Silicon carbide laser processing simulation and morphology evolution prediction method, medium and equipment

Abstract

The invention relates to a silicon carbide femtosecond laser processing process simulation and morphology evolution prediction method, a medium and electronic equipment, and the method specifically comprises the steps: constructing a silicon carbide model, and carrying out discretization processing to obtain a silicon carbide grid model; fluid heat transfer parameters and fluid flow parameters are calculated; constructing a femtosecond laser heat source model; introducing the femtosecond laser heat source model into the double-temperature model and correcting the femtosecond laser heat source model; based on fluid heat transfer parameters and fluid flow parameters, coupling the corrected dual-temperature model with a Navier-Stokes model, and constructing a multi-physical field model; an ablation threshold value is set, and when laser energy reaches or exceeds the ablation threshold value, the grid deforms; calculating the grid deformation speed of the silicon carbide phase explosion; and simulating the removal process of the material according to whether the grid is deformed or not and the deformation speed thereof. According to the method, the multi-physical field model is constructed, so that the process of femtosecond laser processing of silicon carbide can be simulated more accurately, the actual processing condition is reflected, and the prediction accuracy of the processing process is improved.

Description

Technical Field

[0001] The present invention relates to the field of femtosecond laser processing technology, in particular to a method, medium and device for simulating femtosecond laser processing of silicon carbide and predicting the evolution of its morphology. Background Art

[0002] As a third-generation semiconductor material, silicon carbide (SiC) has broad application prospects in the fields of electronic devices, sensors, aerospace, etc. due to its unique physical and chemical properties. Its main characteristics include a high bandgap width (about three times that of traditional silicon materials), high strength, high thermal conductivity, and good chemical inertness. These characteristics make silicon carbide an ideal material for high-power and high-frequency devices, capable of maintaining stable performance in extreme environments.

[0003] However, the high hardness and brittleness of silicon carbide materials pose great challenges to traditional processing methods. In traditional machining, due to the high hardness of silicon carbide, conventional cutting tools are prone to wear during the processing, resulting in a significant reduction in tool life. In addition, the high brittleness of silicon carbide makes the heat-affected zone of the material significantly increase in laser processing or other high-energy density processing methods, and it is easy to generate processing defects, thereby affecting the mechanical properties of the material and the reliability of the device. Therefore, developing an efficient, precise and heat-damage-reducing processing technology is of great significance for the wide application of silicon carbide materials.

[0004] In recent years, the gradual maturity of femtosecond laser processing technology has provided a new direction for solving the above problems. Femtosecond lasers, through their extremely short pulse duration (usually on the order of 10- 15 seconds), can concentrate energy on the material in an extremely short time, thus triggering a non-thermal effect processing mechanism. This mechanism enables the material to undergo instantaneous evaporation or breakdown during processing, thereby avoiding the common heat damage problems in traditional processing methods. Femtosecond laser processing technology has shown significant advantages in the preparation of material substrate wafers, capable of reducing dislocations and improving the processing accuracy and surface quality of the material.

[0005] Although femtosecond laser processing technology has shown great potential in the processing of silicon carbide materials, there are still deficiencies in the current research on the simulation of the femtosecond laser processing process and the prediction of surface morphology. Most of the existing models focus on the combination of optical and thermal models, and less consider fluid flow in the femtosecond laser ablation. Although some studies have attempted to combine fluid flow with thermal and optical physical fields, these studies mainly focus on metal materials, and there are relatively few studies on wide-bandgap materials (such as silicon carbide). Fluid flow plays a crucial role in the femtosecond laser processing process. It not only affects the material removal efficiency but also determines the final formation of the processing morphology. Therefore, developing a simulation method for the femtosecond laser processing process of silicon carbide and a prediction method for the surface morphology evolution that can comprehensively consider the coupling of fluid flow, heat, and light physical fields has important scientific significance and practical value for improving processing accuracy, optimizing processing parameters, and promoting the wide application of silicon carbide materials. Summary of the Invention

[0006] To this end, the technical problem to be solved by the present invention is to overcome the deficiencies in the prior art and provide a method, medium, and device for simulating the laser processing of silicon carbide and predicting the surface morphology evolution. By constructing a multi-physical field model and comprehensively considering the interaction of fluid flow, heat, and light physical fields, the process of femtosecond laser processing of silicon carbide can be more accurately simulated, reflecting the actual processing situation, thereby improving the prediction accuracy of the processing process.

