Method for analyzing 4H-SiC femtosecond laser processing optimal energy interval

Abstract

The application provides a method for analyzing a 4H-SiC femtosecond laser processing optimal energy interval, and belongs to the technical field of engineering optics based on computer data processing. First, the evolution of electron density, lattice temperature and electron temperature under irradiation is simulated by constructing a three-dimensional model and an electron density cumulative rate equation and a double-temperature model, so that the lattice modification threshold and the ablation threshold are determined. Then, a plurality of experimental data points are selected in the interval for single-pulse laser processing, the surface morphology, removal depth and removal radius of each data point are counted by using conventional characterization methods, and the accuracy and non-thermal removal threshold of the model are determined by observing the number of surface spatter particles and the flux calculation of the morphology edge. Further, the optimal structure modification energy interval, cold processing interval and hot ablation processing interval of 4H-SiC are determined. The application uses fewer sample damage test times, improves the sample utilization rate, shortens the research period, and accelerates the flux screening of the optimal laser processing.

Description

Technical Field

[0001] This invention belongs to the field of engineering optics technology based on computer data processing, and particularly relates to a method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing. Background Technology

[0002] Due to its superior physical properties (high breakdown field strength, high thermal conductivity, and high electron mobility), 4H-SiC has become a prominent third-generation semiconductor material, widely used in optoelectronic devices in electric vehicles, aerospace systems, and power conversion. However, due to its extremely high hardness and chemical inertness, 4H-SiC is also a typical difficult-to-machine material. Traditional machining methods are inefficient, result in severe tool wear, and easily introduce microcracks and stacking faults on the material surface and subsurface, seriously affecting device performance and reliability.

[0003] Ultrafast lasers, with their ultrashort pulses and ultra-high peak power, hold immense potential for precision machining and cutting of hard and brittle materials. They offer a promising alternative for high-quality, rapid machining of 4H-SiC, significantly improving surface quality and processing efficiency while broadening the material's application potential. The core advantage of femtosecond lasers lies in their vast "energy control window." By precisely controlling energy density and repetition rate, they can flexibly switch between a high-quality "quasi-cold machining" mode and a high-efficiency material removal mode, enabling them to handle a wide range of applications from extreme precision to general industrial applications. Recent advancements in femtosecond laser-based precision machining technology offer a promising alternative for high-precision, non-destructive machining of 4H-SiC. This technology not only improves surface quality and processing efficiency but also significantly expands the material's application potential.

[0004] Achieving high-efficiency and high-quality femtosecond laser processing hinges on the precise control of laser parameters. However, femtosecond laser energy, scanning speed, and repetition frequency are crucial factors influencing the processed morphology and quality. Among these, energy density control is key to determining whether femtosecond lasers can perform "cold processing" or thermal ablation of silicon carbide crystals. Currently, the selection of pulse energy density primarily employs a trial-and-error method, involving single-pulse energy density damage experiments before actual sample processing. This approach is limited by its blindness, low efficiency, and high cost. Secondly, there is the issue of imprecise thermal effect control. The interaction between femtosecond lasers and matter still involves complex nonlinear effects and ultrafast thermodynamic processes. Inappropriate process parameters can still lead to thermal damage such as phase transitions, recast layers, and microcracks. Therefore, there is an urgent need for a method that can quantitatively predict the thermal field distribution and final morphology of femtosecond laser-processed silicon carbide based on physical mechanisms, enabling precise optimization and active control of processing parameters. Summary of the Invention

[0005] The present invention aims to provide a method for optimizing parameters and predicting processing effects of femtosecond laser processing of silicon carbide based on a dual-temperature coupling model, so as to solve the problems of inaccurate parameter application and poor thermal effect control in the prior art.

[0006] To achieve the above objectives, this invention proposes a method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing, comprising the following steps:

[0007] S1. Establish a three-dimensional geometric model of 4H-SiC and set the vertex position as the femtosecond laser incident point;

[0008] S2. Based on a three-dimensional geometric model, a rate equation for the accumulation of free electrons under femtosecond laser irradiation is constructed, and the evolution of the free electron density of 4H-SiC is obtained by solving the equation.

