Design and method of production of an alumina ceramic insulating component for vacuum

Abstract

This invention discloses a design and fabrication method for alumina ceramic insulating components for vacuum applications, belonging to the technical field of ceramic insulating component design and fabrication. The method includes steps such as macroscopic structural optimization to control the surface electric field distribution and microscopic structural optimization to control secondary electron multiplication. This invention integrates the two stages of vacuum surface flashover initiation and development into a unified optimized design and model construction, effectively reducing the generation of initial electrons and suppressing the multiplication of secondary electrons. This not only significantly enhances the dielectric strength of the entire insulation system but also significantly improves the stability of the equipment. Using ceramic 3D printing with photopolymerization layer-by-layer printing, no additional machining or mold manufacturing is required. A 3D printer using ultraviolet light digital forming technology combined with a sintering furnace can directly generate complex and intricately patterned alumina ceramic components from computer graphics data in a unified manner. This greatly shortens the product development cycle, improves production efficiency, and reduces production costs.

Description

Technical Field

[0001] This invention relates to the field of ceramic insulating component design and fabrication technology, specifically to a method for designing and fabricating an alumina ceramic insulating component for vacuum applications. Background Technology

[0002] Ceramic insulating components play multiple roles in vacuum devices / equipment such as electron beam lithography machines, pulsed power equipment, high-energy electron guns, and CT tubes, providing electrical insulation, mechanical support, and pressure isolation, and have become an indispensable core component of these devices. However, in high-vacuum environments, due to the high voltage and strong electric field of the ceramic insulating components, the composite interface formed by the vacuum and solid insulation is prone to surface discharge breakdown, also known as surface flashover. The presence of surface flashover significantly reduces the withstand voltage of the entire insulation system, limiting the improvement of device voltage levels and the urgent need for miniaturization and compactness.

[0003] To improve the surface dielectric strength of ceramic insulation systems for vacuum applications, existing methods can be summarized into three technical approaches. The first approach reduces the initial electrons generated at the cathode triple junction during the initialization stage of surface flashover. The second approach suppresses the secondary electron multiplication process on the ceramic insulation surface during the development stage of flashover. The third approach suppresses surface gas desorption and increases the voltage threshold for penetrating discharge in the desorbed gas layer on the surface during the final discharge stage of flashover. The specific principles of existing technologies in these three stages of flashover will be described in detail below.

[0004] Initial stage: In order to reduce the maximum electric field intensity at the three junctions, the surface electric field distribution is improved by optimizing the geometry of the ceramic insulating component / metal electrode; the surface electric field distribution is improved by designing graded insulation, increasing the relative permittivity or conductivity of the insulating matrix, and constructing a gradient distribution structure.

[0005] Development stages: In order to suppress secondary electron multiplication, the surface secondary electron emission coefficient of ceramic insulation can be reduced by means of surface treatment; the development of electron avalanche can be hindered by forming ordered or disordered microgroove structures on the ceramic surface;

[0006] Breakdown stage: In order to suppress the probability of gas release from the material surface, gas molecules adsorbed on the surface are eliminated or blocked by means of voltage aging or baking.

[0007] Based on the above principles of improving flashover voltage, the specific implementation process for existing vacuum ceramic insulating components typically covers the following two aspects:

[0008] 1) Preparation of ceramic insulating components

[0009] a. Material selection: Vacuum ceramic insulation components typically use high-purity alumina (Al2O3) or silicon nitride (Si3N4) ceramic materials as the base material. These materials have excellent insulation performance, high temperature stability and resistance to chemical corrosion.

[0010] b. Forming Process: Traditional ceramic insulation forming methods involve using molds, cutting, grinding, and other methods to remove excess material from the raw material to obtain the components. Specific forming processes include injection molding, compression molding, and slip casting.

[0011] c. Sintering process: The formed ceramic parts are placed in a high-temperature furnace and heated at a certain temperature to cause the ceramic particles to bond together and form a dense structure.

[0012] 2) Process for improving the surface dielectric strength of ceramic insulating components

[0013] a. Initial stage: Improving the electric field distribution through geometric structure optimization. Usually before the ceramic insulating component is prepared, a better electrode or ceramic insulating component geometric profile is designed through optimization algorithms. After the ceramic insulating component is prepared, shielding electrodes can be set to suppress the electric field intensity at the three-junction point. On the other hand, an ABA-type sandwich structure can also be used to bond and combine ceramic insulating components with different dielectric constants to form a new ceramic insulating component structure, and the electric field intensity at the three-junction point can be suppressed through graded insulation.

[0014] b. Development Stage: After the ceramic insulating components are fabricated, post-processing methods are typically used to suppress secondary electron multiplication. Specific methods include: surface laser grooving, surface coating, surface ion implantation, surface thermal spraying, surface polishing, direct fluorination, and surface plasma treatment, among other material surface treatment methods.

[0015] c. Breakdown stage: After the ceramic insulating component is prepared, the gas molecules adsorbed on the surface are removed or blocked by means of continuous surface voltage aging treatment or heat baking.

[0016] 1) Existing methods for manufacturing ceramic insulating components are based on mold forming processes, which limit the complexity and flexibility of component shapes and may not meet the requirements for components with special shapes. In addition, the material removal process in traditional methods may lead to material waste, and the mold-making process increases manufacturing time and economic costs.