[0007] In a first aspect, to solve the above technical problem, the present invention provides a method for simulating the laser processing of silicon carbide and predicting the surface morphology evolution, including the following steps:

[0008] S1. Construct a silicon carbide model and perform discretization processing on the model to obtain a silicon carbide grid model;

[0009] S2. Based on the silicon carbide grid model, set the silicon carbide material parameters, and calculate the fluid heat transfer parameters and fluid flow parameters according to the silicon carbide material parameters;

[0010] S3. Set the femtosecond laser process parameters and construct a femtosecond laser heat source model according to the femtosecond laser process parameters;

[0011] S4. Introduce the femtosecond laser heat source model into the two-temperature model and correct the two-temperature model to obtain a corrected two-temperature model;

[0012] S5. Based on the fluid heat transfer parameters and fluid flow parameters, couple the corrected two-temperature model with the Navier-Stokes model to construct a multi-physical field model;

[0013] S6. Set the ablation threshold based on the multi-physical field model. When the laser energy reaches or exceeds the ablation threshold, the grid deforms;

[0014] S7. Calculate the grid deformation velocity of the silicon carbide phase explosion;

[0015] S8. Simulate the material removal process based on whether the grid deforms and its deformation velocity.

[0016] In an embodiment of the present invention, in step S1, the discretization process of the silicon carbide model adopts free-form triangular meshes to convert the silicon carbide model into a silicon carbide grid model.

[0017] In an embodiment of the present invention, in step S2, the silicon carbide material parameters include thermophysical parameters and optical parameters. The thermophysical parameters include the latent heat of fusion L m , evaporation temperature T v , solidus temperature T s in the solid-liquid mixed phase, and liquidus temperature T m ;

[0018] The optical parameters include Planck's constant h, impact ionization coefficient β, and Auger recombination coefficient γ;

[0019] The fluid heat transfer parameters include carrier density n e , liquid volume fraction g l , thermal conductivity k of the mixing zone m , density ρ of the mixing zone m , and specific heat capacity C of the mixing zone pm ;

[0020] The fluid flow parameters include Darcy resistance F Darcy , recoil pressure P r , and Marangoni tangential force.

[0021] In an embodiment of the present invention, the carrier density n e is derived and described by the Fokker-Planck equation:

[0022]

[0023] In the formula, h is Planck's constant, w is the photon frequency, β is the impact ionization coefficient; the Auger recombination coefficient γ, α1 is the single-photon absorption coefficient, α2 is the two-photon absorption coefficient, α3 is the three-photon absorption coefficient, α FCA is the carrier absorption coefficient, and I is the laser intensity, representing the light energy per unit area;

[0024] The calculation formula for the liquid volume fraction g l is as follows:

[0025]

[0026] The thermal conductivity k of the mixing zone mThe calculation formula is as follows:

[0027] k m = g l k l +(1 - g l )k s (3)

[0028] The density ρ of the mixing zone m The calculation formula is as follows:

[0029] ρ m = g l ρ l +(1 - g l )ρ s (4)

[0030] The specific heat capacity C of the mixing zone pm , the calculation formula is as follows:

[0031]

[0032] In the formula, T s is the solidus temperature in the solid - liquid mixed phase, T m is the liquidus temperature, k l is the liquid - phase thermal conductivity, ρ l is the liquid - phase density, C pl is the liquid - phase specific heat capacity, k s is the solid - phase thermal conductivity, ρ s is the solid - phase density; C ps is the solid - phase specific heat capacity, L m is the latent heat of fusion, T l is the lattice temperature;

[0033] The Darcy resistance F Darcy The calculation formula is as follows:

[0034]

[0035] In the formula, A and B are constants. A can take a larger value of 10 6 , and can take a smaller value of 10 -3 , and u is the fluid velocity;

[0036] When g l = 1 (liquid phase), the Darcy resistance F Darcy is 0; when 0 < g l < 1, it is the mixing zone. When g l = 0 (solid phase), the Darcy resistance F Darcy is very large, forcing the fluid velocity to be 0;

[0037] The recoil pressure P r The calculation formula is as follows:

[0038]

[0039] Where P sat is the saturation pressure, P atm is the atmospheric pressure, L v is the latent heat of vaporization, T v is the evaporation temperature, T l is the lattice temperature; k B is the Boltzmann constant;

[0040] The calculation formula of the Marangoni tangential force is as follows:

[0041] σ(T) = 1.943 - 3.5×10 -4 (T l - T m ) (8)

[0042]

[0043] Wherein, σ(T) is the temperature-dependent surface tension coefficient, is the normal unit vector, is the tangential gradient, σ is the stress tensor, μ is the dynamic viscosity, P is the total pressure, and I is the unit tensor.