[0009] S3. Based on the evolution of free electron density obtained in S2, calculate the electro-acoustic coupling factor, band gap change and electron thermal melting of 4H-SiC, and construct a coupling model describing the energy exchange between electrons and lattice in 4H-SiC under femtosecond laser irradiation.

[0010] S4. Based on the coupling model obtained in S3, a suitable laser flux range is selected, and the evolution data of free electron density, electron temperature, and lattice temperature over time are calculated. The data are then visualized and statistically analyzed in the radial and depth directions to obtain the visualization results.

[0011] S5. Based on the visualization results obtained in S4, determine the structural modification threshold and ablation threshold, and determine the number of single-pulse spot experimental groups within this flux range.

[0012] S6. Conduct throughput experiments based on the number of experimental groups, statistically analyze and process the removal radius and removal depth of the selected throughput processing points of 4H-SiC, use thermal ablation morphology throughput as the criterion to correct the accuracy of the model, and select the morphology map with the smoothest processing morphology to calculate the edge throughput and obtain the non-thermal removal threshold; based on the three obtained thresholds, divide into structural modification interval, cold processing interval and ablation processing interval.

[0013] Furthermore, the laser pulse width is on the order of femtoseconds, the laser parameters are defined in the global definition of the COMSOL simulation software, and the model length of the 4H-SiC crystal is on the order of micrometers.

[0014] Furthermore, in S2, the free electron density evolution formula is:

[0015] ;

[0016] Where N is the free electron density, D is the free electron diffusion coefficient, and W Keldysh The photoionization term, W, is based on the Keldysh theory. DrudeIt is the Drude collision ionization term, -γN 3 -aN is the Auger correction term and the linear absorption relaxation time correction term.

[0017] Furthermore, in S3, the electron thermal density is obtained as 3Nk based on the free electron density. B , where k B Let G be the Boltzmann constant, and the coupling factor G be defined as follows: ,in Given the electroacoustic coupling relaxation time, a coupling model is constructed accordingly:

[0018] ;

[0019] in, E g It is a function of the band gap with respect to the lattice temperature. I Where α is the incident laser intensity, α is the linear absorption coefficient, and Q is the laser thermal term. k e , C e and T e These represent the thermal conductivity, electronic heat capacity, and electronic temperature of free electrons, respectively. k l , C l and T l θ represents the thermal conductivity, heat capacity, and temperature of the crystal lattice, respectively; θ represents the free electron absorption coefficient; and n represents the number of photons absorbed by multiphotons. It is the laser photon frequency, T ext It is the vaporization temperature, and h is the convective heat transfer gradient coefficient. It is an external heat source. It is the normal vector of the crystal surface.

[0020] Furthermore, in S4, visualization statistics are performed in the radial and depth directions to obtain visualization results. Specifically, the shape is drawn by rotating a two-dimensional plane into a three-dimensional solid, and one-dimensional statistics are performed in the X / Y / Z directions.

[0021] Furthermore, the determination of the structural modification threshold and ablation threshold in S5 is specifically as follows:

[0022] The lattice temperature curves of each flux calculated by the coupled model are compared with the melting point of 4H-SiC crystal. The calculated fluxes near the melting point line are the ablation thresholds of 4H-SiC crystal. The free electron density evolution curves of each flux calculated by the coupled model are compared with the critical electron density value (N). cr Compare, closer to N crThe calculated flux is the structural modification threshold of 4H-SiC; the critical electron density N cr It can be represented as:

[0023] ;

[0024] Where c represents the speed of light, m e λ is the electron mass, ε0 is the vacuum permittivity, λ is the laser wavelength, and e is the charge number.

[0025] Furthermore, in step S6, the edge flux is calculated by selecting the morphology image with the smoothest processing topography, using the following formula:

[0026] ;

[0027] Where r is the radius of the circular pit at the processing point, and w0 is the radius of the laser spot; in the laser processing experiment, a circular pit without spatter particles and with a processing radius smaller than the spot radius is selected as the standard. The laser flux obtained by this formula is the non-thermal removal threshold for femtosecond laser processing of 4H-SiC.