[0017] 2) Current surface treatment methods exhibit a degree of randomness. Factors such as processing technology, processing time, and substrate material type all increase the uncertainty of the resulting surface structure, thereby affecting the repeatability and timeliness of the improved surface dielectric strength. Furthermore, while numerous surface treatment methods exist, those such as laser grooving or mechanical grooving are inefficient, requiring the movement of the workpiece or grooving equipment to create microstructures individually. This can also lead to cracking, affecting the lifespan of ceramic insulating components. Surface coatings are prone to peeling, reducing equipment lifespan and making it difficult to maintain the modification effect long-term.

[0018] 3) Current methods for improving the surface flashover voltage of ceramic insulation only optimize a single stage of flashover, failing to provide sufficient flexibility and reliability to ensure deep suppression of surface flashover. Therefore, it is necessary to comprehensively consider optimization measures for different stages and achieve a systematic integration of flashover suppression methods at each stage. To this end, a design and fabrication method for alumina ceramic insulating components for vacuum applications is proposed. Summary of the Invention

[0019] The technical problem to be solved by this invention is: how to improve the overall surface dielectric strength of ceramic insulating components. It provides a design method for alumina ceramic insulating components for vacuum applications, which simultaneously addresses the two stages of surface flashover initiation and development, and proposes an integrated design method for the macro-micro structure of ceramic insulating components, which can achieve deep suppression of surface flashover.

[0020] The present invention solves the above-mentioned technical problems through the following technical solution, and the present invention includes the following steps:

[0021] S1: Macroscopic structural optimization and regulation of surface electric field distribution

[0022] With the optimization objectives of homogenizing the surface electric field of the ceramic insulating component and reducing the electric field intensity at the cathode triple junction, the ceramic insulating component region is discretized into multiple grids using the finite element method. The dielectric constant of each grid varies within the range of the substrate dielectric constant to the vacuum dielectric constant. By using a variable density topology optimization algorithm, and considering the limitations of mechanical performance requirements and the range of algorithm parameter values, the optimal spatial distribution of the dielectric constant inside the supporting ceramic insulating component is found, thereby obtaining the macroscopic structure.

[0023] S2: Microstructure optimization regulates secondary electron multiplication

[0024] Microstructures of different sizes are randomly generated on the surface of the macrostructure. Then, surface discharge simulation is carried out using particle simulation and Monte Carlo collision method. The particle simulation method is used to track the motion state of the particles, and the Monte Carlo collision method is used to handle the collision process between particles. By reconstructing the secondary electron multiplication process, the surface structure size parameters of the microstructure with low secondary electron yield are obtained, and thus the microstructure is obtained.

[0025] Furthermore, in step S1, the design optimization variable is the relative permittivity within each grid after discretization of the permittivity optimization region Ω1, as shown below:

[0026] ε(r,z),(r,z)∈Ω1

[0027] Where r and z are the abscissa and ordinate in a two-dimensional axisymmetric coordinate system, respectively, and the dielectric constant of each point after discretization is denoted as ε(r,z);

[0028] Once the optimization variables are determined, the mathematical expression for the optimization objective f is:

[0029]

[0030] Where f1 is the electric field optimization term, f2 is the gradient penalty term, the weighting coefficient q is used to control the proportion of the gradient penalty term in the total optimization objective, Ω1 is the dielectric constant optimization region, Ω2 is the surface electric field optimization region, Ω3 is the local electric field optimization region at CTJ, and C ref1 and C ref2 Let A and h be the normalization parameters for the optimized components in the electric field integral term. mesh ρ and ρ represent the area of ​​the dielectric constant optimization region Ω1, the maximum mesh size, and the material density within the mesh, respectively. E is the electric field intensity within the surface electric field optimization region Ω2. mean This represents the average electric field strength along the surface.

[0031] Furthermore, in step S1, the relationship between the material density ρ within the grid and the relative permittivity is as follows:

[0032]

[0033] Where, ε ri ε max and ε min Let be the dielectric constant, the upper limit of the dielectric constant variation, and the lower limit of the dielectric constant within the i-th grid, respectively; m is the shape control coefficient of the density function; and ρ... i Let be the material density within the i-th grid.

[0034] Furthermore, in step S1, when performing finite element analysis using the variable density topology optimization algorithm, the stress distribution of each mesh under a given mechanical load is simultaneously calculated, and the relationship between stress and strain is expressed by Hooke's Law:

[0035] σ=M*ε

[0036] Where σ is stress, M is the elastic modulus of the material, and ε is strain;

[0037] The strain of each mesh was calculated using the finite element method to obtain the maximum stress S of the entire ceramic insulating component. max With the largest deformation D max ;

[0038] The maximum deformation of ceramic insulating components under a given mechanical load shall not exceed the allowable value D. f ,Right now:

[0039] D max ≤D f

[0040] This provides the constraints for the mechanical strength of ceramic insulating components.

[0041] Furthermore, in step S1, when performing finite element analysis using the variable density topology optimization algorithm, the following constraints are also included:

[0042] 1≤m≤10,0<ρ i <1, 0≤q≤10;

[0043] The final optimization problem is:

[0044] Design variables: ε(r,z), (r,z)∈Ω1

[0045] Optimization goal:

[0046] Constraints:

[0047] 0 < m < 10, 0 < ρ i <1, 0≤q≤10

[0048] D max ≤D f

[0049] Through multiphysics finite element simulations of electric and solid mechanical fields, the parameters m, q, and D were adjusted and optimized. max This yields the optimal spatial distribution of the dielectric constant within the supporting ceramic insulating component.