[0044] In an embodiment of the present invention, in step S3, the femtosecond laser heat source model is as follows:

[0045]

[0046] Where I0 is the peak laser intensity at the center of the light spot, α1 is the single-photon absorption coefficient, α2 is the two-photon absorption coefficient, α3 is the three-photon absorption coefficient, α FCA is the carrier absorption coefficient, F is the laser energy density, τ p is the pulse width, r0 is the laser radius, and R is the reflectivity of silicon carbide.

[0047] In an embodiment of the present invention, in step S4, the two-temperature model is corrected by the Fokker - Plank equation and the Drude equation.

[0048] In an embodiment of the present invention, the expression of the Drude equation is as follows:

[0049]

[0050] Where ε sic is the dielectric function of the material in the initial state, ω is the laser frequency, ω p is the plasma frequency, τ D is the free electron relaxation time; i is the imaginary unit, satisfying i 2= -1;

[0051] The refractive index n and extinction coefficient k are obtained as follows:

[0052]

[0053] The reflectivity R of the modified silicon carbide is:

[0054]

[0055] where Re(ε) is the real part of the dielectric constant and Im(ε) is the imaginary part of the dielectric constant.

[0056] In an embodiment of the present invention, the modified two-temperature model is as follows:

[0057]

[0058] where C e is the electronic heat capacity, C pm is the lattice heat capacity of the mixing zone, K e is the electronic thermal conductivity, K m represents the lattice thermal conductivity of the mixing zone, g is the electron-lattice coupling coefficient, Q is the laser heat source and the electron energy loss term, Q loss is the heat loss term, E g is the band gap energy, K B is the Boltzmann constant.

[0059] In an embodiment of the present invention, the expression of the Navier-Stokes model is as follows:

[0060]

[0061] where is the inertial force, is the pressure, is the viscous force, ρ(1-β(T-T l ))g is the gravity and the buoyancy force caused by the temperature gradient, F Darcy is the Darcy resistance, F r is the recoil pressure, ρ is the material density, μ is the dynamic viscosity, and β is the thermal buoyancy coefficient.

[0062] In an embodiment of the present invention, in step S7, the calculation formula for the grid deformation velocity of the silicon carbide phase explosion is as follows:

[0063]

[0064] where h(T l -T ν ) is the heat flux on the silicon carbide surface, h is the heat transfer coefficient, ρ mis the density of the mixing zone, T v is the evaporation temperature, T l is the lattice temperature is the normal unit vector

[0065] In a second aspect, to solve the above technical problems, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed, the simulation method for the femtosecond laser processing process of silicon carbide and the prediction method for the morphology evolution described in the first aspect are realized.

[0066] In a third aspect, to solve the above technical problems, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, the steps of the simulation method for the laser processing of silicon carbide and the prediction method for the morphology evolution described in the first aspect are realized.

[0067] The above technical solutions of the present invention have the following beneficial effects compared with the prior art:

[0068] In the simulation method for the laser processing of silicon carbide and the prediction method for the morphology evolution of the present invention, the fluid flow, heat, and light physical fields are coupled to construct a multi-physical field model that comprehensively considers various physical effects. This coupled model can more comprehensively reflect the physical behavior of the material during the femtosecond laser processing process, can more accurately simulate the process of femtosecond laser processing of silicon carbide, and reflect the actual processing situation, thereby improving the prediction accuracy of the processing process; compared with the traditional photothermal model, the present invention can more accurately describe the material removal mechanism and the evolution of the surface morphology during the processing process. At the same time, the present invention can also simulate the processing process and morphology under different processing parameters, which helps to achieve higher processing efficiency, better surface quality, and lower cost in actual processing. In addition, the method of the present invention can also be extended to the femtosecond laser processing research of other wide-bandgap materials, promoting the scientific research progress and industrial application in related fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to make the content of the present invention easier to be clearly understood, the following further details the present invention according to the specific embodiments of the present invention and in combination with the attached drawings, where

[0070] Figure 1 is the flow chart of the simulation method for the femtosecond laser processing process of silicon carbide and the prediction method for the morphology evolution in the preferred embodiment of the present invention;

[0071] Figure 2 is the flow chart of the simulation steps for the femtosecond laser processing process of silicon carbide and the prediction method for the morphology evolution in the simulation system COMSOL;

[0072] Figure 3 is the schematic diagram of the silicon carbide model size selection and mesh division;

