A simulation method for seeking the best parameters of depositing and growing semiconductor gallium arsenide film

Abstract

The application provides a simulation method for seeking optimal parameters of deposition growth of a semiconductor gallium arsenide film, and comprises the following steps: S1, a simulation model of a gallium arsenide substrate with a certain roughness is established by using Lammps and Material Studio material simulation software, the surface roughness of the model simulates a gallium arsenide crystal which is difficult to exist in a single crystal state in reality, and a surface rough model is added according to specific conditions, and a fixed region is divided in the model to be fixed to achieve the purpose of a stable base. The simulation method for seeking optimal parameters of deposition growth of a semiconductor gallium arsenide film provided by the application can overcome the difficulty of high cost and long time in experiments by using Material Studio software, Lammps open source software, VESTA software, Ovito visualization software and Origin data processing software, and can make up for the shortage that the motion track and internal structure change of a single atom in the atomic growth process are difficult to observe in the experimental process.

Description

Technical Field

[0001] This invention relates to the field of molecular simulation methods, and in particular to a simulation method for seeking the optimal parameters for the deposition and growth of gallium arsenide thin films. Background Technology

[0002] Gallium arsenide (GaAs) is a second-generation semiconductor material with superior properties such as high electron mobility, direct bandgap transition, low dielectric constant, and large bandgap. Metal-semiconductor field-effect transistors (MOSFETs) and high-mobility transistors (HMTs) based on GaAs crystals play an irreplaceable role in aerospace, mobile communications, and new energy industries, where they are not as readily available as silicon or germanium devices. GaAs thin films have a bright future and a considerable market share. In recent years, Schottky barrier diodes and solar cells produced using GaAs thin films have been widely used in integrated circuits and the solar energy industry.

[0003] In the field of crystal growth simulation, most research focuses on the growth of thin films on third-generation semiconductors such as silicon carbide using heteroepitaxial gallium arsenide and gallium arsenide as substrates. However, heteroepitaxial growth may have problems such as lattice mismatch and thermal adaptation that affect the growth of thin films. In the experimental process of preparing gallium arsenide thin films, it is difficult to observe the internal structural changes and the movement trajectory of individual atoms during the atomic growth process. Molecular dynamics simulation can explore the changes of crystals in depth from a microscopic perspective and is widely used to study the growth of materials. However, such experiments are costly and time-consuming, and it is difficult to observe the movement trajectory of individual atoms and the changes in internal structure during the atomic growth process.

[0004] Therefore, it is necessary to provide a simulation method for seeking the optimal parameters for the deposition and growth of gallium arsenide thin films in semiconductors to solve the above-mentioned technical problems. Summary of the Invention

[0005] This invention provides a simulation method for seeking the optimal parameters for the deposition and growth of gallium arsenide semiconductor thin films, which solves the problems of high experimental costs, long experimental time, and difficulty in observing the movement trajectory and internal structural changes of individual atoms during the atomic growth process.

[0006] To address the aforementioned technical problems, this invention provides a simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films, comprising the following steps:

[0007] S1. Use Lammps and Material Studio material simulation software to establish a gallium arsenide substrate simulation model with a certain roughness. The surface roughness simulates gallium arsenide crystals that are difficult to exist in a single crystal state in reality. The surface roughness model is added according to the specific situation. Fixed areas are divided in the model for fixation to achieve the purpose of stabilizing the substrate.

[0008] S2. Set environmental parameters such as ensemble, time step, boundary conditions, and initial temperature of the simulation substrate model created in S1 to prepare the environment for subsequent atomic deposition.

[0009] S3. Based on S2, the simulation system is further optimized by minimizing energy, minimizing temperature, setting relaxation time, and setting potential function. In the selection of potential function, the Tersoff many-body potential function proposed by Albe is used to improve the accuracy of simulation calculation.

[0010] S4. Using the molecular dynamics simulation software Lammps, set deposition parameters such as the number of atoms and the time interval between the release atoms in the established simulation model; by changing the deposition rate and the incident angle of the deposited atoms, etc., the incident conditions are changed to deposit multiple thin films, and different substrate temperatures are set to obtain crystalline gallium arsenide thin films with different structures.

