Structural circuit overall performance prediction method based on multi-scale simulation
By combining multi-scale simulation methods with molecular dynamics and macroscopic multiphysics models, the micro-macro-functional scale coupling of structural circuits is analyzed, and a full-chain correlation model is established. This solves the problem that traditional technologies cannot predict the performance of structural circuits in a coordinated manner, and achieves accurate overall performance prediction and optimized design, thereby extending the service life of structural circuits.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-30
- Publication Date
- 2026-04-10
AI Technical Summary
Existing technologies cannot effectively predict the overall performance of structural circuits, especially the impact of damage to the conductive paths of the circuit under mechanical loads, which can lead to signal transmission attenuation or breakage, and cannot meet the design optimization and failure prevention requirements of integrated structural circuit components.
By employing a multi-scale simulation method, combined with molecular dynamics and macroscopic multiphysics models, the micro-macro-functional scale coupling of structural circuits is analyzed. Through multi-scale simulation coupling, the co-evolution law of structural mechanical damage and circuit performance is analyzed, and a full-chain correlation model is established to predict the overall performance of structural circuits.
It enables accurate prediction of the overall performance of the structural circuit, provides comprehensive performance data, avoids overall functional failure caused by single performance optimization, extends service life, reduces failure risk, and is applicable to integrated systems of various structural circuits.
Smart Images
Figure CN121835542A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of structural circuit performance evaluation technology, and more specifically, to a method for predicting the overall performance of structural circuits based on multi-scale simulation. Background Technology
[0002] PEEK-Ag composite structural components, with their integrated structural and circuit manufacturing and embedded conductive paths, combine structural load-bearing functions with circuit signal transmission capabilities, and are widely used in aerospace, intelligent equipment, and flexible electronics. During service, these components must simultaneously withstand mechanical loads such as impact, vibration, and tension, as well as circuit operating stresses. Structural damage caused by these mechanical loads, such as matrix cracks, interface peeling, and conductive phase fracture, not only affects the structural mechanical reliability but also disrupts the circuit's conductive path, leading to signal transmission attenuation, short circuits, or open circuits, severely impacting the overall function of the structural circuit.
[0003] Traditional techniques for predicting the overall performance of structural circuits have significant limitations: single structural mechanics simulations, such as ABAQUS, only focus on macroscopic mechanical indicators such as strength, stiffness, and damage evolution, without considering the influence of the microscopic properties of the conductive Ag particles on the overall mechanical-conductive coupling performance; single circuit simulations ignore the dynamic effects of structural mechanical damage, making it impossible to achieve coordinated prediction of mechanical and circuit performance; existing multi-scale methods mostly focus on single mechanical or conductive properties, failing to establish a full-chain correlation model of "microscopic material properties - macroscopic structural mechanical damage - circuit performance degradation," resulting in insufficient accuracy in overall performance prediction and failing to provide comprehensive support for the design optimization and failure prevention of integrated structural circuit components. Summary of the Invention
[0004] To address the problems existing in the prior art, this invention provides a method for predicting the overall performance of structural circuits based on multi-scale simulation. This method breaks down the barriers between micro-, macro-, and functional scales, and achieves accurate prediction of the overall performance of structural circuits by coupling and analyzing the co-evolution law of structural mechanical damage and circuit performance through multi-scale simulation.
[0005] To achieve the above technical objectives, the present invention adopts the following technical solution: A method for predicting the overall performance of a structured circuit based on multi-scale simulation includes the following steps: Step S1: Analyze the material composition of the structural circuit and construct a composite dynamic model of the structural circuit; Step S2: The constructed composite dynamic model is used to conduct simulation analysis on the impact, shear and temperature coupling conditions in the mechanical load to determine the micro-mechanical-conductive coupling parameters of the structural circuit. Step S3: Construct a macroscopic multiphysics model of the structural circuit, import the micromechanical-conductivity coupling parameters into the macroscopic multiphysics model, and set the structural mechanical boundary conditions, circuit operating parameters and coupling damage criteria in the macroscopic multiphysics model to obtain the simulation model of the structural circuit. Step S4: Set multi-condition simulation parameters, and use the multi-condition simulation parameters to perform multi-scale coupled simulation on the simulation model of the structural circuit to obtain the stress distribution, strain field and damage evolution process of the structural circuit, and predict the overall performance of the structural circuit.