[0073] Figure 4 It is the evolution curve of the carrier density during the femtosecond laser processing of silicon carbide;

[0074] Figure 5 It is the evolution of the reflectivity and dielectric function during the femtosecond laser processing of silicon carbide;

[0075] Figure 6 It is the evolution of the electron and lattice temperatures during the femtosecond laser processing of silicon carbide;

[0076] Figure 7 It is the two-dimensional model diagram of silicon carbide before femtosecond laser processing;

[0077] Figure 8 It is the ablation morphology diagram of the simulation and experiment after the femtosecond laser processing of silicon carbide;

[0078] Figure 9 It is the comparison diagram of the ablation pit data between the simulation and experiment during the femtosecond laser processing of silicon carbide;

[0079] Figure (a) shows the depth and width of the ablation pit;

[0080] Figure (b) shows the height and width of the molten bulge. Specific implementation manner

[0081] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the embodiments cited are not intended to limit the present invention.

[0082] Embodiment 1

[0083] Refer to Figure 1 and 2 As shown, the method for simulating the laser processing of silicon carbide and predicting the morphology evolution of the present invention comprises the following specific steps:

[0084] Step S1: Establish a geometric model and divide the grid; establish a two-dimensional silicon carbide model in COMSOL; when discretizing the model, select a free-form triangular grid for grid division. In order to more accurately capture the changes in physical quantities in the model, an adaptive grid refinement technique is adopted. In addition, for the specific area where the femtosecond laser acts, additional local grid refinement processing is performed. In this embodiment, the size selection and grid division of the two-dimensional silicon carbide model are as Figure 3As shown, by discretizing the silicon carbide model using a free-form triangular mesh, the continuous physical model can be transformed into a discrete mesh model, facilitating efficient numerical simulation on a computer. At the same time, by adopting the adaptive mesh refinement technique for the specific area affected by femtosecond laser, the mesh density can be dynamically adjusted according to the change of physical quantities, thereby providing higher resolution in the key area, improving the accuracy of the simulation, and maintaining a lower mesh density in other areas to save computing resources.

[0085] Step S2: Define the material parameters of silicon carbide, including thermal physical properties and optical parameters. Among them, the thermal physical properties include the latent heat of fusion L m , evaporation temperature T v , solidus temperature T s and liquidus temperature T m in the solid-liquid mixed phase; the optical parameters include Planck's constant h, impact ionization coefficient β, and Auger recombination coefficient γ. Then, according to these material parameters of silicon carbide, calculate the fluid flow parameters and fluid heat transfer parameters.

[0086] The fluid heat transfer parameters include carrier density n e , liquid volume fraction g l , thermal conductivity k m of the mixed zone, density ρ m of the mixed zone, and specific heat capacity C pm of the mixed zone; the fluid flow parameters include Darcy resistance F Darcy , recoil pressure P r and Marangoni tangential force. By calculating the fluid flow parameters and fluid heat transfer parameters, the fluid flow and heat transfer behaviors of silicon carbide under the action of femtosecond laser can be comprehensively described. The accurate calculation of these parameters provides a basis for subsequent multi-physical field coupling simulation, ensuring the reliability and accuracy of the simulation results. The following is the specific calculation process of the fluid flow parameters and fluid heat transfer parameters:

[0087] (1) Carrier density n e

[0088] An improved equation derived from the Fokker - Plank equation can be used to describe the carrier density n e , and the calculation formula is as follows:

[0089]

[0090] where h is Planck's constant, w is the photon frequency, and β is the impact ionization coefficient;

[0091] (2) Thermal physical properties of the material in the solid-liquid mixed zone

[0092] For the thermal physical parameters of the solid-liquid mixing zone materials, the phase field model is used for reference, and the calculation formula is as follows:

[0093]

[0094] k m =g l k l +(1 - g l )k s (3)

[0095] ρ m =g l ρ l +(1 - g l )ρ s (4)

[0096]

[0097] In the formula, g l is the liquid volume fraction, T s is the solidus temperature in the solid-liquid mixed phase, T m is the liquidus temperature, k m is the thermal conductivity of the mixing zone, ρ m is the density of the mixing zone, C pm is the specific heat capacity of the mixing zone, k l is the thermal conductivity of the liquid phase, ρ l is the density of the liquid phase, C pl is the specific heat capacity of the liquid phase, k s is the thermal conductivity of the solid phase, ρ s is the density of the solid phase, is the specific heat capacity of the solid phase, L m is the latent heat of fusion;

