Design Method for Thermal Insulation Performance of Silicon Carbide Ceramic Gradient TPMS Structure

Abstract

The present invention discloses a design method for the heat insulation performance of a silicon carbide ceramic gradient TPMS structure, including: changing the volume fraction of the surface region of the TPMS structure by adjusting the control parameter t; fitting the relationship between the volume fraction P and the change of the control parameter t; dividing the structure into continuous m layers, each layer i by assigning different parameters t i , realizing the gradient distribution of porosity, calculating the thermal conductivity of the porosity layer from the first layer to the mth layer, and superimposing the total thermal conductivity of all layers on each plane perpendicular to the heat flow direction; changing the volume fraction of any layer or multiple layers simultaneously until the total thermal conductivity meets the requirements. Through the structure correlation coefficient library and the generalized volume fraction model, the rapid parametric design of various TPMS types is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of additive manufacturing and optimization design, and the present invention relates to a method for designing thermal insulation performance of a silicon carbide ceramic gradient TPMS structure. Background Art

[0002] SiC ceramics also have high strength, high hardness, low thermal expansion coefficient, excellent thermal shock resistance, oxidation resistance and corrosion resistance, making them an ideal material for manufacturing high-performance heat exchangers. At present, SiC-based ceramic plates are often used in complex operating environments, and their operating temperatures are usually between 600 and 1300°C. However, the SiC solid structure is heavy and large in volume, which reduces the overall heat dissipation efficiency. The thermal conductivity of SiC ceramics is higher but still does not reach the thermal conductivity of metals. In addition, the agglomeration problem or lattice defects of silicon carbide prevents the composite from achieving the required degree of sealing, resulting in its thermal conductivity far below its respective theoretical value.

[0003] In order to solve the above problems, some lattice structures such as the triply periodic minimum surface (TPMS) have structures with high symmetry and optimal physical properties. The TPMS structure can shorten the melting time of phase change materials, and the system has better heat transfer performance, and is widely used in the forming of ceramics such as silicon carbide. The uniform structure has a good effect on stable and uniform heat sources, but the heat dissipation characteristics are different under different heat source conditions. Hot spot heat dissipation in power integrated circuits has been widely studied for directional heat dissipation of hot spots. Therefore, a non-uniform structure TPMS is required. The heat dissipation design method for different heat source conditions is still unclear. The existing methods currently have problems such as single structure, low efficiency, and limited optimization dimension. Summary of the invention

[0004] The object of the present invention is to provide a method for designing the thermal insulation performance of a silicon carbide ceramic gradient TPMS structure, and to achieve rapid parameterized design of various TPMS types through a structure correlation coefficient library and a universal volume fraction model.

[0005] The technical solution to achieve the purpose of the present invention is:

[0006] A method for designing thermal insulation performance of a silicon carbide ceramic gradient TPMS structure comprises the following steps:

[0007] S01: By adjusting the control parameters Changing the volume fraction of the surface area of the TPMS structure;

[0008] S02: Fitting volume fraction and control parameters the relationship between changes in

[0009] S03: Divide the structure into continuous Layer, each layer By assigning different parameters , a porosity gradient distribution is achieved, and the porosity and thermal conductivity of each layer from the first layer to the th layer are calculated, and the total thermal conductivity of all layers on each plane perpendicular to the heat flow direction is superimposed;

[0010] S04: Change the volume fraction of any layer or multiple layers simultaneously until the total thermal conductivity meets the requirements.

[0011] In the preferred technical solution, step S01 further includes defining an implicit function of any TPMS structure, expressed as:

[0012] ;

[0013] In the formula, , , are three-dimensional coordinates, is a periodic function of a specific TPMS type, is the unit cell size, is the regulation parameter;

[0014] Define the volume fraction as the ratio of the solid region to the total volume of the unit cell:

[0015] ;

[0016] Wherein, is the regulation parameter corresponding solid volume.

[0017] In the preferred technical solution, in step S01, within a specific parameter interval , the volume fraction is expressed as a linear or piecewise linear relationship:

[0018] In the formula, the coefficients and are determined by the TPMS type, and the determination methods of the coefficients and include:

[0019] Select typical parameter values , ;

[0020] Measure the corresponding volume fraction by the finite element method or X-ray tomography , ;

[0021] Fit the linear equation , .