[0006] Further, step S1 includes the following sub-steps: Step S1.1: Analyze the material composition of the structural circuit, including: the structural matrix and the conductive functional phase; Step S1.2: Construct the molecular chains of the structural matrix using the COMPASS force field and periodic boundary conditions, replicate and relax them into an amorphous matrix model, and construct a vacuum layer interface model between structural matrices by stacking them. Step S1.3: Establish a model of the conductive functional phase, and combine it with the amorphous matrix model to construct a sandwich interface model of the structural matrix-conductive functional phase; Step S1.4: Perform NVT and NPT relaxation optimization on the vacuum layer interface model and the sandwich interface model to obtain the composite dynamic model of the structural circuit.
[0007] Furthermore, the micromechanical-conductive coupling parameters of the structure circuit include: the elastic modulus, fracture strength, and damage threshold of the structural matrix in the structure circuit; the lattice distortion rate, atomic diffusion coefficient, and conductivity-stress response function of the conductive functional phase in the structure circuit; and the interfacial binding energy, shear strength, and damage evolution law in the structure circuit.
[0008] Furthermore, the process of constructing the macroscopic multiphysics model of the structural circuit in step S3 is as follows: based on the actual geometric dimensions, structural topology, and circuit wiring layout of the structural circuit, a macroscopic multiphysics model of the structural circuit is constructed using multiphysics simulation software; the multiphysics simulation software is a combination of ABAQUS and circuit simulation modules.
[0009] Furthermore, the structural mechanical boundary conditions include: load type and constraint form; the circuit operating parameters include: input voltage and signal frequency.
[0010] Furthermore, the coupling damage criterion includes: an energy-based structural mechanical damage criterion and a circuit conductivity damage criterion based on the effective cross-sectional area of the conductive path. The structural mechanical damage criterion and the circuit conductivity damage criterion are used to jointly determine whether the structural circuit is conductive and whether it has failed.
[0011] Furthermore, the multi-condition simulation parameters include: mechanical load level, loading rate, ambient temperature, and circuit operating mode; the overall performance of the structural circuit includes: structural mechanical performance and circuit performance, wherein the structural mechanical performance includes ultimate bearing capacity, stiffness retention rate, and fatigue life, and the circuit performance includes conductivity attenuation, signal transmission delay, and crosstalk voltage.
[0012] Furthermore, the simulation model of the aforementioned circuit structure needs to be optimized for simulation accuracy before it is put into use: i: Calculate the error between the overall performance of the structural circuit predicted by the simulation model and the overall performance of the structural circuit verified by experiments under the same working conditions; ii: If the error exceeds the set threshold, dynamically adjust the micromechanical-conductive coupling parameters of the structural circuit and re-predict the overall performance of the structural circuit; iii: Repeat steps i-ii until the error is less than the set threshold, thus completing the accuracy optimization of the simulation model.
[0013] Furthermore, it also includes: based on the predicted overall performance of the structural circuit, identifying the weak points of the structural circuit, and performing optimization at the material, structural, and circuit levels; Among them, material-level optimization includes optimizing the particle size and content of conductive functional phases in the structural circuit and interface modification of the sandwich interface model of matrix-conductive functional phase. Structural optimization includes optimizing the topology design of the circuit structure and increasing the thickness of the protective layer for conductive paths. Circuit-level optimization includes optimizing the wiring of the structural circuit and setting up redundant conductive paths.