[0098] (3) Darcy resistance F Darcy

[0099] The enthalpy-porosity method is used to deal with the movement of the solid-liquid interface during the phase change process, aiming to handle the solid-liquid mixing zone through the porous medium model. During the melting phase change process, the solid phase velocity is zero, the porosity is zero, and the velocity magnitude in the solid phase gradually increases and then transforms into the liquid phase. The momentum loss caused by the phase change is calculated by the Darcy resistance, and its calculation formula is as follows:

[0100]

[0101] In the formula, A and B are constant values. A can take a larger value (10 6 ), and B can take a smaller value (10 -3 ). u is the fluid flow velocity. When g l =1 (liquid phase), the Darcy resistance is 0. When 0 < g l <1, it is the mixing zone. When gl When it is in the solid phase at =0, the Darcy resistance is very large, forcing the fluid velocity to be 0;

[0102] (4) Recoil pressure P r

[0103] Due to the violent phase explosion, a recoil pressure is generated at the material interface, causing the interface to be indented and bent. The recoil pressure P r The calculation formula is as follows:

[0104]

[0105] In the formula, P sat is the saturation pressure, P atm is the atmospheric pressure, L v is the latent heat of vaporization, T v is the evaporation temperature;

[0106] (5) Marangoni tangential force

[0107] There is a surface tension on the surface of the molten liquid, and the change in its temperature gradient brings about the Marangoni tangential force. The calculation formula is as follows:

[0108] σ(T) = 1.943 - 3.5×10 -4 (T l -T m ) (8)

[0109]

[0110] In the formula, σ(T) is the surface tension coefficient related to temperature, is the normal unit vector, is the tangential gradient, σ is the stress tensor, μ is the dynamic viscosity, P is the total pressure, and I is the unit tensor.

[0111] Step S3: According to the actual experimental conditions, define a series of key parameters of the femtosecond laser process. These parameters include the laser energy density F, the laser radius r0, the pulse width τ p as well as the single-photon, two-photon, three-photon, and carrier absorption coefficients α1, α2, α3, α FCA , and then consider the reflectivity R of silicon carbide and the attenuation of the laser power density along the incident direction, and construct a femtosecond laser heat source model with a Gaussian distribution for both time and space shaping. This model takes into account the interaction between the laser and the material, including the reflectivity R of silicon carbide and the attenuation of the laser power density, so as to more accurately describe the distribution and deposition of laser energy in the material, providing key inputs for subsequent thermal effect simulations.

[0112] The femtosecond laser heat source model is shown in Eqs. (10), (11), and (12):

[0113]

[0114] Where \(I_0\) is the peak laser intensity at the center of the light spot, \(\alpha_1\) is the single-photon absorption coefficient, \(\alpha_2\) is the two-photon absorption coefficient, \(\alpha_3\) is the three-photon absorption coefficient, and \(\alpha\) FCA is the carrier absorption coefficient, \(F\) is the laser energy density, and \(\tau\) p is the pulse width, \(r_0\) is the laser radius, and \(R\) is the reflectivity of silicon carbide.

[0115] Since the laser irradiation of the material will change the reflectivity \(R\) of its silicon carbide, the Drude equation is introduced to correct this, which can be expressed as:

[0117] Where \(\varepsilon\) sic is the dielectric function of the material in the initial state, \(\omega\) is the laser frequency, \(\omega\) p is the plasma frequency, and \(\tau\) D is the free electron relaxation time.

[0118] The refractive index \(n\) and extinction coefficient \(k\) are obtained as follows:

[0119]

[0120] Then the reflectivity \(R\) is:

[0121]

[0122] Step S4: In COMSOL, the femtosecond laser heat source model is introduced into the two-temperature model, and the traditional two-temperature model is corrected by the Fokker - Plank equation and the Drude equation to accurately construct a model of the femtosecond laser-induced plasma evolution process.

[0123] Step S5: With the help of the fluid heat transfer module in COMSOL, the corrected two-temperature model is combined with the Navier - Stokes model to construct a multi-physics field model covering optical, thermal, and fluid flow effects. This multi-physics field coupling model can more comprehensively describe the complex physical phenomena in the femtosecond laser processing process and improve the accuracy and reliability of the simulation.

[0124] The corrected two-temperature model is shown in Equations (17), (18), (19), and (20) as follows:

[0125]

[0126] Where \(C\) e and \(C\) pm represent the lattice heat capacities of electrons and the hybrid region, \(K\) e is the electron thermal conductivity, and \(K\) m$\kappa$ is the lattice thermal conductivity of the mixing zone, $g$ is the electron-lattice coupling coefficient, $Q$ is the laser heat source and the electron energy loss term, $Q$ loss is the heat loss term, $E$ g is the bandgap energy, $K$ B is the Boltzmann constant.

