermal (Joule heating) results obtained from the TCAD simulation into the COMSOL 3D model, the simulation object is extended from a two-dimensional cellular structure to a more complex three-dimensional multi-gate finger structure. This allows for a more comprehensive analysis of the thermodynamic characteristics of the GaN HEMT device under multi-physics conditions, better capturing local hot spots and stress concentration areas within the GaN HEMT device, and providing more accurate simulation data for optimizing device design and improving its performance and reliability under high pressure, high temperature, and radiation environments.

[0085] Although preferred embodiments of the present invention have been described above in conjunction with the accompanying drawings, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not limiting. Those skilled in the art can make many specific modifications under the guidance of the present invention without departing from the spirit of the invention and the scope of protection of the claims, and these modifications all fall within the scope of protection of the present invention.

Claims

1. A method for simulating thermal and mechanical characteristics of a semiconductor device under the action of multiple physical fields, characterized in that, The method comprises the following steps: S1 constructing a grid two-dimensional structure model in semiconductor simulation software TCAD; S2 adding an electrical simulation model, constructing an electrical model of the device, and applying a bias voltage to the model to obtain an electrical characteristic curve; S3 comparing the electrical characteristic curve of the simulation model with an electrical characteristic curve in an actual device product manual to optimize the model; S4 setting a collision ionization model and setting incident particle information parameters to construct a single particle burnout effect simulation model and perform simulation simulation; S5 adding a lattice heating model and inputting physical parameters to perform thermal effect analysis; S6 constructing a three-dimensional multi-gate finger structure model of the semiconductor device in finite element simulation software COMSOL according to the structure characteristics of the actual device, setting corresponding material properties, and performing grid division on the three-dimensional structure model; S7 setting boundary conditions in the thermal conduction module and structural mechanics module of the finite element simulation software COMSOL, adding a thermal expansion model in the multi-physical field, and performing simulation simulation on the thermal force distribution of the device; S8 performing thermodynamic analysis according to the simulation results of the multi-physical field.

2. The method of claim 1, wherein, The step S1 specifically comprises: S11 obtaining process structure parameters of an actual semiconductor device; S12 constructing a cell structure model in TCAD according to the parameters of the actual semiconductor device; S13 performing grid division on each region to construct a grid two-dimensional simulation structure model; S14 defining the process structure and material parameters of each region and matching them with the structure of the device.

3. The method of claim 1, wherein the method further comprises: The electrical simulation model in the step S2 comprises a mobility model, a carrier statistics model and a recombination model, and the electrical characteristic curve comprises a transfer characteristic, an output characteristic and a breakdown characteristic.

4. The method of claim 1, wherein, In the step S3, the electrical characteristic curve of the simulation model is compared with the electrical characteristic curve in the actual device product manual, and the comparison result is as follows: If the error is within 20%, the next step is simulated; If the error exceeds 20%, the parameters of the two-dimensional simulation structure model in the step S1 are optimized to make the electrical characteristic curve of the two-dimensional structure model consistent with the electrical characteristic curve of the actual device, and then the next step is performed.

5. The method of claim 4, wherein the method further comprises: The optimization comprises calibrating the substrate, epitaxial layer size and doping concentration of the device.

6. The method of claim 1, wherein, In the step S4, the incident particle information comprises an incident position, an incident angle, a track width, a linear charge deposition (LCD), a peak time and a width of a charge generation pulse.

7. The method of claim 1, wherein, In the step S5, the physical parameters comprise lattice thermal conductivity and specific heat capacity; and the thermal effect analysis is to generate data of thermal power density changing with time and position, and fit the data into a Gaussian distribution function.

8. The method of claim 7, wherein the method further comprises: The formula of the Gaussian distribution function is: where: Q(t) is the heat power density as a function of time, x is the heat source position in the transverse coordinate, x(t) is the heat source position in the transverse coordinate as a function of time, and R is the heat source radius.

9. The method of claim 1, wherein, In the step S6, the three-dimensional model comprises a gate, a drain, a source, a channel layer and a substrate; and the material properties comprise the density, thermal conductivity, specific heat capacity, Young's modulus and thermal expansion coefficient of GaN, AlGaN and Si materials.

10. The method of claim 1, wherein, The step S7 specifically includes: in the structural mechanics module, a fixed constraint is applied to the bottom of the model to limit the displacement of the bottom of the device; in the heat conduction module, an initial temperature is set and a Gaussian distribution function is input to simulate the thermal distribution of the device during the single particle burnout process; the stress distribution change caused by the single particle hit is simulated in the thermal expansion multi-physics field; the temperature and stress change process of each layer of material is observed through multiple probes; and in the transient simulation process, the time step is picosecond level, and the dynamic evolution process of temperature and stress during the single particle burnout process is recorded through the transient solver.

11. The method of claim 1, wherein, In the step S8, the thermal effect analysis is performed through the temperature field distribution diagram, the stress field distribution diagram, the local overheating area and the stress concentration area in the device output by the multi-physics field simulation, the thermal force field distribution at the burnout moment, the stress distribution during the temperature rising process, and the temperature and stress changes of different material layers.

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