[0050] Furthermore, after determining the optimization objective and constraints, finite element simulation analysis software was used to establish electric and force field simulation models of the ceramic insulating components. The global moving asymptote optimization algorithm was then used to solve the optimization problem, obtain the optimized material density distribution of the ceramic insulating components, and thus obtain the macroscopic structure.

[0051] Furthermore, in step S2, the specific surface discharge simulation process is as follows:

[0052] S21: Set the minimum forming size S for the microstructure. minThe macroscopic structure surface is divided into N grid matrix units, and different types of lattice structures are used to determine the relationship between the minimum lattice structure size parameters.

[0053] S22: The obtained structures of different sizes are simulated using particle simulation and Monte Carlo collision method to simulate the electric field distribution and the trajectory of charged particles during the secondary electron multiplication process, and the optimized lattice structure size parameters are obtained to improve the vacuum surface electrical resistance of the material.

[0054] Furthermore, in step S21, the minimum lattice structure size parameters include: the length l0 and width d0 of the lattice, the height h0 of the lattice, and the diameter z0 of the lattice pillars. The relationship between these size parameters is as follows:

[0055]

[0056] Furthermore, in step S22, the specific process of simulation using particle simulation and Monte Carlo collision method is as follows:

[0057] S221: Particle Data Processing

[0058] Given the incident angle θ and the bombardment energy E i The total secondary electron emission coefficient δ is determined as follows:

[0059]

[0060]

[0061]

[0062] Where, δ max E represents the maximum secondary electron emission coefficient value in the secondary electron emission curve for vertical incidence. max k represents the corresponding incident electron energy. s E is the roughness coefficient. min The minimum electron energy required to trigger a secondary electron emission;

[0063] Based on the above, the emission coefficients of the three types of electrons are obtained. The three types of electrons are: primary electrons that are elastically scattered; primary electrons that are inelastically scattered; and true secondary electrons.

[0064] S222: Electromagnetic Field Data Processing

[0065] In the electrostatic model, the electrostatic potential is obtained by solving the Poisson equation using the explicit FDTD method, and the electrostatic field is obtained by solving the potential gradient equation. In the electromagnetic model, in order to avoid the limitation of the time step by the CFL condition, the Maxwell equations are solved by the implicit FDTD method to obtain the radio frequency electromagnetic field distribution, and the electrostatic field is solved in the same way as in the electrostatic model.

[0066] S223: Particle Data and Mesh Data Interaction

[0067] The interaction between particles and grid data includes two processes: from particle data to grid data and from grid data to particle data. The process from particle data to grid data involves calculating the charge density and current density on the grid based on parameters such as the particle's position and charge. The process from grid data to particle data involves interpolating the electromagnetic field of the grid onto the particles to calculate the force acting on the particles.

[0068] S224: Particle Collision Processing

[0069] The Monte Carlo collision method is used to handle Coulomb collisions between charged particles.

[0070] This invention also provides a method for preparing alumina ceramic insulating components for vacuum applications. Based on the macroscopic and microscopic structures obtained by the above design method, the ceramic insulating components are formed using photopolymerization ceramic 3D printing technology, including the following steps:

[0071] S3: Photopolymer 3D Printing

[0072] Alumina powder (70-85% by mass), photocurable resin (5-14% by mass), acrylate monomer (5-18% by mass), UV photoinitiator (1-5% by mass), and other additives (1-3% by mass) are dispersed and stirred in a vacuum planetary gravity mixer at a constant temperature of 40-50°C for 5-10 minutes at a stirring speed of 1000-2000 rpm to obtain a uniformly dispersed slurry free of air bubbles. The prepared slurry is then placed in the feed tank of a 3D printer and 3D printed using a photocurable 3D printer to obtain an alumina ceramic component preform.

[0073] S4: Ceramic degreasing

[0074] First, the temperature is raised from room temperature to 600℃ in a vacuum environment at a heating rate of 1℃ / min. During this process, the temperature is held at three temperature nodes of 200, 250 and 300℃ for 90 min each, and then held at 600℃ for 150 min. After the temperature drops to room temperature, air is introduced into the tube furnace, and the temperature is raised from room temperature to 600℃ at the same heating rate of 1℃ / min. The temperature is held for 120 min and then cooled with the furnace.

[0075] S5: Ceramic Sintering

[0076] Sintering was completed in a high-temperature box furnace at 1750℃. During sintering, the temperature was first raised to 1400℃ at a rate of 10℃ / min and held for 120 min. Then, the temperature was raised to 1600℃ at a rate of 5℃ / min and held for another 120 min. Finally, the temperature was slowly raised to 1700℃ at a rate of 2℃ / min and held for 60 min to fully densify the ceramic body. Finally, the temperature was allowed to cool naturally to room temperature, and the sintered dense alumina component was removed, which is the alumina ceramic insulating component.

[0077] Compared with existing technologies, this invention has the following advantages: The design and fabrication method for vacuum alumina ceramic insulating components integrates the two stages of vacuum surface flashover initiation and development through unified optimization design and model building. This effectively reduces the generation of initial electrons and suppresses the multiplication of secondary electrons, significantly improving the dielectric strength of the entire insulation system and the stability of the equipment. Using ceramic 3D printing with photopolymerization layer-by-layer printing eliminates the need for machining or mold making. A single 3D printer using UV digital forming technology can directly generate complex and intricately patterned ceramic components from computer graphics data, greatly shortening the product development cycle, improving production efficiency, and reducing production costs. The surface microstructure is formed through printing, avoiding potential cracking problems during post-processing. This significantly increases the service life of the insulating equipment and improves its reliability. Attached Figure Description

[0078] Figure 1 This is a flowchart illustrating the design and fabrication method of alumina ceramic insulating components for vacuum applications in Embodiment 1 of the present invention.