[0127] The Navier-Stokes equations used to describe fluid flow are shown in Equation (21):

[0128]

[0129] where is the inertial force, is the pressure, is the viscous force, $\rho(1 - \beta(T - T$ l ))$g$ is the gravity and the buoyancy force caused by the temperature gradient, $F$ Darcy is the Darcy resistance, $F$ r is the recoil pressure. Where $\rho$ is the material density, $\mu$ is the dynamic viscosity, and $\beta$ is the thermal buoyancy coefficient.

[0130] Step S6: Calculate and set the ablation threshold based on the multi-physics model; when the laser energy density exceeds this threshold, the material removal mechanism is triggered, and when the laser energy density is lower than this threshold, the material remains unremoved and the processing continues without triggering material removal;

[0131] When the material temperature rises rapidly above its evaporation temperature, accompanied by extremely high pressure accumulation, a phase explosion phenomenon will occur, which is an extreme material removal mechanism.

[0132] Step S7: In order to accurately reproduce this physical process and its impact on material removal in COMSOL, a phase explosion grid rate $u$ mesh applicable to silicon carbide materials is defined to accurately simulate the surface morphology formed after femtosecond laser ablation of silicon carbide.

[0133] Among them, the phase explosion grid rate $u$ mesh of silicon carbide material is calculated as shown in Equation (22):

[0134]

[0135] where $h(T$ l $- T$ ν ) is the heat flux on the silicon carbide surface, $h$ is the heat transfer coefficient (taking a larger value), and a larger heat flux is obtained when the lattice temperature is greater than the vaporization temperature.

[0136] Step S8: According to the grid deformation and deformation speed, use COMSOL to run the simulation, convert the simulation results into an intuitive ablation morphology, and then realize the simulation of the processing process and the prediction of morphology evolution.

[0137] During the simulation process, domain probes are added to the entire domain of the silicon carbide model, and through these probes, the carrier density, optical parameters, and numerical values of the electron lattice temperature at the center of the material surface are measured respectively during the simulation process. As the simulation time progresses, the change data of these physical quantities over time are recorded, and then the change curves of the carrier density, optical parameters, and electron lattice temperature over time are obtained. By recording the above change curves, the final processing result can be predicted, the femtosecond laser processing process can be understood and controlled more comprehensively, and according to the change curves, the laser processing parameters can be adjusted to optimize the processing process and achieve the required processing effect, which helps to improve the accuracy of femtosecond laser processing prediction. In this embodiment, in order to ensure the accuracy of the results, a fully coupled solver is used and the convergence criteria of the solver are carefully adjusted.

[0138] It should be noted that in order to ensure the stability of the simulation results, multiple independent COMSOL solutions are carried out and the results are compared, and the simulation of the processing process and the prediction of the ablation morphology are realized through the above operations.

[0139] Figure 4 is the evolution curve of the carrier density over time. It can be seen from the figure that under the action of femtoseconds, the carrier density rises rapidly, and with the increase of the laser energy, more electrons are excited, and the carrier density continues to increase. With the end of the pulse, the carrier density gradually decreases through radiative recombination and Auger recombination.

[0140] Figure 5 are the changes in the reflectivity R and dielectric constant of silicon carbide. It can be seen from the figure that the optical properties of silicon carbide change violently under the action of different laser energies. As the laser energy density gradually increases, the carrier density increases rapidly, and the tendency of "metallization" becomes more rapid and obvious. Correspondingly, the real part of the dielectric function decreases gradually to a negative value with the increase of the energy density. When approaching 0, the reflectivity R of silicon carbide gradually shows the "metallization" characteristic, and the imaginary part of the dielectric function is the absorption of photons, and its trend is inversely proportional to the real part.

[0141] Figure 6 is the evolution of the electron and lattice temperature. It can be seen from the figure that under the action of femtosecond laser, the electron temperature rises on the femtosecond time scale, the lattice temperature rises on the picosecond time scale, and the heat transfer in the lattice is on the nanosecond time scale. It can be seen from the figure that under the radiation of the femtosecond laser, the electrons absorb energy in an extremely short time, and the electron temperature rises rapidly to reach the peak within 500 fs. At this time, the lattice temperature just begins to rise, so the electron temperature and the lattice temperature are in a non-equilibrium state at this time. Subsequently, through carrier-phonon scattering, the carriers transfer the energy to the lattice within 4 ps, and the lattice temperature gradually rises, and finally the electron temperature and the lattice temperature reach equilibrium.