[0022] In the preferred technical solution, in step S03, through the general formula calculate the porosity of each layer, and the equivalent thermal conductivity of each layer is calculated by the following formula:

[0023] ;

[0024] represents the thermal conductivity of silicon carbide;

[0025] The total equivalent thermal conductivity is:

[0026] .

[0027] In the preferred technical solution, step S04 includes calling coefficients , according to the selected TPMS type, the optimization objective is to minimize , maximize the thermal shock resistance, obtain the distribution of the gradient regulation parameter , and output the STL model.

[0028] The present invention also discloses an STL model obtained by using the above-mentioned thermal insulation performance design method for the silicon carbide ceramic gradient TPMS structure, including the following steps:

[0029] (a) Use a 3D printing device to form the silicon carbide ceramic slurry, set the intensity of the emitted ultraviolet light to 20 - 30 mW / cm², the wavelength to 405 nm, and adjust the exposure parameters to a radiation intensity of 72 mW / cm², a slice thickness of 50 μm, and an exposure time of 4 - 6 seconds;

[0030] (b) After printing, immerse the sample in an ultrasonic cleaner containing absolute ethanol for 2 minutes;

[0031] (c) During the sintering process, heat the sample at a rate of 2°C per minute until it reaches 300°C, and hold it at this temperature for 1 hour. Subsequently, further heat it to 800°C at a rate of 5°C per minute and hold it for another 1 hour. Continue heating at a rate of 2°C per minute until it reaches 1700°C, keep the sample for 16 hours, and finally, cool the sample naturally to room temperature.

[0032] Compared with the prior art, the present invention has the following remarkable advantages:

[0033] 1. Generalized volume fraction model: Through the structure - related coefficient library and the linear formula , realizing the rapid parametric design of multiple types of TPMS. Through technology integration and dimension expansion, the present invention solves the core problems of single structure, low efficiency, and limited optimization dimensions in existing methods, and has significant application value in fields such as aerospace high-temperature heat insulation and nuclear reactor shielding structures.

[0034] 2. Normalized parameter mapping: Map the parameters of different TPMS to a unified interval (such as [-1, 1]) to simplify cross-type comparison and optimization.

[0035] 3. Automated design process: Integrate functions of numerical calibration, parameter allocation, and manufacturing constraint verification, and support collaborative optimization of multiple types of TPMS. Description of the Drawings

[0036] Figure 1 is the flowchart of the design method for the heat insulation performance of the silicon carbide ceramic gradient TPMS structure in this embodiment;

[0037] Figure 2 is the schematic diagram of the gradient structure in this embodiment;

[0038] Figure 3 is the heat insulation performance at 800 degrees Celsius in this embodiment. Detailed Embodiment

[0039] The principle of the present invention is: Through the structure correlation coefficient library and the generalized volume fraction model, realize the rapid parametric design of multiple types of TPMS. By precisely regulating the geometric parameters and porosity distribution of the TPMS structure, combined with multi-scale equivalent thermal conductivity calculation and optimization algorithms, achieve directional optimization of heat insulation performance.

[0040] Embodiment 1:

[0041] As Figure 1 shown, a design method for the heat insulation performance of a silicon carbide ceramic gradient TPMS structure includes the following steps:

[0042] S01: Change the volume fraction of the surface area of the TPMS structure by adjusting the control parameters ;

[0043] S02: Fit the relationship between the volume fraction and the change of the control parameters ;

[0044] S03: Divide the structure into continuous layers along the heat transfer direction, and each layer realizes a gradient distribution of porosity by assigning different parameters , and calculate from the first layer to the Porosity of the layer, thermal conductivity of the layer, and the total thermal conductivity of all layers stacked on each plane perpendicular to the heat flow direction;

[0045] S04: Change the volume fraction of any layer or multiple layers simultaneously until the total thermal conductivity meets the requirements.

[0046] The specific description is as follows:

[0047] 1. General formula of TPMS implicit function and definition of volume fraction

[0048] Any TPMS structure can be represented by the following implicit function:

[0049] ;

[0050] In the formula, is a periodic function of a specific TPMS type (such as Gyroid, Diamond, Primitive), is the unit cell size, is the regulation parameter.

[0051] Volume fraction is defined as the ratio of the solid region to the total volume of the unit cell:

[0052] ;

[0053] Among them, is the parameter corresponding solid volume, which needs to be determined by numerical integration or experimental calibration.