[0079] Figure 2(a) is a schematic diagram of the minimum lattice structure used in the microstructure optimization process in Embodiment 1 of the present invention;

[0080] Figure 2(b) is a schematic diagram of the structure formed by the arrangement and combination of multiple minimum lattice structures in Figure 2(a);

[0081] Figure 3 This is an initial structural schematic diagram of the ceramic insulating component with a strong parallel electric field in Embodiment 2 of the present invention;

[0082] Figure 4 This is a schematic diagram of the optimized structure of the ceramic insulating component with a strong parallel electric field in Embodiment 2 of the present invention;

[0083] Figure 5 This is an initial structural schematic diagram of the ceramic insulating component with a strong vertical electric field in Embodiment 3 of the present invention;

[0084] Figure 6 This is a schematic diagram of the optimized structure of the ceramic insulating component with a strong vertical electric field in Embodiment 3 of the present invention;

[0085] Figure 7 This is an initial structural schematic diagram of the ceramic insulating component with a mixed electric field in Embodiment 4 of the present invention;

[0086] Figure 8 This is a schematic diagram of the optimized structure of the ceramic insulating component with a mixed electric field in Embodiment 4 of the present invention. Detailed Implementation

[0087] The embodiments of the present invention are described in detail below. These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiments.

[0088] Example 1

[0089] This embodiment provides a technical solution: a design method for alumina ceramic insulating components for vacuum applications, mainly including the following key aspects:

[0090] Initial stage: By controlling the macroscopic material density distribution of ceramic insulation, a macroscopic functional gradient structure is formed to actively homogenize the electric field distribution, reduce the field concentration phenomenon at the cathode triple junction (CTJ), and thus improve the flashover voltage.

[0091] Development stage: From the perspective of suppressing secondary electron multiplication, the controllable design of surface secondary electron yield and the manufacturing constraints of complex structures are taken into account. Complex and ordered microstructures, i.e. micro-complex microstructures, are designed on the ceramic surface.

[0092] This embodiment provides a technical solution: a method for preparing an alumina ceramic insulating component for vacuum applications, mainly including the following key aspects:

[0093] In terms of preparation method, the present invention adopts photopolymer ceramic 3D printing technology. By accumulating and forming layer by layer, the macroscopic functional gradient structure and the microscopic complex microstructure designed in advance by the design method of vacuum alumina ceramic insulating parts are directly printed into solid parts. There is no need for a complicated mold preparation process, which improves the complexity and flexibility of the part shape and avoids material waste.

[0094] Specifically, the design and fabrication methods of the aforementioned vacuum alumina ceramic insulating components will be further explained below.

[0095] like Figure 1 As shown in this embodiment, a design method for an alumina ceramic insulating component for vacuum applications includes the following two aspects:

[0096] 1. Macroscopic structural optimization and regulation of surface electric field distribution

[0097] Firstly, to address the issues of abnormally high electric field at CTJ and uneven electric field distribution along the surface, a gradient distribution of the dielectric constant of ceramic insulation is constructed using topology optimization numerical simulation. This constructs dielectric functional gradient insulation, thereby reducing the electric field strength at the cathode triple junction and homogenizing the electric field along the surface, thus improving the flashover voltage.

[0098] Specifically, with the optimization objectives of homogenizing the surface electric field of the ceramic insulating component and reducing the electric field strength at CTJ, the ceramic insulating component is discretized. The dielectric constant of each tiny unit varies within the range of the substrate dielectric constant (here, the dielectric constant of alumina ceramic at power frequency is selected as 11) to the vacuum dielectric constant (taken as 1). The optimal spatial distribution of the dielectric constant (i.e., material density) inside the supporting ceramic insulating component is found through a variable density topology optimization algorithm.

[0099] The design variable is the relative permittivity within each tiny cell of the discretized permittivity optimization region Ω1, which can be specifically expressed as:

[0100] ε(r,z),(r,z)∈Ω1 (1)

[0101] Where r and z are the abscissa and ordinate in a two-dimensional axisymmetric coordinate system, respectively, and the dielectric constant of each point after discretization is denoted as ε(r,z). After the optimization variables are determined, the optimization objective f can be mathematically expressed as:

[0102]

[0103] Where f1 is the electric field optimization term, f2 is the gradient penalty term, the weighting coefficient q is used to control the proportion of the gradient penalty term in the total optimization objective, Ω1 is the dielectric constant optimization region, Ω2 is the surface electric field optimization region, Ω3 is the local electric field optimization region at CTJ, and C ref1 and C ref2 Let A and h be the normalization parameters for the optimized components in the electric field integral term. mesh ρ and ρ represent the area of ​​the dielectric constant optimization region Ω1, the maximum mesh size, and the material density within the mesh, respectively. E is the electric field intensity within the surface electric field optimization region Ω2. mean This represents the average electric field strength along the surface.

[0104] The relationship between the material density ρ within the mesh and the relative permittivity is as follows:

[0105]

[0106] Where, ε ri ε max and ε minLet represent the dielectric constant, the upper limit of dielectric constant variation (dielectric constant of the alumina ceramic matrix, valued at 11), and the lower limit of dielectric constant (vacuum dielectric constant, valued at 1) within the i-th grid, respectively; m is the shape control coefficient of the density function; ρ i Let be the material density within the i-th grid.