[0011] S5. Various analytical methods, such as radial distribution function, surface roughness density, crystal structure identification, and dislocation identification, are used to analyze the changes in the surface and internal structure of the deposited thin film, and the results are used to guide the experiment.

[0012] Preferably, the establishment of the gallium arsenide substrate simulation model in S1 includes the following steps: using the "Supercell" function of Material Studio software to expand the gallium arsenide cell, the resulting gallium arsenide cube has a size of 10.1×10.1×6.3nm3, and fixing 4 layers of atoms at the bottom of the substrate to be unaffected by temperature and stress, thus achieving the effect of fixing the substrate; using the software Lammps to create spherical protrusions and depressions on the surface of the established cube, wherein the command is as follows: region 40sphere 15.5477 77.7384 63.6041 7 units box delete_atoms region 40 create_atoms region 40.

[0013] Preferably, in S2, the environmental parameters such as the potential function of the simulation model of the deposition substrate established in S1 are set as follows: Write an IN file to set the boundary conditions of the x-axis and y-axis in the deposition box to be periodic boundaries and the z-axis to be aperiodic boundaries. The specific setting command is as follows: boundary ppf #p is a periodic boundary; Set the ensemble, time step, temperature initialization, etc. of the simulation model. The specific setting command is as follows: fix 1all nvt temp 800.0 800.0 100.0 #ensemble settings run 300000 #time step velocity other create 298 39849 mom yes rot yes distgaussian #temperature initialization.

[0014] Preferably, the specific operation for environmental optimization of the simulation model in S3 is as follows: using the Tersoff multibody potential function proposed by Albe to improve the accuracy of simulation calculation, the specific setting command is as follows: pair_style tersoff pair_coeff **GaAs.tersoff Ga As #force field setting; the specific command for minimizing the energy of the system is as follows: min_style cg minimize 1e-8 1e-8 10000 10000.

[0015] Preferably, in S4, the deposition parameters of the deposition simulation model established in S1 are set as follows: The relevant deposition commands are as follows: fix 2all deposit 6000 1 1500 95485 region sput near 1 vz-50 -50 units box fix 3 all deposit 6000 2 1500 95485 region sput near 2 vz-50-50units box.

[0016] Preferably, in step S5, microstructure characterization methods such as radial distribution function, surface roughness calculation, and visualization analysis are used to analyze the obtained thin film surface data. The focus is on calculating thin film quality parameters such as surface roughness and density, and the calculation results can effectively guide experimental analysis.

[0017] Preferably, when using the molecular dynamics simulation software Lammps in S4, a display screen is used. A rotating block is fixedly installed at the bottom of the display screen, and a second rotating seat is rotatably connected to the outer side of the rotating block. One end of the second rotating seat is slidably connected to the inner side of the fixed frame. A toothed plate is fixedly installed on the back of the display screen, and a pull block is fixedly installed on the top of the display screen.

[0018] Preferably, the inner side of the fixed frame is provided with sliding grooves on both sides, and the inner side of the sliding groove is slidably connected to a limiting block, which is fixedly installed on both sides of the slider.

[0019] Preferably, a rubber pad is fixedly installed at the bottom of the fixed frame, and a first rotating seat is fixedly installed at the top of the fixed frame. A support plate is rotatably connected inside the first rotating seat, and one end of the support plate is engaged with the inner side of the toothed plate.

[0020] Preferably, buffer pads are fixedly installed on three sides of the fixed frame.

[0021] Compared with related technologies, the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided by this invention has the following advantages:

[0022] This invention provides a simulation method for seeking the optimal parameters for the deposition and growth of gallium arsenide semiconductor thin films. Using Material Studio software, Lammps open-source software, VESTA software, Ovito visualization software, and Origin data processing software, the molecular dynamics simulation method overcomes the difficulties of high cost and long time in experiments, and makes up for the lack of observation of the motion trajectory and internal structural changes of individual atoms during the atomic growth process in experiments. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the structure of a first embodiment of a simulation method for seeking optimal parameters for depositing and growing gallium arsenide thin films provided by the present invention;

[0024] Figure 2 for Figure 1 The diagram shows the gallium arsenide thin film deposition and growth process.