[0054] 2. General relationship model between volume fraction and parameter of

[0055] For any TPMS structure, within the specific parameter interval , , is the lower and upper limits of the regulation parameter , the volume fraction can be approximately expressed as a linear or piecewise linear relationship:

[0056] ;

[0057] In the formula, the coefficients and are determined by the TPMS type and are determined through the following steps:

[0058] (1) Numerical calibration:

[0059] Select typical parameter values , (such as );

[0060] Measure the corresponding volume fraction by the finite element method or X-ray tomography , ;

[0061] Fit a linear equation , .

[0062] The structure correlation coefficient library is as shown in Table 1 below:

[0063]

[0064] 3. Gradient Porosity Design and Equivalent Thermal Conductivity Calculation

[0065] (1) Gradient parameter allocation:

[0066] Divide into layers along the heat transfer direction, and allocate parameters to each layer , and calculate the porosity of each layer through the general formula .

[0067] Example (Primitive structure, target gradient porosity 30%→20%):

[0068] Layer 1: t 1 = 0.8 → P 1 = -25×0.8 + 50 = 30%;

[0069] Layer 2: t 2 = 1.0 → P 2 = 25%;

[0070] Layer 3: t 3 = 1.2 → P 3 = 20%.

[0071] (2) Equivalent thermal conductivity calculation:

[0072] The equivalent thermal conductivity of each layer is calculated by the following formula:

[0073] ;

[0074] The total equivalent thermal conductivity is obtained by harmonic mean superposition:

[0075] ;

[0076] 4. Optimization Algorithm and Design Verification

[0077] (1) Multi-objective optimization framework:

[0078] Design variables: number of layers , parameters Distribution, TPMS type selection;

[0079] Constraints: manufacturing process limitations (e.g., minimum wall thickness ≥ 0.3 mm);

[0080] Optimization objective: minimize , and maximize thermal shock resistance.

[0081] The calculation of thermal shock resistance is based on a simplified formula , where is the average porosity, is the thermal conductivity of the silicon carbide matrix. The optimization objective is to minimize and maximize , through the weighted objective function for multi-objective trade-off (default weights , ). The optimization algorithm traverses the parameters of each layer and TPMS type combinations, and outputs the Pareto optimal solution set for the user to select, ensuring the balance between thermal insulation performance and mechanical reliability.

[0082] (2) Automatic parameter calibration:

[0083] Automatic parameter calibration is implemented in the Rhino Grasshopper plugin: after the user selects the TPMS type from the drop-down menu, the plugin automatically calls the coefficients , and parameter intervals stored in the database; input the target porosity gradient (e.g., 30% → 20%), and the system generates the parameters of each layer through reverse calculation and automatically checks whether it exceeds the limit (e.g., Gyroid requires ); if the parameter exceeds the limit, it prompts to adjust the target or switch the TPMS type. Finally, it outputs an STL model that meets the requirements of 3D printing, supports direct import into the printing device, and realizes the integrated process from design to manufacturing.

[0084] In the grasshopper plugin of the general design software rhino, according to the selected TPMS type, it automatically calls the coefficients , , generates the gradient key parameters distribution, and outputs the STL model.

[0085] The TPMS structure-related coefficient library contains three categories of core data:

[0086] 1. TPMS mathematical expression library: stores implicit functions of structures such as Gyroid, Primitive, and Diamond;

[0087] 2. Linear coefficient library: Records the coefficients a and b in the volume fraction formula P = a⋅t + b corresponding to each type, as well as the effective parameter intervals.

[0088] 3. Manufacturing constraint library: Defines process constraint parameters such as the minimum wall thickness and the maximum number of layers.

[0089] After the user selects the TPMS type, the system automatically calls the corresponding data to avoid repeated modeling and calibration.

[0090] Through the structure - related coefficient library and linear formulas , rapid parametric design of multiple TPMS types is achieved. Taking the Gyroid structure as an example, its implicit function is . By finite - element simulation or experimental calibration of the linear relationship between the volume fraction and the regulation parameters (such as ). After the user selects the TPMS type, the system automatically calls the corresponding linear coefficients , , and directly calculates the porosity of each layer through , avoiding the cumbersome process of repeated calibration in traditional methods. This method shortens the parametric design time by more than 80% and is applicable to the rapid switching and iterative optimization of multiple TPMS structures.