[0028] Furthermore, in S6, by obtaining three thresholds, the laser flux is divided into three intervals: when it is higher than the structural modification threshold but lower than the non-thermal removal threshold, it is the modification processing interval; when it is higher than the non-thermal removal threshold but lower than the thermal ablation threshold, it is the cold processing interval; and when it is higher than the thermal ablation threshold, it is the hot processing interval.

[0029] Furthermore, the method of using the morphological flux at the exact start of ablation spatter as a criterion to correct the model's accuracy specifically involves:

[0030] The laser flux at which particle spatter occurred, obtained from the experiment, was compared with the calculated thermal ablation threshold flux. The electroacoustic coupling relaxation time was fine-tuned within the range of 300fs-500fs to reduce the error between the model calculation and the experimental values. The non-thermal removal threshold obtained from the experiment was substituted into the model to calculate the electron temperature and lattice temperature. These values ​​were used as a scale line to mark the removal depth and removal radius obtained from the calculation model, thus obtaining the total removal depth and removal radius calculated by the coupled model.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. This approach elevates femtosecond laser processing of silicon carbide from an experience-based trial-and-error method to a scientifically designed approach based on physical models. This reduces the number of trial-and-error attempts and sample waste in the initial stages of silicon carbide laser processing, saving R&D costs. Coupled analysis methods can directly determine the optimal energy density range for processing materials in different application scenarios, shortening the initial trial-and-error cycle.

[0033] 2. For the first time, Keldysh theory and Drude theory were combined to describe the physical process in the laser processing of silicon carbide. By coupling a dual-temperature model with the phase transition mechanism, and after experimental verification and correction, the temperature and morphology of the processing area can be predicted with high accuracy, so that femtosecond laser cold processing can effectively avoid thermal damage.

[0034] 3. This method is not only applicable to silicon carbide crystals, but its basic principle can also be applied to the femtosecond laser processing of other wide bandgap semiconductors (such as GaN and diamond) after appropriate modifications. Attached Figure Description

[0035] Figure 1 This is a flowchart of the method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing according to the present invention.

[0036] Figure 2 This is a schematic diagram of the geometric model of the coupled model; where (a) is a two-dimensional cross-sectional geometric model and (b) is a three-dimensional geometric model.

[0037] Figure 3 This is a schematic diagram of a processing stage model for femtosecond laser processing of silicon carbide.

[0038] Figure 4 The images show the calculated morphology of the lattice temperature and free electron density distribution of 4H-SiC at 0.7 μJ energy; where (a) is the lattice temperature morphology distribution and (b) is the electron density morphology distribution.

[0039] Figure 5 These are the morphology images observed by AFM when the material is smoothly processed and when thermal ablation has just occurred; where (a) is the morphology image without thermal removal and (b) is the morphology image where thermal removal begins.

[0040] Figure 6 These are comparison charts of the calculated and simulated values ​​of the laser-processed surface radius and depth; where (a) is a comparison chart of the calculated and experimental values ​​of the laser-processed depth of silicon carbide, and (b) is a comparison chart of the calculated and experimental values ​​of the laser-processed radius of silicon carbide.

[0041] Figure 7 This is a graph showing the proportion of removal factors in the laser processing surface radius and processing depth; where (a) is the proportion of non-thermal removal and thermal removal in processing depth, and (b) is the proportion of non-thermal removal and thermal removal in processing radius. Detailed Implementation

[0042] The invention will be further described below with reference to specific embodiments.

[0043] This embodiment takes the fabrication of micro-pits on the surface of a 4H-SiC crystal as an example to further illustrate the specific implementation of the present invention. The overall process is as follows: Figure 1 As shown.