[0025] Figure 3 for Figure 1 The surface density curves and surface roughness curves are shown for different incident angles and incident velocities.

[0026] Figure 4 for Figure 1 The surface roughness and density curves before and after annealing at different incident angles are shown.

[0027] Figure 5 for Figure 1 The three-dimensional waterfall plot of the radial distribution function before and after annealing versus time is shown.

[0028] Figure 6 for Figure 1 The morphology and crystallinity of the deposited thin film vary with substrate temperature.

[0029] Figure 7 for Figure 1 The dislocation perspective view of the deposited thin film at five incident angles under different substrate temperatures is shown.

[0030] Figure 8 This is a schematic diagram of the structure of a second embodiment of a simulation method for seeking optimal parameters for depositing and growing gallium arsenide thin films provided by the present invention;

[0031] Figure 9 for Figure 8 The diagram shows the side structure of the fixed frame.

[0032] Figure 10 for Figure 8 The diagram shows a cross-sectional view of the fixed frame structure.

[0033] Figure 11 This is a schematic diagram of the third embodiment of a simulation method for seeking optimal parameters for depositing and growing gallium arsenide thin films, provided by the present invention.

[0034] The following are the labels in the diagram: 1. Fixed frame, 11. Slide groove, 12. Rubber pad, 2. First rotating seat, 21. Support plate, 3. Slider, 31. Limiting block, 32. Second rotating seat, 33. Rotating block, 34. Display screen, 35. Pull block, 36. Toothed plate, 4. Buffer pad. Detailed Implementation

[0035] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0036] First Embodiment

[0037] Please refer to the following: Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 ,in, Figure 1 This is a schematic diagram of the structure of a first embodiment of a simulation method for seeking optimal parameters for depositing and growing gallium arsenide thin films provided by the present invention; Figure 2 for Figure 1 The diagram shows the gallium arsenide thin film deposition and growth process. Figure 3 for Figure 1 The surface density curves and surface roughness curves are shown for different incident angles and incident velocities. Figure 4 for Figure 1 The surface roughness and density curves before and after annealing at different incident angles are shown. Figure 5 for Figure 1 The three-dimensional waterfall plot of the radial distribution function before and after annealing versus time is shown. Figure 6 for Figure 1 The morphology and crystallinity of the deposited thin film vary with substrate temperature. Figure 7 for Figure 1 The diagram shows dislocation perspective views of deposited thin films at five incident angles under different substrate temperatures. A simulation method for seeking optimal parameters for the deposition and growth of gallium arsenide semiconductor thin films includes the following steps:

[0038] S1. Use Lammps and Material Studio material simulation software to establish a gallium arsenide substrate simulation model with a certain roughness. The surface roughness simulates gallium arsenide crystals that are difficult to exist in a single crystal state in reality. The surface roughness model is added according to the specific situation. Fixed areas are divided in the model for fixation to achieve the purpose of stabilizing the substrate.

[0039] S2. Set environmental parameters such as ensemble, time step, boundary conditions, and initial temperature of the simulation substrate model created in S1 to prepare the environment for subsequent atomic deposition.

[0040] S3. Based on S2, the simulation system is further optimized by minimizing energy, minimizing temperature, setting relaxation time, and setting potential function. In the selection of potential function, the Tersoff many-body potential function proposed by Albe is used to improve the accuracy of simulation calculation.

[0041] S4. Using the molecular dynamics simulation software Lammps, set deposition parameters such as the number of atoms and the time interval between the release atoms in the established simulation model; by changing the deposition rate and the incident angle of the deposited atoms, etc., the incident conditions are changed to deposit multiple thin films, and different substrate temperatures are set to obtain crystalline gallium arsenide thin films with different structures.

[0042] S5. Various analytical methods, such as radial distribution function, surface roughness density, crystal structure identification, and dislocation identification, are used to analyze the changes in the surface and internal structure of the deposited thin film, and the results are used to guide the experiment.