[0014] Compared with existing technologies, this invention has the following advantages: The multi-scale simulation-based method for predicting the overall performance of structural circuits establishes a complete chain correlation model of "microscopic material properties - macroscopic mechanical damage - circuit performance degradation" for the first time through multi-scale coupling of molecular dynamics, macroscopic structure, and circuit performance. This solves the problem that traditional technologies cannot achieve coordinated prediction of the overall performance of the structure and circuit. By predicting the overall performance of the structural circuit, including predicting the mechanical reliability of the structure and the functional stability of the circuit, it provides a comprehensive performance basis for the design of structural circuits, avoiding overall functional failure caused by single performance optimization. Furthermore, based on the predicted overall performance of the structural circuit, this invention optimizes the weak parts of the structural circuit, which can specifically improve the mechanical-conductive coupling performance of the structural circuit, extend its service life, and reduce the risk of failure. This invention is applicable to various integrated structural circuit systems, such as metal-polymer, ceramic-conductive phase composite structures, and complex operating conditions, and has the characteristics of wide applicability and strong practicality. Attached Figure Description
[0015] Figure 1 This is a flowchart of the overall performance prediction method for structural circuits based on multi-scale simulation according to the present invention; Figure 2 This is a schematic diagram of the composite dynamics model of the structural circuit; Figure 3 A simulation model for the structural circuit; Figure 4 This is a schematic diagram illustrating multi-scale coupled simulation of a structural circuit simulation model using multi-condition simulation parameters. Figure 5 This is a schematic diagram of the mechanical properties of the structural circuit predicted by the present invention. Detailed Implementation
[0016] The technical solution of the present invention will be further explained and described below with reference to the accompanying drawings.
[0017] like Figure 1 This is a flowchart of the overall performance prediction method for structural circuits based on multi-scale simulation according to the present invention. The overall performance prediction method for structural circuits includes the following steps: Step S1: Analyze the material composition of the structural circuit and construct a composite dynamic model of the structural circuit; including the following sub-steps: Step S1.1: Analyze the material composition of the structural circuit, including: structural matrix and conductive functional phase. For the PEEK-Ag composite structural circuit, the structural matrix is polyetheretherketone, and the conductive functional phase is silver particles. Step S1.2: Construct the molecular chains of the structural matrix using the COMPASS force field and periodic boundary conditions, replicate and relax them into an amorphous matrix model, and construct the vacuum layer interface model of the structural matrix-structural matrix through stacking, i.e., the PEEK-PEEK vacuum layer interface model. Step S1.3: Establish a model of the conductive functional phase, and combine it with the amorphous matrix model to build a sandwich interface model of the structural matrix-conductive functional phase, namely the sandwich interface model of PEEK-Ag. Step S1.4: Perform NVT and NPT relaxation optimization on the vacuum layer interface model and the sandwich interface model to obtain the composite dynamic model of the structural circuit, such as... Figure 2 As shown.
[0018] Step S2: The constructed composite dynamic model is used to conduct simulation analysis on impact, shear, and temperature coupled conditions under mechanical loads. This determines the micromechanical-conductive coupling parameters of the structural circuit, establishes a quantitative mapping model between microscopic parameters and load magnitude and loading rate in macroscopic conditions, and forms a basic parameter database for multi-scale simulation. This solves the problem of accurately obtaining microscopic characteristics while ensuring the adaptability of the micromechanical-conductive coupling parameters to actual service conditions. The micromechanical-conductive coupling parameters include: the elastic modulus, fracture strength, and damage threshold of the structural matrix in the structural circuit; the lattice distortion rate, atomic diffusion coefficient, and conductivity-stress response function of the conductive functional phase in the structural circuit; and the interfacial binding energy, shear strength, and damage evolution law in the structural circuit.