[0044] In step 1, a three-dimensional model of 4H-SiC is established, such as... Figure 2 As shown; a model of the processing stage for femtosecond laser processing of silicon carbide, as follows. Figure 3 As shown, the model is obtained by rotating a two-dimensional rectangle around the Y-axis. The rectangle represents the cross-section of the 4H-SiC crystal, and the upper left vertex of the rectangle is the zero point of the coordinate axis, which is also the incident point of the femtosecond laser. Furthermore, the laser pulse width is on the order of femtoseconds. Laser parameters are defined in the global definition of the COMSOL simulation software, and the model length of the 4H-SiC crystal is on the order of micrometers. The geometric dimensions, boundary conditions (such as adiabatic boundaries), and initial conditions of the simulation region are set. Considering the rotational symmetry of the Gaussian beam, a three-dimensional axisymmetric finite element model is established in this embodiment. The center of the Gaussian beam coincides with the axis of symmetry. In the finite element simulation, a 3×6 μm two-dimensional geometric structure is used, and a three-dimensional structure is generated by rotating this rectangular geometry. The minimum mesh size is set to 0.01 μm, and the time step is 30 femtoseconds. The simulation ends after a relaxation time of 6000 femtoseconds. The initial temperature of both the lattice and the electrons is set to 300K.

[0045] Input femtosecond laser parameters, including but not limited to: laser wavelength, pulse width, single-pulse energy / power density, spot radius, pulse repetition frequency, and scanning speed. The expression for an infrared femtosecond laser is shown below:

[0046] ;

[0047] Where I(r,z,t) is the laser illumination intensity at radius r, depth z, and time t, R is the reflectivity of 4H-SiC, and t p Let E be the laser pulse width, E be the laser single pulse energy, w0 be the spot radius, and t be the laser pulse width. c α represents the laser peak time position, α is the 4H-SiC absorption coefficient, θ is the free electron absorption coefficient, and N is the free electron density.

[0048] In step 2, femtosecond laser cold processing achieves high-precision material modification through a mechanism primarily based on non-thermal effects. Under infrared laser irradiation, the outermost electrons of silicon and carbon atoms are excited through multiphoton absorption and tunneling processes, forming an initial seed electron density. These seed electrons subsequently induce collisional ionization, initiating an avalanche ionization process accompanied by electron-hole pair diffusion. The resulting high-frequency plasma formation ultimately alters the crystal structure properties of 4H-SiC. In this embodiment, femtosecond laser processing of 4H-SiC is divided into three different thresholds, which are structural modification thresholds, their values ​​determined by the critical free electron density N. crCalculations show that the electronic structure of the material will change significantly when this threshold is exceeded. The non-thermal removal threshold is determined jointly by experimental data and the calculation program. It is determined experimentally by simply judging the laser flux at which non-thermal removal occurs, and then substituting this into the program to calculate lattice temperature, electron temperature, and other data. When a specific electron temperature is reached, non-thermal removal begins, thus determining most of the physical quantities calculated subsequently by the program. The thermal ablation threshold is the critical point at which the material reaches its melting point and undergoes ablation morphology, directly obtained by the calculation program. Furthermore, this embodiment uses Keldysh photoionization theory to model the multiphoton ionization and tunneling ionization mechanisms. The Keldysh photoionization theory formula is:

[0049] ;

[0050] Where w is the photoionization rate, ω is the laser angular frequency, and γ is the Keldysh parameter. To reduce Planck's constant, For the effective ionization potential energy, both the K-function and the E-function represent elliptic integrals, and Q is the Q-function. The process of multiphoton ionization induced by femtosecond lasers is described as follows:

[0051] ;

[0052] Where w is the photoionization rate and ω is the laser angular frequency. To reduce Planck's constant, E g Let be the bandgap, m be the effective electron mass, e be the elementary charge number, and F be the laser electric field intensity. The tunneling ionization process induced by ultra-high power density laser is as follows:

[0053] ;

[0054] Where w is the photoionization rate, ω is the laser angular frequency, and γ is the Keldysh parameter. To reduce Planck's constant, For effective ionization potential energy, E g Φ is the bandgap width, and Φ is the Dawson integral.

[0055] The avalanche ionization process is handled by Drude's collisional ionization theory. The principle is that when the seed electron density generated by photoionization reaches a certain level, the resulting high electron density triggers cascade avalanche ionization. The Drude model is particularly suitable for wide-bandgap semiconductors and low-dielectric-constant silicon carbide materials. The formula is:

[0056] ;

[0057] ;

[0058] Among them, W DrudeLet E be the impact ionization rate, I be the laser illumination intensity, and E be the laser beam intensity. g Where is the bandgap width, N is the free electron density, e is the elementary charge number, and ω is the laser angular frequency. Let c be the collision relaxation time, and c be the speed of light. Where n is the vacuum dielectric constant and n is the refractive index of 4H-SiC. For effective electronic quality.