[0107] Regarding constraints, while optimizing the electric field distribution by controlling the material distribution, the mechanical support strength of the ceramic insulating components must also be considered to meet the needs of practical engineering applications. When subjected to force, the ceramic insulating components generate internal reaction forces, known as stress. The magnitude and direction of this stress affect their deformation and mechanical properties. When the stress on the ceramic insulating component exceeds its strength limit, it will lead to cracking and failure. In the topology optimization finite element analysis, the ceramic insulating component structure has been discretized into a triangular mesh. Each finite element (mesh) has a set of nodes and material properties. Appropriate boundary conditions and loading conditions are applied to these nodes according to actual working conditions, and the stress distribution of each finite element is calculated. The relationship between stress and strain can be expressed by Hooke's Law:

[0108] σ=M*ε (4)

[0109] Where σ is stress, M is the elastic modulus of the material, and ε is strain.

[0110] By calculating the strain of each grid, the maximum stress S of the entire ceramic insulating component is finally obtained. max With the largest deformation D max Because of S max It exhibits strong mesh dependence, with significant differences in calculation results under different mesh densities. To reflect the constraints on mechanical properties, it is further stipulated that the maximum deformation of the ceramic insulating component under a given mechanical load shall not exceed the allowable value D. f ,Right now:

[0111] D max ≤D f (5)

[0112] In addition to the constraint objective of mechanical strength, other constraints determined during topology optimization based on the finite element method include:

[0113] 1≤m≤10,0<ρ i <1, 0≤q≤10 (6)

[0114] Where m is the shape control coefficient of the density function, which is usually taken as an integer.

[0115] In summary, the final optimization problem can be summarized as follows:

[0116] Design variables: ε(r,z), (r,z)∈Ω1

[0117] Optimization goal:

[0118] Constraints:

[0119] 0 < m < 10, 0 < ρ i <1, 0≤q≤10

[0120] D max ≤D f

[0121] Based on the above equation, the parameters m, q, and D are adjusted and optimized through multiphysics finite element simulation of electric field and solid mechanical field. max The goal is to find a suitable spatial distribution of dielectric constant that yields good manufacturing and optimization results, thus obtaining an optimized spatial distribution of dielectric constant (i.e., material density) inside the supporting ceramic insulating component.

[0122] Specifically, finite element simulation analysis software was used to establish simulation models of the electric and force fields of the ceramic insulating components. A global moving asymptote optimization algorithm was then employed to gradually approach the optimal solution by continuously adjusting the search path and step size. The steps are as follows:

[0123] 1) Dielectric constant initialization: Select material density ρ i An initial solution is obtained, and the search step size and control parameters m, q, and D are set. max The specific value;

[0124] 2) Moving asymptote operation: Based on the current parameter settings, the force and electric field distributions are obtained through finite element calculation, and a moving operation is performed according to the step size and search direction to calculate and generate a new solution;

[0125] 3) Judgment criterion: If the absolute value error between the new solution and the solution obtained in the previous calculation is less than 10... -4 If the maximum number of iterations is reached, return the optimal solution; otherwise, return to step 2) to perform the asymptote movement operation.

[0126] 4) Finally, the optimization problem in equation (7) is solved to obtain the optimized density distribution of ceramic insulating component material, which meets the requirements of electrical and mechanical strength.

[0127] 2. Microstructural optimization to regulate secondary electron multiplication

[0128] After clarifying the optimized macroscopic structure, the secondary electron multiplication process on the insulating surface is considered to regulate the surface structure of the ceramic insulating component at the microscale, thereby significantly improving the surface dielectric strength of the ceramic insulating component.

[0129] Specifically, microstructures of different sizes are first randomly generated on the macroscopic surface. Then, detailed surface discharge simulation studies are conducted using particle simulation and Monte Carlo collision (PIC and MCC) techniques. The PIC method is used to track the motion state of particles, and the MCC method is used to handle the collision process between particles. By reconstructing the secondary electron multiplication process, microstructure surfaces with low secondary electron yield (SEY) are obtained.

[0130] The specific simulation process is as follows:

[0131] To meet the minimum printing feature accuracy requirements of the 3D printing platform, the minimum forming size S of the microstructure is set. min The macroscopic surface is divided into N grid matrix units, using the lattice structure shown in Figure 2(a). The lattice structure in Figure 2(a) is the minimum lattice structure used in the microstructure optimization process, attached to the surface of the ceramic insulating component after macrostructure optimization. The minimum lattice unit size variables include: the length l0 and width d0 of the lattice (determining the planar dimensions of the surface grooves), the height h0 of the lattice (determining the depth of the surface grooves), and the diameter z0 of the lattice pillars. It should be noted that the parameters satisfy the following relationship:

[0132]

[0133] The obtained structures of different sizes were simulated using the PIC and MCC methods. The PIC and MCC calculation process mainly includes the following four parts: particle data processing, electromagnetic field data processing, particle and electromagnetic field data interaction, and particle collision processing, as detailed below:

[0134] Particle data processing: Electrons incident from a material surface are scattered by atoms (and other electrons) within the material. During scattering, the incident electrons undergo a complex physical process, potentially leading to secondary electron emission. Given an incident angle θ and bombardment energy E... i The total secondary electron emission coefficient δ is as follows:

[0135]

[0136] Where, δ max E represents the maximum SEY value (secondary electron emission coefficient) in the secondary electron emission curve for vertical incidence. max k represents the corresponding incident electron energy. s E is the roughness coefficient. minThe minimum electron energy required to trigger secondary electron emission. Current phenomenological models of secondary electrons suggest that the total number of secondary electrons emitted from the material surface mainly consists of three parts: primary electrons that are elastically scattered; primary electrons that are inelastically scattered; and true secondary electrons. The emission coefficients of each of the three types of electrons can be obtained from equation (9).