[0142] Figure 7 It is a two-dimensional model diagram of silicon carbide before being processed by femtosecond laser; Figure 8 It is the ablation morphology diagram of silicon carbide after being processed by femtosecond laser through simulation and experiment. In this embodiment, the simulation results are compared with the experiment to verify the accuracy of the model. In order to quantitatively compare the errors between the simulation and the experiment, the depth and width of the ablation pit, as well as the height and width of the molten protrusion, are respectively measured. The measurement results of the two are as Figure 9 shown. Figure (a) shows the depth and width of the ablation pit. It can be seen from the figure that as the laser energy increases, both the ablation depth and radius increase, but the removal rate decreases. The ablation depth is well fitted at low laser energy, while there are large errors at higher energies. For the ablation radius, it is well fitted at low and high energy densities, and there are large errors at intermediate energies. The reason is related to the deposition efficiency of laser energy. Figure (b) shows the height and width of the molten protrusion. It can be seen from the figure that the height of the recast layer is well fitted at low energy density, and there will be large fluctuations along the simulated values at high energy density.

[0143] Embodiment 2

[0144] The present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed, it implements the method for simulating the femtosecond laser processing process of silicon carbide and predicting the morphology evolution in Embodiment 1.

[0145] Embodiment 3

[0146] The present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, it implements the steps of the method for simulating the femtosecond laser processing process of silicon carbide and predicting the morphology evolution in Embodiment 1.

[0147] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0148] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0149] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0151] Obviously, the above embodiments are only examples for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or variations can be made based on the above description. It is not necessary and impossible to exhaustively list all implementation manners here. And the obvious changes or variations derived therefrom are still within the protection scope of the present invention.

Claims

1. A method for simulating laser processing of silicon carbide and predicting the evolution of morphology, characterized in that: Including the following steps: S1. Construct a silicon carbide model, and perform discretization processing on the model to obtain a silicon carbide grid model; S2. Based on the silicon carbide grid model, set the silicon carbide material parameters, and calculate the fluid heat transfer parameters and fluid flow parameters according to the silicon carbide material parameters; S3. Set the femtosecond laser process parameters, and construct a femtosecond laser heat source model according to the femtosecond laser process parameters; S4. Introduce the femtosecond laser heat source model into the two-temperature model, and correct the two-temperature model to obtain a corrected two-temperature model; S5. Based on the fluid heat transfer parameters and fluid flow parameters, couple the corrected two-temperature model with the Navier-Stokes model to construct a multi-physics field model; S6. Set the ablation threshold based on the multi-physics field model. When the laser energy reaches or exceeds the ablation threshold, the grid deforms; S7. Calculate the grid deformation velocity of the silicon carbide phase explosion; S8. Simulate the material removal process according to whether the grid deforms and its deformation velocity.

2. The silicon carbide laser processing simulation and morphology evolution prediction method according to claim 1, wherein: In step S1, the discretization processing of the silicon carbide model adopts a free-form triangular grid to convert the silicon carbide model into a silicon carbide grid model.

3. The silicon carbide laser processing simulation and morphology evolution prediction method according to claim 1, characterized in that: In step S2, the silicon carbide material parameters include thermophysical parameters and optical parameters, and the thermophysical parameters include the latent heat of fusion L m , evaporation temperature T v , solidus temperature T s and liquidus temperature T m in the solid-liquid mixed phase; the optical parameters include Planck's constant h, impact ionization coefficient β, and Auger recombination coefficient γ; The fluid heat transfer parameters include the carrier density n e , the liquid phase volume fraction g l , the thermal conductivity k of the mixing zone m , the density ρ of the mixing zone m and the specific heat capacity C of the mixing zone pm ; The fluid flow parameters include the Darcy resistance F Darcy , the backflush pressure P r and the Marangoni tangential force.