[0019] Step S3: Construct a macroscopic multiphysics model of the structural circuit. Import the micromechanical-conductive coupling parameters into the macroscopic multiphysics model, accurately define the material properties of the structural matrix, conductive functional phase, and interface regions, and set the structural mechanical boundary conditions, circuit operating parameters, and coupling damage criteria in the macroscopic multiphysics model to obtain the simulation model of the structural circuit, such as... Figure 3 As shown, this invention, based on the actual dimensions of the structural circuit, utilizes ABAQUS and a circuit simulation module to construct a macroscopic multiphysics model, maps microscopic parameters, and embeds coupling damage criteria, thus solving the challenge of macroscopic multiphysics modeling. The structural mechanical boundary conditions include load type and constraint form; the circuit operating parameters include input voltage and signal frequency; and the coupling damage criteria include an energy-based structural mechanical damage criterion and a circuit conductivity damage criterion based on the effective cross-sectional area of the conductive path. These two criteria are used to jointly determine whether the structural circuit is conductive and whether it has failed, achieving a synergistic correlation between structural damage and circuit failure.
[0020] The process of constructing the macroscopic multiphysics model of the structural circuit in this invention is as follows: based on the actual geometric dimensions, structural topology and circuit wiring layout of the structural circuit, wherein the circuit wiring layout can refer to the distribution of silver conductive paths, the macroscopic multiphysics model of the structural circuit is constructed using multiphysics simulation software; the multiphysics simulation software is a combination of ABAQUS and circuit simulation modules.
[0021] Step S4: Set multi-condition simulation parameters, including: mechanical load level, loading rate, ambient temperature, and circuit operating mode. Use these parameters to perform multi-scale coupled simulation on the structural circuit model to obtain the stress distribution, strain field, and damage evolution history of the structural circuit. The damage evolution history includes crack length, interface peeling area, and conductive phase fracture rate, such as... Figure 4The simulation model of the structural circuit displays the overall Mises equivalent stress. The stress zone at the top contact area is reddish-yellow, indicating stress concentration, while the bottom is mostly blue, indicating low stress. The stress distribution, strain field, and damage evolution history of the structural circuit are converted into an elastic matrix and damage threshold recognizable by ABAQUS using Cauchy-Born, thereby predicting the overall performance of the structural circuit, including structural mechanical performance and circuit performance. Structural mechanical performance includes ultimate bearing capacity, stiffness retention rate, and fatigue life, while circuit performance includes conductivity attenuation, signal transmission delay, and crosstalk voltage. By predicting the structural mechanical reliability and circuit functional stability, a comprehensive performance basis is provided for the design of the structural circuit, avoiding overall functional failure caused by single performance optimization.
[0022] In one technical solution of the present invention, the simulation model of the structural circuit needs to be optimized for simulation accuracy before it is put into use, so as to ensure the consistency and accuracy of multi-scale simulation: i: Calculate the error between the overall performance of the structural circuit predicted by the simulation model and the overall performance of the structural circuit verified by experiments under the same working conditions; ii: If the error exceeds the set threshold, dynamically adjust the micromechanical-conductive coupling parameters of the structural circuit and re-predict the overall performance of the structural circuit; iii: Repeat steps i-ii until the error is less than the set threshold, thus completing the accuracy optimization of the simulation model.
[0023] In one technical solution of the present invention, the method further includes: based on the predicted overall performance of the structural circuit, identifying the weak parts of the structural circuit, including conductive path areas with high stress concentration, weak interface bonding parts, etc., and performing optimization at the material level, structural level and circuit level, which can specifically improve the mechanical-conductive coupling performance of the structural circuit, ensure that the structural load-bearing capacity and circuit transmission performance meet the design requirements, extend service life and reduce the risk of failure.
[0024] Among them, material-level optimization includes optimizing the particle size and content of conductive functional phases in the structural circuit and interface modification of the sandwich interface model of matrix-conductive functional phase. Structural optimization includes optimizing the topology design of the circuit structure to distribute stress and increasing the thickness of the protective layer for conductive paths. Circuit-level optimization includes optimizing the wiring of the structural circuit to avoid high-stress areas, reducing the impact of line distribution on conductivity, and setting up redundant conductive paths.