[0137] Electromagnetic field data processing: In the electrostatic model, the electrostatic potential is obtained by solving the Poisson equation using the explicit FDTD method, and the electrostatic field is obtained by solving the potential gradient equation. In the electromagnetic model, in order to avoid the limitation of the time step by the CFL condition, the Maxwell equations are solved using the implicit FDTD method to obtain the radio frequency electromagnetic field distribution, and the electrostatic field is solved using the same method as the electrostatic model.

[0138] Particle data and mesh data interaction: The interaction between particle and mesh data includes two processes: from particle data to mesh data and from mesh data to particle data. The former mainly involves calculating the charge and current densities on the mesh based on parameters such as particle position and charge. The charge density is calculated using an area-based Zr bilinear interpolation method, while the current density is calculated using a charge conservation distribution scheme based on trajectory decomposition. The process from mesh data to particle data involves interpolating the electromagnetic field of the mesh onto the particles to calculate the forces acting on them.

[0139] Particle Collision Handling: In a vacuum, the effects of Coulomb collisions are significant. To more accurately describe particle collision behavior, the MCC method will be used to handle Coulomb collisions between charged particles. Specifically, the algorithm proposed by Higginson et al. for handling Coulomb collisions between unequal-weighted particles will be adopted.

[0140] After the microstructure is simulated using the PIC / MCC algorithm, the electric field distribution and the trajectory of charged particles during the secondary electron multiplication process can be simulated with high accuracy, resulting in optimized lattice size parameters, which in turn effectively improves the vacuum surface dielectric strength of the material.

[0141] The method for preparing a vacuum alumina ceramic insulating component in this embodiment includes the following two aspects:

[0142] 1) Photopolymer 3D printing

[0143] After the design is completed, complex and intricately designed ceramic components are generated directly from computer graphics data. These components are then formed using ceramic 3D printing technology. The specific steps are as follows:

[0144] a. According to the mass fraction, 70-85% alumina powder, 5-14% UV-curable resin, 5-18% acrylate monomer, 1-5% UV photoinitiator, and 1-3% other additives (including defoamers, UV absorbers, etc.) are dispersed and stirred using a vacuum planetary gravity mixer at a constant temperature of 40-50℃. The stirring speed is 1000-2000 rpm. After stirring for 5-10 minutes, a uniformly dispersed slurry without bubble defects is obtained.

[0145] b. Place the prepared mixed slurry into the 3D printer's feed tank and 3D print it using a photopolymerization 3D printer to obtain an alumina ceramic component preform.

[0146] In photopolymer 3D printing, the equipment irradiates a resin layer of a certain thickness with 405nm ultraviolet light, accumulating layer by layer for 3D printing. When ultraviolet light irradiates the slurry, on the one hand, the photosensitive resin absorbs the ultraviolet light and undergoes a photocuring reaction; on the other hand, the alumina ceramic particles reflect the ultraviolet light, weakening the radiation effect of the light in the slurry, thereby reducing the thickness of the cured layer. According to Beer-Lambert's law, the curing depth of the photosensitive resin satisfies:

[0147] C d =D p ln(E r / E c (10)

[0148] Among them, C d At the exposure energy E r The thickness of the layer that can be formed by photopolymerization, E r For ultraviolet light energy, E c Critical exposure is the energy required for the resin to begin curing; its value depends primarily on the resin formulation, oxygen content, etc. p The photosensitive parameter is a function of the properties of the ceramic particles and the optical properties of the photocurable resin material. It ensures sufficient interlayer bonding during the printing process, allowing for smooth printing and complete green body formation.

[0149] 2) Ceramic degreasing and sintering

[0150] Degreasing is a crucial step in the entire sintering process. Different degreasing techniques significantly affect the thoroughness of degreasing in ceramic bodies. Direct degreasing in air results in a higher pyrolysis rate of organic matter, but the gas cannot escape completely, causing defects such as porosity. Degreasing in a vacuum, on the other hand, results in a slower pyrolysis rate of organic matter, but due to the scarcity of oxygen, the carbon produced by the pyrolysis cannot be removed through the reaction. Therefore, combining the advantages of thorough pyrolysis from air degreasing with the gas-escape-friendly properties of vacuum degreasing helps to completely remove organic matter from the ceramic body and reduce defects such as porosity and cracks. To maximize the removal of impurities other than alumina, a high-temperature sintering furnace is used for degreasing the ceramic body. The specific process is as follows:

[0151] a. First, raise the temperature from room temperature to 600℃ in a vacuum environment at a heating rate of 1℃ / min. During this process, hold the temperature at three temperature nodes of 200, 250 and 300℃ for 90 min each, and hold the temperature at 600℃ for 150 min.

[0152] b. After the temperature drops to room temperature, introduce air into the tube furnace. Continue to raise the temperature from room temperature to 600℃ at a heating rate of 1℃ / min, hold for 120 minutes, and then cool with the furnace.

[0153] c. Sintering after degreasing is completed in a high-temperature box furnace at 1750℃. During sintering, the temperature is first increased to 1400℃ at a rate of 10℃ / min, held for 120min, and then increased to 1600℃ at a rate of 5℃ / min, and held for another 120min.