[0091] Map the parameters of different TPMS to a unified interval (such as [-1, 1]) to simplify cross - type comparison and optimization. To achieve unified comparison and optimization of parameters of different TPMS types, the present invention proposes a normalized parameter mapping technique. Taking the Primitive structure as an example, its original parameter range is . Through the linear formula , it is mapped to the interval [-1, 1]. After optimization, it is restored to the original parameter range through the inverse operation . Define as the original regulation parameter (i.e., the parameter in the TPMS implicit function), as the normalized parameter (mapped to the interval [-1, 1]). The two are mutually converted through linear transformation to ensure cross - type parameter comparability. This method solves the problem of cross - type parameter scale differences. For example, after normalizing the of the Diamond structure, it can be directly co - optimized with the Gyroid structure parameters.

[0092] Automated design process: Integrates numerical calibration, parameter allocation, and manufacturing constraint verification functions to support collaborative optimization of multiple types of TPMS. The automated design process supports collaborative optimization of multiple types of TPMS by integrating numerical calibration, parameter allocation, and manufacturing constraint verification.

[0093] The specific process of collaborative optimization is as follows: Select the TPMS type independently for each layer divided along the heat transfer direction, and allocate the normalization parameters , is the regulation parameter for mapping the th layer to the unified interval; taking the total equivalent thermal conductivity and thermal shock resistance as the optimization objectives, use the NSGA-II genetic algorithm for multi-objective optimization (NSGA-II (Non-dominated Sorting Genetic Algorithm II) is a multi-objective optimization algorithm that screens the Pareto optimal solution set through non-dominated sorting and crowding degree calculation, and is suitable for solving trade-off problems in complex design spaces.). During the optimization process, the system automatically checks constraints such as the minimum wall thickness (≥0.3 mm) and the porosity change rate between adjacent layers ( ), and adjusts the parameters in real time through voxelization analysis to ensure the manufacturability of the structure. For example, in a five-layer gradient structure, Gyroid and Diamond types are mixed and used. After optimization is reduced to 23.7 W / (m·K).

[0094] The specific implementation process is as follows:

[0095] First, define its geometric shape based on the implicit level set function of the TPMS structure. Taking the Schoen Gyroid type structure as an example, its mathematical expression is:

[0096] ;

[0097] In the formula , , are three-dimensional coordinates, is the unit cell size, is the regulation parameter. By adjusting the parameter , the surface morphology of the TPMS structure can be changed, and then the volume fraction (i.e., relative density) of the solid region can be controlled. The volume fraction is defined as the ratio of the volume of the solid region to the total volume of the unit cell :

[0098] ;

[0099] Experiments show that for the Schoen Gyroid type TPMS structure, when , the volume fraction has a linear relationship with the parameter :

[0100] ;

[0101] For example, when When , it corresponds to a semi-dense structure; when When , a high-porosity skeleton is formed. This linear relationship provides a direct parametric basis for the design of gradient porosity.

[0102] The structure is divided into continuous layers along the heat transfer direction (such as the thickness direction). Different parameters are assigned to each layer to achieve a gradient distribution of porosity. For example, when designing a five-layer gradient structure, the porosity of the middle layer is set to 30% (corresponding to ), and the porosities of adjacent layers are 25% ( ) and 35% (=0.448) in turn, forming a decreasing sequence. The equivalent thermal conductivity of each layer is jointly determined by the porosity and the thermal conductivity of the silicon carbide matrix (taking 120 W / (m·K)). The calculation formula is:

[0103] ;

[0104] For example, when the thermal conductivities of a three-layer structure are 72, 60, and 48 W / (m·K) respectively, the total equivalent thermal conductivity , which is significantly lower than that of the homogeneous structure (60 W / (m·K)).

[0105] To verify the effectiveness of the design, taking the Diamond-type TPMS structure as an example, the target thermal conductivity is set. Through experiments, its volume fraction formula is calibrated as ( ). It is divided into 7 layers along the thickness direction, and the porosity increases from 18% to 66% in a gradient manner. The calculated total equivalent thermal conductivity meets the design requirements. For the homogeneous Diamond structure with the same porosity (18% - 66%), its equivalent thermal conductivity is . The gradient design of the present invention reduces the thermal conductivity by 37.9%, verifying the significant improvement of the gradient distribution on the heat insulation performance.