4. The method for simulating silicon carbide laser processing and predicting morphology evolution according to claim 3, characterized in that: Carrier density n e , which is derived and described by the Fokker-Planck equation: Where h is Planck's constant, w is the photon frequency, β is the impact ionization coefficient; the Auger recombination coefficient γ, α1 is the single-photon absorption coefficient, α2 is the two-photon absorption coefficient, α3 is the three-photon absorption coefficient, and α FCA is the carrier absorption coefficient, and I is the laser intensity, representing the light energy per unit area; Liquid volume fraction g l The calculation formula is as follows: Thermal conductivity k of the mixing zone m The calculation formula is as follows: k m = g l k l +(1 - g l )k s (3) The density ρ of the mixing zone m is calculated as follows: ρ m = g l ρ l +(1 - g l )ρ s (4) Specific heat capacity C of the mixing zone pm , and the calculation formula is as follows: where, T s is the solidus temperature in the solid-liquid mixed phase, T m is the liquidus temperature, k l is the liquid-phase thermal conductivity, ρ l is the liquid-phase density, C pl is the liquid-phase specific heat capacity, k s is the solid-phase thermal conductivity, ρ s is the solid-phase density; C ps is the solid-phase specific heat capacity, L m is the latent heat of fusion, T l is the lattice temperature; Darcy resistance F Darcy The calculation formula is as follows: where A and B are constant values, A can take a relatively large value of 10 6 , and can take a relatively small value of 10 -3 , and u is the fluid flow velocity; When g l = 1 is the liquid phase, the Darcy resistance F Darcy is 0. When 0 < g l < 1, it is the mixed zone. When g l = 0 is the solid phase, the Darcy resistance F Darcy is very large, forcing the fluid velocity to be 0; Recoil pressure P r The calculation formula is as follows: where P sat is the saturation pressure, P atm is the atmospheric pressure, L v is the latent heat of vaporization, T v is the evaporation temperature, T l is the lattice temperature; k B is the Boltzmann constant; The calculation formula of the Marangoni tangential force is as follows: σ(T) = 1.943 - 3.5×10 -4 (T l -T m ) (8) where, σ(T) is the temperature-dependent surface tension coefficient, is the unit normal vector, is the tangential gradient, σ is the stress tensor, μ is the dynamic viscosity, P is the total pressure, and I is the unit tensor.

5. The method for simulating silicon carbide laser processing and predicting morphology evolution according to claim 1, characterized in that: In step S3, the expression of the femtosecond laser heat source model is as follows: Where \(I_0\) is the peak laser intensity at the center of the light spot, \(\alpha_1\) is the single-photon absorption coefficient, \(\alpha_2\) is the two-photon absorption coefficient, \(\alpha_3\) is the three-photon absorption coefficient, \(\alpha\) FCA is the carrier absorption coefficient, \(F\) is the laser energy density, \(\tau\) p is the pulse width, \(r_0\) is the laser radius, and \(R\) is the reflectivity of silicon carbide.

6. The silicon carbide laser processing simulation and morphology evolution prediction method according to claim 1, characterized in that: In step S4, the two-temperature model is corrected by the Fokker-Plank equation and the Drude equation; The expression of the Drude equation is as follows: where ε sic is the dielectric function of the initial state of the material, ω is the laser frequency, ω p is the plasma frequency, τ D is the free electron relaxation time; i is the imaginary unit, satisfying i 2 = -1; Thus, the refractive index n and extinction coefficient k are obtained as follows: The reflectivity R of the corrected silicon carbide is: In the formula, Re(ε) is the real part of the dielectric constant, and Im(ε) is the imaginary part of the dielectric constant; The expression of the corrected two-temperature model is as follows: where C e is the electronic heat capacity, C pm is the lattice heat capacity of the mixed region, K e is the electronic thermal conductivity, K m represents the lattice thermal conductivity of the mixed region, g is the electron-lattice coupling coefficient, Q is the laser heat source and the electron energy loss term, Q loss is the heat loss term, E g is the bandgap energy, K B is the Boltzmann constant.

7. The method for simulating silicon carbide laser processing and predicting morphology evolution according to claim 1, wherein: The expression of the Navier-Stokes model is as follows: where is the inertial force, is the pressure, is the viscous force, ρ(1-β(T-T l ))g is the gravity and the buoyancy caused by the temperature gradient, F Darcy is the Darcy resistance, F r is the recoil pressure, ρ is the material density, μ is the dynamic viscosity, and β is the thermal buoyancy coefficient.

8. The silicon carbide laser processing simulation and morphology evolution prediction method according to claim 1, wherein: In step S7, the calculation formula for calculating the grid deformation velocity of the silicon carbide phase explosion is as follows: where h(T l - T ν ) is the heat flux on the surface of silicon carbide, h is the heat transfer coefficient, ρ m is the density of the mixing zone, T v is the evaporation temperature, T l is the lattice temperature, is the normal unit vector.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the method for simulating silicon carbide laser processing and predicting morphology evolution according to any one of claims 1 to 8 is realized.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method for simulating silicon carbide laser processing and predicting morphology evolution according to any one of claims 1 to 8 are realized.

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