[0059] The interaction between the femtosecond laser beam and 4H-SiC induces the generation of free electrons through the ionization of the substrate material. The density evolution of these free electrons is described by the Fock-Planck equation, which is as follows:

[0060] ;

[0061] and This effectively captures the critical plasma electron density threshold at which non-thermal damage begins to occur. Where N is the free electron density, t is time, ▽ is the Hamiltonian operator, D is the free electron diffusion coefficient, and W... Keldysh For photoionization rate, W Drude denoted as the collisional ionization rate, γ as the Auger coupling coefficient, and a as the linear absorption relaxation time.

[0062] Step 3 describes the ultrafast process by which laser energy, after being absorbed by the electronic subsystem, is transferred to the lattice subsystem via electron-phonon coupling. To simulate the fundamental physical processes, this embodiment employs different partial differential equations (PDEs). Simultaneously, an improved two-temperature model is used to characterize the behavior near the damage threshold caused by thermal effects under femtosecond laser irradiation. The coupling time evolution equations between electron and lattice energy provide a complete framework for understanding the energy transfer dynamics between electrons and the lattice. This scheme modifies the classical two-temperature equations into a semiconductor-type coupled two-temperature equation form as follows:

[0063] ;

[0064] ;

[0065] ;

[0066] ;

[0067] ;

[0068] Here, The value of W represents the electron heat capacity, which is determined by the free electron density N. N is the free electron density, t is time, ∠ is the Hamiltonian operator, D is the free electron diffusion coefficient, and W... Keldysh For photoionization rate, W Drudeγ is the collisional ionization rate, α is the Auger coupling coefficient, a is the linear absorption relaxation time, Q is the heat source, α is the absorption coefficient, θ is the free electron absorption coefficient, I is the laser illumination intensity, and k is the free electron absorption coefficient. B Boltzmann's constant, T is the reduced Planck constant. e and T l K represents the electron temperature and the lattice temperature, respectively. e and k l Representing electronic heat capacity and lattice heat capacity respectively, where n is the multiphoton order of absorption, and T ext It is the vaporization temperature, and h is the convective heat transfer gradient coefficient. It is an external heat source. It is the normal vector of the crystal surface. The electron-phonon coupling factor G is defined as... ,in This represents the electron-phonon relaxation time of solid-state 4H-SiC under a specific state. The parameters of the above formula are shown in Table 1.

[0069] Table 1 Simulation calculation of 4H-SiC parameters

[0070]

[0071] In step 4, the coupled equations established in step 3 are parametrically scanned with respect to laser flux using the finite element method and the finite difference method, and numerically solved to obtain four-dimensional statistical data on the X / Y / Z axes and time t. This step is performed using COMSOL software. Matrix analysis and plotting of the XYZ data for each calculation time step yields three-dimensional graphical representations of the evolution of lattice temperature, electron temperature, and free electron density over time. If the laser flux is used as a one-dimensional image coordinate axis, and the statistical data on the X / Y / Z axes at the final relaxation time is used as the Y-axis, a one-dimensional function graph of lattice temperature, electron temperature, and free electron density with respect to laser flux can be obtained. The radius and depth distributions can be determined from this one-dimensional graph. This step is implemented using MATLAB.

[0072] In step 5, based on the statistical analysis of the simulation data from step 4, taking a single pulse energy of 0.7 μJ as an example, the following results are obtained: Figure 4 The spatiotemporal distribution of electrons and lattice temperature within a set of silicon carbide samples is shown, and the relationship between free electron density N and time, depth, and radius is obtained. By observing the one-dimensional evolution of lattice temperature and free electron density with respect to time, when the lattice temperature exceeds the melting point, the laser flux can be determined as the thermal ablation threshold of 4H-SiC. When the peak position of the free electron density evolution exceeds N... cr When the laser flux is at that time, the corresponding laser flux is the structural modification threshold of 4H-SiC.