[0154] d. Finally, slowly raise the temperature to 1700℃ at a rate of 2℃ / min and hold for 60 minutes to fully densify the ceramic body. Finally, allow it to cool naturally to room temperature and remove the sintered, dense alumina component.

[0155] Example 2

[0156] The initial structure of the ceramic insulating component with a strong parallel electric field is as follows: Figure 3 As shown, it is commonly used in high-energy electron guns, electron beam lithography machines, and pulsed power equipment, responsible for introducing a high-voltage source into the vacuum chamber. After optimizing the macroscopic topology and fine-scale lattice structure using the design and fabrication methods described in Example 1, the optimized ceramic insulating component structure is as follows. Figure 4 As shown.

[0157] Example 3

[0158] The initial structure of the ceramic insulating component with a strong vertical electric field is as follows: Figure 5As shown, ceramic insulating components, commonly used in low-light night vision devices and other vacuum electronic devices, serve to withstand high voltage and provide vacuum sealing. After optimizing the macroscopic topology and fine-scale lattice structure using the design and fabrication methods described in Example 1, the optimized ceramic insulating component structure is as follows: Figure 6 As shown.

[0159] Example 4

[0160] The initial structure of the ceramic insulating component with mixed electric field is as follows: Figure 7 As shown, in commonly used pulse power equipment and other large vacuum equipment, it serves to support metal conductors and isolate potentials. After optimizing the macroscopic topology and fine-scale lattice structure using the design and fabrication methods described in Example 1, the optimized ceramic insulating component structure is as follows: Figure 8 As shown.

[0161] In summary, the design and fabrication method of vacuum alumina ceramic insulating components described in the above embodiments integrates the two stages of vacuum surface flashover initiation and development through integrated optimization design and model building. This effectively reduces the generation of initial electrons and suppresses the multiplication of secondary electrons, which not only significantly improves the dielectric strength of the entire insulation system but also significantly enhances the stability of the equipment. The ceramic 3D printing method, using photopolymerization and layer-by-layer printing, eliminates the need for machining or mold making. A single 3D printer with UV digital forming technology can directly generate complex and intricately patterned ceramic components from computer graphics data. This greatly shortens the product development cycle, improves production efficiency, and reduces production costs. The surface microstructure formed through printing avoids potential cracking problems during post-processing. This significantly increases the service life of the insulating equipment and improves its reliability.

[0162] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A design method for an alumina ceramic insulating component for vacuum applications, characterized in that, Includes the following steps: S1: Macroscopic structural optimization and regulation of surface electric field distribution With the optimization objectives of homogenizing the surface electric field of the ceramic insulating component and reducing the electric field intensity at the cathode triple junction, the ceramic insulating component region is discretized into multiple grids using the finite element method. The dielectric constant of each grid varies within the range of the substrate dielectric constant to the vacuum dielectric constant. By using a variable density topology optimization algorithm, and considering the limitations of mechanical performance requirements and the range of algorithm parameter values, the optimal spatial distribution of the dielectric constant inside the supporting ceramic insulating component is found, thereby obtaining the macroscopic structure. In step S1, the design optimization variable is the relative permittivity within each grid after discretization of the permittivity optimization region Ω1, as shown below: ε(r,z),(r,z)∈Ω1 Where r and z are the abscissa and ordinate in a two-dimensional axisymmetric coordinate system, respectively, and the dielectric constant of each point after discretization is denoted as ε(r,z); Once the optimization variables are determined, the mathematical expression for the optimization objective f is: Where f1 is the electric field optimization term, f2 is the gradient penalty term, the weighting coefficient q is used to control the proportion of the gradient penalty term in the total optimization objective, Ω1 is the dielectric constant optimization region, Ω2 is the surface electric field optimization region, Ω3 is the local electric field optimization region at CTJ, and C ref1 and C ref2 Let A and h be the normalization parameters for the optimized components in the electric field integral term. mesh ρ and ρ represent the area of ​​the dielectric constant optimization region Ω1, the maximum mesh size, and the material density within the mesh, respectively. E is the electric field intensity within the surface electric field optimization region Ω2. mean This represents the average electric field strength along the surface. In step S1, the relationship between the material density ρ within the grid and the relative permittivity is as follows: Where, ε ri ε max and ε min Let be the dielectric constant, the upper limit of the dielectric constant variation, and the lower limit of the dielectric constant within the i-th grid, respectively; m is the shape control coefficient of the density function; and ρ... i Let be the material density within the i-th grid. In step S1, when performing finite element analysis using the variable density topology optimization algorithm, the stress distribution of each mesh under a given mechanical load is simultaneously calculated. The relationship between stress and strain is expressed by Hooke's law: σ=M*ε Where σ is stress, M is the elastic modulus of the material, and ε is strain; The strain of each mesh was calculated using the finite element method to obtain the maximum stress S of the entire ceramic insulating component. max With the largest deformation D max ; The maximum deformation of ceramic insulating components under a given mechanical load shall not exceed the allowable value D. f ,Right now: D max ≤D f That is, to obtain the constraint conditions for the mechanical strength of the ceramic insulating component; S2: Microstructure optimization regulates secondary electron multiplication Microstructures of different sizes are randomly generated on the surface of the macrostructure. Then, surface discharge simulation is carried out using particle simulation and Monte Carlo collision method. The particle simulation method is used to track the motion state of the particles, and the Monte Carlo collision method is used to handle the collision process between particles. By reconstructing the secondary electron multiplication process, the surface structure size parameters of the microstructure with low secondary electron yield are obtained, and then the microstructure is obtained. In step S2, the specific surface discharge simulation process is as follows: S21: Set the minimum forming size S for the microstructure. min The macroscopic structure surface is divided into N grid matrix units, and different types of lattice structures are used to determine the relationship between the minimum lattice structure size parameters. S22: The obtained structures of different sizes are simulated by particle simulation and Monte Carlo collision method to simulate the electric field distribution and the trajectory of charged particles during the secondary electron multiplication process, and the optimized lattice structure size parameters are obtained to improve the vacuum surface electrical resistance of the material. In step S21, the minimum lattice structure size parameters include: the length l0 and width d0 of the lattice, the height h0 of the lattice, and the diameter z0 of the lattice pillars. The relationship between these size parameters is as follows: l0>S min ,d0>S min ,h0>S min l0>z0>S min ,d0>z0>S min ,h0>z0>S min ; In step S22, the specific process of simulation using particle simulation and Monte Carlo collision method is as follows: S221: Particle Data Processing Given the incident angle θ and the bombardment energy E i The total secondary electron emission coefficient δ is determined as follows: Where, δ max E represents the maximum secondary electron emission coefficient value in the secondary electron emission curve for vertical incidence. max k represents the corresponding incident electron energy. s E is the roughness coefficient. min The minimum electron energy required to trigger a secondary electron emission; Based on the above, the emission coefficients of the three types of electrons are obtained. The three types of electrons are: primary electrons that are elastically scattered; primary electrons that are inelastically scattered; and true secondary electrons. S222: Electromagnetic Field Data Processing In the electrostatic model, the electrostatic potential is obtained by solving the Poisson equation using the explicit FDTD method, and the electrostatic field is obtained by solving the potential gradient equation. In the electromagnetic model, in order to avoid the limitation of the time step by the CFL condition, the Maxwell equations are solved by the implicit FDTD method to obtain the radio frequency electromagnetic field distribution, and the electrostatic field is solved in the same way as in the electrostatic model. S223: Particle Data and Mesh Data Interaction The interaction between particles and grid data includes two processes: from particle data to grid data and from grid data to particle data. The process from particle data to grid data involves calculating the charge density and current density on the grid based on parameters such as the particle's position and charge. The process from grid data to particle data involves interpolating the electromagnetic field of the grid onto the particles to calculate the force acting on the particles. S224: Particle Collision Processing The Monte Carlo collision method is used to handle Coulomb collisions between charged particles.