[0025] This invention presents a multi-scale simulation-based method for predicting the overall performance of structural circuits. Through multi-scale coupling of molecular dynamics, macroscopic structure, and circuit performance, it establishes for the first time a full-chain correlation model of "microscopic material properties, macroscopic mechanical damage, and circuit performance degradation." This solves the problem that traditional techniques cannot achieve coordinated prediction of the overall performance of structure and circuit. It is applicable to various integrated structural circuit systems, such as metal-polymer, ceramic-conductive phase composite structures, and complex operating conditions. It has the characteristics of wide applicability and strong practicality.
[0026] Example By constructing a composite dynamic model of the PEEK-Ag structure circuit, the impact load conditions of 0-50J were simulated, and the micromechanical-conductive coupling parameters were calculated as follows: PEEK elastic modulus 3.8GPa, fracture strength 95MPa; Ag particle lattice distortion rate as a function of impact energy, distortion rate 8.2% at 30J; PEEK-Ag interface bonding energy 4.1eV, shear strength 12MPa.
[0027] Based on the actual size of the PEEK-Ag structure circuit (500mm×400mm×300mm), with an embedded Ag conductive path and a 10-meter wire (2mm wide and 2mm thick), a macroscopic multiphysics model of the structure circuit was constructed using ABAQUS and a circuit simulation module. Micromechanical-conductive coupling parameters were imported, and a "crack propagation-conductive path breakage" coupling damage criterion was embedded. For example, when a crack penetrates the conductive path region, the conductivity drops sharply by 90%.
[0028] The impact energies were set to 10J, 20J, and 30J, and the simulation was started. Under the 20J impact, the overall performance of the structure and circuit was predicted: the PEEK matrix developed a 5mm long crack, the Ag conductive path fracture rate was 18%, the structural stiffness retention rate was 82%, the circuit conductivity decreased by 22%, and the signal transmission delay increased by 12ns; under the 30J impact, the crack penetrated the conductive path, the structural load-bearing capacity decreased to 45% of the initial value, and the circuit was open.
[0029] The method of this invention predicts the stress-strain curves of structural circuits at different test points and under different conditions, such as... Figure 5 As shown, the horizontal axis represents strain, and the unit is... The vertical axis represents stress, with values ranging from -50 to 300 MPa. The orange and blue stress-strain curves represent the Myses stress and compressive stress at test point 1, respectively, while the purple and green stress-strain curves represent the Myses stress and compressive stress at test point 2, respectively. Test point 1 is located in the conductive path region, and test point 2 is located at the weak point of the interface. When the Myses stress reaches the yield strength of PEEK, the material will undergo plastic deformation, which can be used to determine the plastic failure and yield region of the structure. Compressive stress is used to analyze the compressive stability of the structure; the greater the compressive stress, the greater the degree of damage.
[0030] Based on the predicted overall performance of the structural circuit, the weak parts of the structural circuit are identified, the layout of the conductive path is optimized, and the stress concentration area of the structure is avoided. After optimization, under a 30J impact, the structural stiffness retention rate is increased to 68%, the conductive path breakage rate is reduced to 8%, and the optimized structural circuit still maintains effective signal transmission.
[0031] In one technical solution of the present invention, a computer-readable storage medium is also provided, storing a computer program that enables a computer to execute the overall performance prediction method for structural circuits based on multi-scale simulation of the present invention.
[0032] In one technical solution of the present invention, an electronic device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for predicting the overall performance of structural circuits based on multi-scale simulation of the present invention.
[0033] In the embodiments disclosed in this application, a computer storage medium may be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, and portable compact disc read-only memory (CD). ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
[0034] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0035] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.