[0043] The establishment of the gallium arsenide substrate simulation model in S1 includes the following steps: using the "Supercell" function of Material Studio software to expand the gallium arsenide cell, the resulting gallium arsenide cube has a size of 10.1×10.1×6.3nm3, and fixing 4 layers of atoms at the bottom of the substrate to prevent them from being affected by temperature and stress, thus achieving the effect of fixing the substrate; using the software Lammps to create spherical protrusions and depressions on the surface of the cube, the command is as follows: region 40sphere 15.5477 77.7384 63.6041 7 units box delete_atoms region 40 create_atoms region 40.

[0044] In S2, the environmental parameters such as the potential function of the simulation model of the deposition substrate established in S1 are set as follows: Write an IN file to set the x-axis and y-axis boundary conditions in the deposition box to periodic boundaries and the z-axis to a non-periodic boundary. The specific setting command is as follows: boundary ppf #p is a periodic boundary; Set the ensemble, time step, and temperature initialization of the simulation model. The specific setting commands are as follows: fix 1 all nvt temp 800.0 800.0 100.0 #ensemble settings run300000 #time step velocity other create 298 39849 mom yes rot yes dist gaussian #temperature initialization.

[0045] The specific operations for environmental optimization of the simulation model in S3 are as follows: The Tersoff multibody potential function proposed by Albe is used to improve the accuracy of the simulation calculation. The specific setting command is as follows: pair_style tersoff pair_coeff **GaAs.tersoff Ga As # Force field setting; The specific command for minimizing the energy of the system is as follows: min_style cg minimize 1e-8 1e-8 10000 10000.

[0046] In S4, the deposition parameters of the deposition simulation model established in S1 are set as follows. The relevant deposition commands are as follows: fix 2 all deposit 6000 1 1500 95485 region sput near 1 vz-50-50units box fix 3 all deposit 6000 2 1500 95485 region sput near 2 vz-50 -50units box.

[0047] In step S5, microstructure characterization methods such as radial distribution function, surface roughness calculation, and visualization analysis are used to analyze the obtained thin film surface data. The focus is on calculating thin film quality parameters such as surface roughness and density; the calculation results can effectively guide experimental analysis.

[0048] With the aim of obtaining gallium arsenide (GaAs) thin films with excellent physical properties, this invention simulates the homoepitaxial growth behavior of GaAs thin films on GaAs substrates under different incident conditions using molecular dynamics simulations. Optimal thin films and deposition parameters are derived through computational analysis of GaAs thin films deposited under different incident conditions to guide experiments. This invention utilizes a high-density simulation and computing server with 1152 cores based on optical interconnects, with a theoretical peak calculation capacity of 23 trillion calculations per second. It is mainly used for large-scale molecular dynamics simulations, calculation of material electrical properties, and simulation of electronic device structures. The internal structure of the deposited thin film was studied using the "Defect Analysis Technology (DXA)" and "Diamond Structure Identification" features of the open-source software OVITO. Furthermore, by combining surface roughness and radial distribution function, the influence of As8 clusters on the surface morphology and internal structure of GaAs thin films under different incident angles, velocities, and substrate temperatures was investigated, providing precise guidance for experimental GaAs growth.

[0049] Gallium arsenide thin films were deposited and grown under different incident conditions using molecular dynamics simulations. The products were analyzed in depth from the aspects of surface morphology and internal structure to seek the incident parameters under the optimal deposition state, providing theoretical guidance for the fabrication of gallium arsenide thin films.

[0050] A total of 12,000 atoms were deposited, 6,000 Ga atoms and 6,000 As atoms. Because arsenic and gallium atoms have relatively large atomic masses, when multiple atoms are deposited in the system, As atoms tend to agglomerate to form As8 structures, causing system disorder. Therefore, a limit was set that only when the distance to existing atoms... The atom insertion conditions were set, with one atom inserted at a time interval of 1.5 ps. Multiple sets of independent variables, such as different incident angles, incident rates, and substrate temperatures, were set to obtain simulated deposition atom visualizations and log data under various incident conditions.