[0106] Regarding the heat transfer characteristics of the gradient structure, the unit cell size is dynamically adjusted along the temperature change direction (such as the Z-axis). Based on the reference size , the unit cell size of the th layer changes according to , is the reference temperature, is the total temperature difference (the temperature difference from the hot end to the cold end), where is the coefficient of thermal expansion, is the local temperature. To ensure the continuity of the structure, the number of units in adjacent layers It is necessary to meet , ensuring geometric seamless connection when the unit cell size gradually changes from 2 mm to 0.8 mm (compression ratio 60%). For example, in the 800°C heat insulation test, the equivalent thermal conductivity of the five-layer gradient structure is 23.7 W / (m·K), which is 52% lower than that of the homogeneous structure, verifying the effectiveness of the design method.

[0107] In another embodiment, a method for forming a gradient TPMS structure of silicon carbide ceramics includes the following steps:

[0108] (a) Use a 3D printing device (such as ADT-3D-ZP-Printer-Pro-192-50; Shenzhen Qiyu Technology Co., Ltd.) to form the silicon carbide ceramic slurry. The 3D printing parameters are optimized based on the photocuring characteristics of the silicon carbide ceramic slurry: Through orthogonal experiments, it is found that when the ultraviolet light intensity is 20~30 mW / cm² and the exposure time is 4~6 seconds, the curing depth of the slurry and the interlayer bonding strength reach the best balance (interlayer shear strength ≥ 15 MPa), avoiding defects caused by undercuring or overcuring. Preferably, the ultraviolet light intensity emitted by the device is 28 mW / cm² and the wavelength is 405 nm. Adjust the exposure parameters to a radiation intensity of 72 mW / cm², a slice thickness of 50 μm, and an exposure time of 5 seconds.

[0109] (b) After printing, immerse the sample in an ultrasonic cleaner containing absolute ethanol for 2 minutes. The dimensional accuracy of the TPMS sample is 40 mm³.

[0110] (c) During the sintering process, heat the sample at a rate of 2°C per minute until it reaches 300°C and hold it at this temperature for 1 hour. Subsequently, further heat it to 800°C at a rate of 5°C per minute and hold it for another 1 hour. Continue heating at a rate of 2°C per minute until it reaches 1700°C, and keep the sample for 16 hours. Finally, cool the sample naturally to room temperature.

[0111] The forming process of the present invention can be formed by conventional digital light processing, and has excellent high-efficiency heat dissipation after printing and sintering.

[0112] The variable density TPMS structure can improve the overall thermal resistance of the structure and enhance its heat insulation performance without changing the space occupied by the structure. Precise forming and design presentation are achieved under this process.

[0113] Figure 2 , Figure 3 As shown, different heating sizes at the bottom (1.5 cm, 2 cm, 2.5 cm) will also result in different heat dissipation effects. From Figure 3As can be seen from the heating conditions shown in a-c, the larger the hot spot size, the more consistent the heating curves of different structures. This is mainly because larger hot spots are less affected by pores. Regarding the upper surface temperature, when the heating size is 1.5 cm, Schoen gyroid shows the best heat insulation performance, stabilizing at about 250 °C, while the other two structures stabilize at about 290 °C ( Figure 3 d). When the heating size is 2 cm, Schoen gyroid has the worst heat insulation performance, stabilizing at about 350 °C, followed by Neovius surface at 310 °C, and Schwarz diamond at 280 °C ( Figure 3 e). In contrast, at a heating size of 2.5 cm, the heat insulation characteristics of the three structures are comparable, and all structures stabilize at about 335 °C ( Figure 3 f). Among them, Schoenygroid changes most significantly with the hot spot size. Generally speaking, the overall temperature drop of the heat insulation effects of the three structures exceeds 50%.

[0114] The above embodiments are the preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement methods and are all included in the protection scope of the present invention.

Claims

1. A design method for the thermal insulation performance of a silicon carbide ceramic gradient TPMS structure, characterized in that, Including the following steps: S01: By adjusting the control parameters Changing the volume fraction of the surface region of the TPMS structure; S02: Fitted volume fraction and the relationship with the change of regulation parameters; S03: Divide the structure into continuous layers along the heat transfer direction, and for each layer achieve a gradient distribution of porosity by assigning different parameters , calculate the porosity layer thermal conductivity from the first layer to the nth layer, and sum up the total thermal conductivity of all layers on each plane perpendicular to the heat flow direction; calculate the porosity of each layer through the general formula , and the equivalent thermal conductivity of each layer is calculated by the following formula: , represents the thermal conductivity of silicon carbide; The total equivalent thermal conductivity is: ； S04: Change the volume fraction of any layer or multiple layers simultaneously until the total thermal conductivity meets the requirements; Call coefficients according to the selected TPMS type , , with the optimization objective of minimizing , maximizing the thermal shock resistance, obtaining the gradient regulation parameter distribution, and outputting the STL model.