2. The design method for a vacuum alumina ceramic insulating component according to claim 1, characterized in that, In step S1, the following constraints are also included when performing finite element analysis using the variable density topology optimization algorithm: 1≤m≤10.0<ρ i <1.0≤q≤10; The final optimization problem is: Design variables: ε(r,z), (r,z)∈Ω1 Optimization goal: Constraints: 0<m<10.0<ρ i <1.0≤q≤10 D max ≤D f Through multiphysics finite element simulations of electric and solid mechanical fields, the parameters m, q, and D were adjusted and optimized. max This yields the optimal spatial distribution of the dielectric constant within the supporting ceramic insulating component.

3. The design method for alumina ceramic insulating components for vacuum applications according to claim 2, characterized in that, After determining the optimization objective and constraints, finite element simulation analysis software was used to establish electric and force field simulation models of the ceramic insulating components. The global moving asymptote optimization algorithm was then used to solve the optimization problem, obtain the optimized material density distribution of the ceramic insulating components, and thus obtain the macroscopic structure.

4. A method for preparing an alumina ceramic insulating component for vacuum applications, characterized in that, Based on the macroscopic and mesoscopic structures obtained by the design method described in any one of claims 1 to 3, ceramic insulating components are formed using photopolymer ceramic 3D printing technology, comprising the following steps: S3: Photopolymer 3D Printing Alumina powder (70-85% by mass), photocurable resin (5-14% by mass), acrylate monomer (5-18% by mass), UV photoinitiator (1-5% by mass), and other additives (1-3% by mass) are dispersed and stirred in a vacuum planetary gravity mixer at a constant temperature of 40-50°C for 5-10 minutes at a stirring speed of 1000-2000 rpm to obtain a uniformly dispersed slurry free of air bubbles. The prepared slurry is then placed in the feed tank of a 3D printer and 3D printed using a photocurable 3D printer to obtain an alumina ceramic component preform. S4: Ceramic degreasing First, the temperature is raised from room temperature to 600℃ in a vacuum environment at a heating rate of 1℃ / min. During this process, the temperature is held at three temperature nodes of 200, 250 and 300℃ for 90 min each, and then held at 600℃ for 150 min. After the temperature drops to room temperature, air is introduced into the tube furnace, and the temperature is raised from room temperature to 600℃ at the same heating rate of 1℃ / min. The temperature is held for 120 min and then cooled with the furnace. S5: Ceramic Sintering Sintering was completed in a high-temperature box furnace at 1750℃. During sintering, the temperature was first raised to 1400℃ at a rate of 10℃ / min and held for 120 min. Then, the temperature was raised to 1600℃ at a rate of 5℃ / min and held for another 120 min. Finally, the temperature was slowly raised to 1700℃ at a rate of 2℃ / min and held for 60 min to fully densify the ceramic body. Finally, the temperature was allowed to cool naturally to room temperature, and the sintered dense alumina component was removed, which is the alumina ceramic insulating component.

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