[0051] In step S5, we also anneal the deposited film. Annealing is a crucial step in crystal growth, transforming a disordered crystal into a single crystal. During annealing, the crystal is heated and melted, causing the atoms to rearrange and converting the disordered state of the deposited atoms into an ordered state. Figure 4 After annealing, the surface roughness of the atoms at different incident angles decreases in an overall translational manner, while the average atomic height decreases at different incident angles and the density increases irregularly overall. The gallium arsenide film also becomes denser and the atomic arrangement becomes more compact due to the increased compactness after annealing. Figure 5 The peak values ​​of the radial distribution curves of the system before and after annealing changed from sharp and slender to short and blunt peaks as the number of steps increased. The orderly arrangement of the atoms gradually disappeared, and it became an amorphous-single crystal mixture with amorphous atoms.

[0052] In S5, the internal structure of the simulation results is visualized and analyzed. The simulation results include the coordinates, energy information, volume, and mechanical information of each atom in the simulation system. Ovito's "identify diamond structure" technique and defect analysis technique are used to analyze the internal structural composition and defects of the deposited thin film. Figure 6 The distribution of crystal structure types at different temperatures shows that as the substrate temperature increases, homogeneous nucleation begins to occur in the thin film. The boundary between crystalline and amorphous materials gradually extends upwards from the substrate, and the nucleation type is heterogeneous directional nucleation. Figure 7 As shown, dislocation lines were found at temperatures of 773 K and above. All dislocations appeared in the deposited layer, and the probability of dislocation formation increased with increasing substrate temperature. At substrate temperatures of 773 K and 973 K, the dislocation types were mainly a-type dislocations (b = 1 / 3 <1–210>) and other dislocations. At substrate temperature of 1173 K, a large number of shockley dislocations (b = 1 / 3 <1–100>) appeared.

[0053] The working principle of the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided by this invention is as follows:

[0054] First, a simulation model of a gallium arsenide deposition substrate with a certain roughness was created. As and Ga atoms were deposited on the substrate surface under different incident angles, incident velocities, and substrate temperatures. Comparison of multiple experimental results led to the conclusion that: a high incident angle has a positive effect on suppressing the formation of As8 clusters; at different incident rates, As8 was deposited on the thin film surface, and the surface roughness increased with the increase of the incident rate; the incident angle and incident rate of the deposited atoms affected the formation time of the As8 structure in the vertical position, resulting in different roughness and density differences; the changes in radial curves before and after annealing confirmed that annealing has a positive effect on the formation of single crystals; the substrate temperature has a positive effect on reducing surface roughness; dislocation lines were found in the thin films deposited at different substrate temperatures, and the probability of occurrence and the length of the dislocation lines increased with the increase of the substrate temperature. Although the increase in substrate temperature increases the possibility of dislocations, the crystallization rate increases at a very considerable rate. This invention reduces the workload of annealing during crystal growth. The invention uses computer simulation to study the growth process of gallium arsenide semiconductor thin films and employs various research methods to analyze and compare the deposited films under different incident conditions. Compared with laboratory growth, this invention saves experimental costs and time. The conclusions can provide effective guidance for laboratory deposition experiments and industrial processing of high-quality semiconductor thin films.

[0055] Compared with related technologies, the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided by this invention has the following advantages:

[0056] Using Material Studio software, Lammps open-source software, VESTA software, Ovito visualization software, and Origin data processing software, the molecular dynamics simulation method overcomes the difficulties of high cost and long time in experiments, and makes up for the lack of observation of the motion trajectory and internal structural changes of individual atoms during the atomic growth process in experiments.

[0057] Second Embodiment

[0058] Please refer to the following: Figure 8 , Figure 9 and Figure 10 Based on the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided in the first embodiment of this application, the second embodiment of this application proposes another simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films. The second embodiment is merely a preferred embodiment of the first embodiment, and the implementation of the second embodiment will not affect the separate implementation of the first embodiment.