[0073] In step 6, using the structural modification threshold and thermal ablation threshold obtained in step 5, laser processing point-mapping experiments are designed around these ranges. Taking six data points as an example, six sets of laser single-pulse energies were designed: 0.1 μJ, 0.15 μJ, 0.2 μJ, 0.3 μJ, 0.5 μJ, and 0.7 μJ, corresponding to laser fluxes of 3.07 J / cm². 2 4.61 J / cm 2 6.14 J / cm 2 9.21 J / cm 2 15.35 J / cm 2 21.49 J / cm 2 Actual femtosecond laser 1-on-1 processing experiments were conducted under the stated laser parameters, and these fluxes were used for synchronous calculations within the coupled model. The depth and radius of the processed morphology were measured using an atomic force microscope or scanning electron microscope, and the processed morphology was photographed. The experimentally measured morphology data was compared with the simulation prediction results from step 4. The flux corresponding to the morphology where an explosion spatter occurred was selected, such as... Figure 5 As shown on the right, compare the results with the calculation results to see if the melting point has been reached. If there are some differences, the error can be eliminated by recalculating the electroacoustic relaxation time in the coupling model. The adjustment range is 300fs-500fs.

[0074] A processing point with an aperture smaller than the laser spot diameter and a smooth surface is selected, and its flux is fitted using the following formula:

[0075] ;

[0076] Where I is the laser illumination intensity, I0 is the initial laser illumination intensity, r is the radius, and w0 is the laser spot radius. The edge laser flux at this processing point can be obtained through fitting. Taking 0.1 μJ as an example... Figure 5 As shown on the left, the radius of the processing point in the experiment is smaller than the radius of the laser spot. Through fitting, it can be determined that its edge flux is 2.653 J / cm. 2 This flux represents the non-thermal removal threshold of 4H-SiC under this laser. Substituting this flux into the model for calculations yields the corresponding electron temperature, lattice temperature, and free electron density. Using these three values ​​as indicators of non-thermal removal, the calculated depth and radius distribution are further analyzed, such as... Figure 6 As shown, the total machining depth and machining radius calculated by the coupled model can be obtained, and as... Figure 7As shown, experimental comparisons and thermal composition analysis can be performed to obtain three flux ranges for laser processing. The range between the structural modification threshold and the non-thermal removal threshold is the structural modification range; the range between the non-thermal removal threshold and the thermal ablation threshold is the cold processing range; and the range where the laser flux is greater than that in the thermal ablation range is the hot processing range.

[0077] Based on the comparison of calculated and experimental curves, key parameters in the model (such as the electron-phonon coupling coefficient G and absorption rate) were fine-tuned to ensure a high degree of agreement between the simulation results and experimental data, thus obtaining a high-precision prediction model that has been experimentally verified. This coupling model can predict the processing morphology and evolution of 4H-SiC processed by infrared femtosecond laser with the same pulse width and wavelength.

[0078] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0079] While the specific embodiments of the present invention have been described above, they are not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing, characterized in that, Includes the following processes: S1. Establish a three-dimensional geometric model of 4H-SiC and set the vertex position as the femtosecond laser incident point; S2. Based on a three-dimensional geometric model, a rate equation for the accumulation of free electrons under femtosecond laser irradiation is constructed. Solving the equation yields the evolution of the free electron density in 4H-SiC. The free electron density evolution formula is: ； Where N is the free electron density, D is the free electron diffusion coefficient, and W Keldysh The photoionization term, W, is based on the Keldysh theory. Drude It is the Drude collision ionization term, -γN 3 -aN is the Auger correction term and the linear absorption relaxation time correction term; S3. Based on the free electron density evolution obtained in S2, the electro-acoustic coupling factor, band gap change, and electron thermal melting of 4H-SiC are calculated to construct a coupling model describing the electron and lattice energy exchange of 4H-SiC under femtosecond laser irradiation; the specific process is as follows: Based on the free electron density, the electron thermal fusion is obtained as 3 Nk. B , where k B Let G be the Boltzmann constant, and the coupling factor G be defined as follows: ,in Given the electroacoustic coupling relaxation time, a coupling model is constructed accordingly: ； in, E g It is a function of the band gap with respect to the lattice temperature. I Where α is the incident laser intensity, α is the linear absorption coefficient, and Q is the laser thermal term. k e , C e and T e These represent the thermal conductivity, electronic heat capacity, and electronic temperature of free electrons, respectively. k l , C l and T l θ represents the thermal conductivity, heat capacity, and temperature of the crystal lattice, respectively; θ represents the free electron absorption coefficient; and n represents the number of photons absorbed by multiphotons. It is the laser photon frequency, T ext It is the vaporization temperature, and h is the convective heat transfer gradient coefficient. It is an external heat source. It is the normal vector of the crystal surface; S4. Based on the coupling model obtained in S3, a suitable laser flux range is selected, and the evolution data of free electron density, electron temperature, and lattice temperature over time are calculated. The data are then visualized and statistically analyzed in the radial and depth directions to obtain the visualization results. S5. Based on the visualization results obtained in S4, determine the structural modification threshold and ablation threshold, and determine the number of single-pulse spot experimental groups within this flux range. S6. Conduct throughput experiments based on the number of experimental groups, statistically analyze and process the removal radius and removal depth of the selected throughput processing points of 4H-SiC, use thermal ablation morphology throughput as the criterion to correct the accuracy of the model, and select the morphology map with the smoothest processing morphology to calculate the edge throughput and obtain the non-thermal removal threshold; based on the three obtained thresholds, divide into structural modification interval, cold processing interval and ablation processing interval.