2. The heat insulation performance design method of the silicon carbide ceramic gradient TPMS structure according to claim 1, characterized in that, Step S01 further includes defining an implicit function of any TPMS structure, expressed as: ， In the formula, , , are three-dimensional coordinates, is a periodic function of a specific TPMS type, is the unit cell size, is the regulation parameter; Define volume fraction as the ratio of the solid region to the total volume of the unit cell: ， Among them, is a regulation parameter corresponding to the entity volume.

3. The heat insulation performance design method of the silicon carbide ceramic gradient TPMS structure according to claim 1, characterized in that, In step S01, within a specific parameter range , , being the lower and upper limits of the regulation parameter , the volume fraction is expressed as a linear or piecewise linear relationship: ， In the formula, the coefficients and are determined by the TPMS type. The determination methods of the coefficients and include: Select typical parameter values , ; Measure the corresponding volume fraction by the finite element method or X-ray tomography , ; Fitted linear equation , .

4. The design method for the heat insulation performance of the silicon carbide ceramic gradient TPMS structure according to claim 1, wherein, Calculation formula of thermal shock resistance , where is the average porosity, is the thermal conductivity of the silicon carbide matrix; the optimization goal is to minimize and maximize . Through the weighted objective function for multi-objective trade-off, , are the weights. The optimization algorithm traverses the parameters of each layer and the combination of TPMS types, and outputs the optimal solution set.

5. The design method for the heat insulation performance of the silicon carbide ceramic gradient TPMS structure according to claim 1, characterized in that Step S04 further includes mapping the parameters of different TPMSs to a unified interval, and the calculation of the normalized parameter is as follows: , By inverse operation Restore to the original parameter range; Among them, is the original regulation parameter, is the parameter after normalization.

6. The method for designing the heat insulation performance of the silicon carbide ceramic gradient TPMS structure according to claim 5, characterized in that, Step S04 further includes the collaborative optimization of multiple types of TPMS. The specific methods include: independently selecting the TPMS type for each layer divided along the heat transfer direction and allocating the normalization parameters; using the NSGA-II genetic algorithm for multi-objective optimization with the total equivalent thermal conductivity and thermal shock resistance as the optimization objectives. During the optimization process, the constraints of the minimum wall thickness and the change rate of the porosity of adjacent layers are verified, and the parameters are adjusted in real time through voxelization analysis to ensure the manufacturability of the structure.

7. The design method for the heat insulation performance of the silicon carbide ceramic gradient TPMS structure according to claim 1, wherein, Step S04 further includes dynamically adjusting the unit cell size along the temperature change direction according to the heat transfer characteristics of the gradient structure, with the reference size as the basis, the unit cell size of the th layer changes according to , where is the reference temperature, is the total temperature difference, is the coefficient of thermal expansion, is the local temperature, and the number of adjacent layer units needs to satisfy .

8. A forming method of a silicon carbide ceramic gradient TPMS structure, characterized in that, The STL model obtained by using the thermal insulation performance design method of the silicon carbide ceramic gradient TPMS structure according to any one of claims 1-3 includes the following steps: (a) Use a 3D printing device to form the silicon carbide ceramic slurry, set the emitted ultraviolet light intensity to 20-30 mW / cm², the wavelength to 405 nm, and adjust the exposure parameters to a radiation intensity of 72 mW / cm², a slice thickness of 50 μm, and an exposure time of 4-6 seconds; (b) After printing, immerse the sample in an ultrasonic cleaner containing absolute ethanol for 2 minutes; (c) During the sintering process, heat the sample at a rate of 2°C per minute until it reaches 300°C and hold it at this temperature for 1 hour. Subsequently, further heat it to 800°C at a rate of 5°C per minute and hold it for another 1 hour. Continue heating at a rate of 2°C per minute until it reaches 1700°C, hold the sample for 16 hours, and finally, let the sample cool naturally to room temperature.

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