[0059] Specifically, the second embodiment of this application provides a simulation method for seeking the optimal parameters for depositing and growing gallium arsenide semiconductor thin films. The difference lies in the fact that, in the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide semiconductor thin films, a display screen 34 is used when using the molecular dynamics simulation software Lammps in step S4. A rotating block 33 is fixedly installed at the bottom of the display screen 34, and a second rotating seat 32 is rotatably connected to the outer side of the rotating block 33. One end of the second rotating seat 32 is slidably connected to the inner side of the fixed frame 1. A toothed plate 36 is fixedly installed on the back of the display screen 34, and a pull block 35 is fixedly installed on the top of the display screen 34.

[0060] The inner side of the fixed frame 1 is provided with sliding grooves 11 on both sides. The inner side of the sliding grooves 11 is slidably connected to limit blocks 31, and the limit blocks 31 are fixedly installed on both sides of the slider 3.

[0061] A rubber pad 12 is fixedly installed at the bottom of the fixed frame 1, and a first rotating seat 2 is fixedly installed at the top of the fixed frame 1. A support plate 21 is rotatably connected inside the first rotating seat 2, and one end of the support plate 21 is engaged with the inner side of the toothed plate 36.

[0062] The working principle of the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided by this invention is as follows:

[0063] When in use, the user operates the molecular dynamics simulation software Lammps through the display screen 34. During use, the user rotates the support plate 21, causing it to engage with the inner surfaces of different toothed plates 36, thereby adjusting the angle of the display screen 34. After using the display screen 34, the user rotates it until it is level with the slider 3. Then, the user pushes the display screen 34, causing it to slide the slider 3 towards the inner surface of the fixed frame 1, thus retracting the display screen 34 into the inner surface of the fixed frame 1.

[0064] Compared with related technologies, the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided by this invention has the following advantages:

[0065] The fixed frame 1, slider 3, limiting block 31, and display screen 34 work together to store the display screen 34 inside the fixed frame 1 after use, thus preventing damage to the display screen 34 from impacts when not in use. Furthermore, the support plate 21 is inserted into different grooves inside the toothed plate 36, allowing the angle of the display screen 34 to be adjusted, increasing its adaptability.

[0066] Third Embodiment

[0067] Please refer to the following: Figure 11 Based on the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided in the first embodiment of this application, the third embodiment of this application proposes another simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films. The third embodiment is merely a preferred embodiment of the first embodiment, and the implementation of the third embodiment will not affect the separate implementation of the first embodiment.

[0068] Specifically, the third embodiment of this application provides a simulation method for seeking the optimal parameters for depositing and growing gallium arsenide semiconductor thin films, which differs in that the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide semiconductor thin films has buffer pads 4 fixedly installed on three sides of the fixed frame 1.

[0069] The working principle of the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided by this invention is as follows:

[0070] When in use, a buffer pad 4 is installed on the outer side of the fixed frame 1. The buffer pad 4 is made of rubber and has a certain elasticity. When the fixed frame 1 is impacted, the buffer pad 4 can protect the fixed frame 1.

[0071] Compared with related technologies, the simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films provided by this invention has the following advantages:

[0072] When in use, the buffer pad 4 can protect the fixed frame 1 and act as a buffer when the fixed frame 1 is impacted, thus preventing damage to the fixed frame 1.

[0073] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A simulation method for seeking the optimal parameters for the deposition and growth of gallium arsenide thin films, characterized in that, Includes the following steps: S1. Use Lammps and Material Studio material simulation software to establish a gallium arsenide substrate simulation model with a certain roughness. The surface roughness simulates gallium arsenide crystals that are difficult to exist in a single crystal state in reality. The surface roughness model is added according to the specific situation. Fixed areas are divided in the model for fixation to achieve the purpose of stabilizing the substrate. S2. Set the ensemble, time step, boundary conditions, and initial temperature environment parameters of the simulation substrate model created in S1 to prepare the environment for subsequent atomic deposition. S3. Based on S2, the simulation system is further optimized by minimizing energy, minimizing temperature, setting relaxation time, and setting potential function. In the selection of potential function, the Tersoff many-body potential function proposed by Albe is used to improve the accuracy of simulation calculation. S4. Using the molecular dynamics simulation software Lammps, the number of deposited atoms and the time interval between the released atoms were set for the established simulation model. Multiple thin films were deposited by changing the deposition rate and the incident angle of the deposited atoms to change the incident conditions. Different substrate temperatures were set to obtain crystalline gallium arsenide thin films with different structures. S5. Multiple analytical methods, including radial distribution function, surface roughness density, crystal structure identification, and dislocation identification, were used to analyze the changes in the surface and internal structure of the deposited thin film. The results were then used to guide the experiments.

2. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 1, characterized in that, The establishment of the gallium arsenide substrate simulation model in S1 includes the following steps: using the "Supercell" function of Material Studio software to expand the gallium arsenide unit cell, resulting in a gallium arsenide cube with dimensions of 10.1 × 10.1 × 6.3 nm. 3 Four atomic layers are fixed at the bottom of the substrate to prevent them from being affected by temperature and stress, thus achieving the effect of fixing the substrate. Spherical protrusions and depressions are created on the surface of the cube using the software Lammps, with the following commands: region 40sphere 15.5477 77.7384 63.6041 7 units box delete_atoms region 40 create_atoms region 40.

3. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 1, characterized in that, The potential function environment parameters for the simulation model of the deposition substrate established in S1 in S2 are set as follows: Write an IN file to set the x-axis and y-axis boundary conditions as periodic boundaries and the z-axis as a non-periodic boundary in the deposition box. The specific setting command is as follows: boundary ppf # p is a periodic boundary; Perform ensemble, time step, and temperature initialization settings for the simulation model. The specific setting commands are as follows: fix 1 all nvt temp 800.0 800.0 100.0 # Ensemble settings run 300000 # Time step velocity other create 298 39849 mom yes rot yes distgaussian # Temperature initialization.

4. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 1, characterized in that, The specific operations for environmental optimization of the simulation model in S3 are as follows: The Tersoff multibody potential function proposed by Albe is used to improve the accuracy of the simulation calculation. The specific setting command is as follows: pair_style tersoff pair_coeff * * GaAs.tersoff Ga As #force field settings; The specific command for minimizing the energy of the system is as follows: min_style cg minimize 1e-8 1e-8 10000 10000.

5. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 1, characterized in that, In S4, the deposition parameters of the deposition simulation model established in S1 are set as follows. The relevant deposition commands are as follows: fix 2 all deposit 6000 1 1500 95485 region sput near 1 vz -50 -50units box fix 3 all deposit 6000 2 1500 95485 region sput near 2 vz -50 -50units box.

6. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 1, characterized in that, In step S5, the obtained thin film surface data are analyzed using radial distribution function, surface roughness calculation, visualization analysis, and microstructure characterization methods. The focus is on calculating the thin film surface roughness, thin film density, and thin film quality parameters. The calculation results can effectively guide experimental analysis.

7. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 1, characterized in that, When using the molecular dynamics simulation software Lammps in S4, a display screen, a fixed frame, and a slider are used. A rotating block is fixedly installed at the bottom of the display screen, and a second rotating seat is rotatably connected to the outer side of the rotating block. One end of the second rotating seat is slidably connected to the inner side of the fixed frame. A toothed plate is fixedly installed on the back of the display screen, and a pull block is fixedly installed on the top of the display screen.

8. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 7, characterized in that, The inner side of the fixed frame is provided with sliding grooves on both sides, and the inner side of the sliding groove is slidably connected to a limit block, which is fixedly installed on both sides of the slider.

9. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 8, characterized in that, A rubber pad is fixedly installed at the bottom of the fixed frame, and a first rotating seat is fixedly installed at the top of the fixed frame. A support plate is rotatably connected inside the first rotating seat, and one end of the support plate is engaged with the inner side of the toothed plate.

10. The simulation method for seeking the optimal parameters for depositing and growing gallium arsenide thin films according to claim 9, characterized in that, The fixed frame is fixedly installed with buffer pads on three sides.

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