2. The method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing as described in claim 1, characterized in that: The laser pulse width is on the order of femtoseconds. The laser parameters are defined in the global definition of the COMSOL simulation software. The model length of the 4H-SiC crystal is on the order of micrometers.

3. The method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing as described in claim 1, characterized in that: In step S4, visualization statistics are performed in the radial and depth directions to obtain visualization results. Specifically, the shape is drawn by rotating a two-dimensional plane into a three-dimensional solid, and one-dimensional statistics are performed in the X / Y / Z directions.

4. The method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing as described in claim 3, characterized in that: The process for determining the structural modification threshold and ablation threshold in S5 is as follows: The lattice temperature curves of each flux calculated by the coupled model are compared with the melting point of 4H-SiC crystal. The calculated fluxes near the melting point are the ablation thresholds of 4H-SiC crystal. The free electron density evolution curves of each flux calculated by the coupled model are compared with the critical electron density value Ncr. The calculated fluxes close to Ncr are the structural modification thresholds of 4H-SiC. The critical electron density Ncr can be expressed as: ； Where c represents the speed of light, m e λ is the electron mass, ε0 is the vacuum permittivity, λ is the laser wavelength, and e is the charge number.

5. The method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing as described in claim 4, characterized in that: In step S6, the edge flux is calculated by selecting the morphology map with the smoothest processing morphology, using the following formula: ； Where r is the radius of the circular pit at the processing point, and w0 is the radius of the laser spot; in the laser processing experiment, a circular pit without spatter particles and with a processing radius smaller than the spot radius is selected as the standard. The laser flux obtained by this formula is the non-thermal removal threshold for femtosecond laser processing of 4H-SiC.

6. The method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing as described in claim 4, characterized in that: In step S6, three thresholds are obtained, and the laser flux is divided into three intervals according to the form of laser flux. When the flux is higher than the structural modification threshold and lower than the non-thermal removal threshold, it is the modification processing interval; when the flux is higher than the non-thermal removal threshold and lower than the thermal ablation threshold, it is the cold processing interval. When the temperature exceeds the thermal ablation threshold, it falls within the thermal processing range.

7. The method for analyzing the optimal energy range of 4H-SiC femtosecond laser processing as described in claim 4, characterized in that: The accuracy of the model is calibrated based on the flux at which ablation spatter just begins, specifically: The laser flux at which particle spatter occurred, obtained from the experiment, was compared with the calculated thermal ablation threshold flux. The electroacoustic coupling relaxation time was fine-tuned within the range of 300fs-500fs to reduce the error between the model calculation and the experimental values. The non-thermal removal threshold obtained from the experiment was substituted into the model to calculate the electron temperature and lattice temperature. These values ​​were used as a scale line to mark the removal depth and removal radius obtained from the calculation model, thus obtaining the total removal depth and removal radius calculated by the coupled model.

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