Claims
1. A method for predicting the overall performance of a structured circuit based on multi-scale simulation, characterized in that, Includes the following steps: Step S1: Analyze the material composition of the structural circuit and construct a composite dynamic model of the structural circuit; Step S2: The constructed composite dynamic model is used to conduct simulation analysis on the impact, shear and temperature coupling conditions in the mechanical load to determine the micro-mechanical-conductive coupling parameters of the structural circuit. Step S3: Construct a macroscopic multiphysics model of the structural circuit, import the micromechanical-conductivity coupling parameters into the macroscopic multiphysics model, and set the structural mechanical boundary conditions, circuit operating parameters and coupling damage criteria in the macroscopic multiphysics model to obtain the simulation model of the structural circuit. Step S4: Set multi-condition simulation parameters, and use the multi-condition simulation parameters to perform multi-scale coupled simulation on the simulation model of the structural circuit to obtain the stress distribution, strain field and damage evolution process of the structural circuit, and predict the overall performance of the structural circuit.
2. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, Step S1 includes the following sub-steps: Step S1.1: Analyze the material composition of the structural circuit, including: the structural matrix and the conductive functional phase; Step S1.2: Construct the molecular chains of the structural matrix using the COMPASS force field and periodic boundary conditions, replicate and relax them into an amorphous matrix model, and construct a vacuum layer interface model between structural matrices by stacking them. Step S1.3: Establish a model of the conductive functional phase, and combine it with the amorphous matrix model to construct a sandwich interface model of the structural matrix-conductive functional phase; Step S1.4: Perform NVT and NPT relaxation optimization on the vacuum layer interface model and the sandwich interface model to obtain the composite dynamic model of the structural circuit.
3. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, The micromechanical-conductive coupling parameters of the structured circuit include: the elastic modulus, fracture strength, and damage threshold of the structural matrix in the structured circuit; the lattice distortion rate, atomic diffusion coefficient, and conductivity-stress response function of the conductive functional phase in the structured circuit; and the interfacial binding energy, shear strength, and damage evolution law in the structured circuit.
4. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, The process of constructing the macroscopic multiphysics model of the structural circuit in step S3 is as follows: based on the actual geometric dimensions, structural topology and circuit wiring layout of the structural circuit, a macroscopic multiphysics model of the structural circuit is constructed using multiphysics simulation software; the multiphysics simulation software is a combination of ABAQUS and circuit simulation modules.
5. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, The structural mechanical boundary conditions include: load type and constraint form; the circuit operating parameters include: input voltage and signal frequency.
6. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, The coupling damage criteria include: an energy-based structural mechanical damage criterion and a circuit conductivity damage criterion based on the effective cross-sectional area of the conductive path. The structural mechanical damage criterion and the circuit conductivity damage criterion are used to jointly determine whether the structural circuit is conductive and whether it has failed.
7. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, The multi-condition simulation parameters include: mechanical load level, loading rate, ambient temperature, and circuit operating mode; the overall performance of the structure and circuit includes: structural mechanical performance and circuit performance, wherein the structural mechanical performance includes ultimate bearing capacity, stiffness retention rate, and fatigue life, and the circuit performance includes conductivity attenuation, signal transmission delay, and crosstalk voltage.
8. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, Before the simulation model of the aforementioned circuit structure is put into use, the simulation accuracy needs to be optimized. i: Calculate the error between the overall performance of the structural circuit predicted by the simulation model and the overall performance of the structural circuit verified by experiments under the same working conditions; ii: If the error exceeds the set threshold, dynamically adjust the micromechanical-conductive coupling parameters of the structural circuit and re-predict the overall performance of the structural circuit; iii: Repeat steps i-ii until the error is less than the set threshold, thus completing the accuracy optimization of the simulation model.
9. The method for predicting the overall performance of a structured circuit based on multi-scale simulation according to claim 1, characterized in that, Also includes: Based on the predicted overall performance of the structural circuit, weak points in the structural circuit are identified, and optimizations are performed at the material, structural, and circuit levels. Among them, material-level optimization includes optimizing the particle size and content of conductive functional phases in the structural circuit and interface modification of the sandwich interface model of matrix-conductive functional phase. Structural optimization includes optimizing the topology design of the circuit structure and increasing the thickness of the protective layer for conductive paths. Circuit-level optimization includes optimizing the wiring of the structural circuit and setting up redundant conductive paths.