A method for designing and predicting the performance of a metal matrix composite

Abstract

The present application relates to metal matrix composites, and in particular to a method for designing and predicting the performance of metal matrix composites. The present application uses a finite element method based on the model composite physical properties and structural parameters, fully considers the influence of the interface matrix strengthening microzone on the performance of the composite material during the model establishment process, effectively reflects the influence of the real interface performance and debonding behavior on the service failure of the composite material, truly restores the internal situation of the composite material, realizes the performance-oriented design and performance prediction of the metal matrix composite, and has the characteristics of truly restoring the characteristics of the composite material and accurate performance prediction.

Description

Technical Field

[0001] This invention relates to metal matrix composites, and more specifically to a method for designing and predicting the performance of metal matrix composites. Technical background:

[0002] Metal matrix composites (MMCs) are widely used in aerospace, rail transportation, energy and power, and advanced weaponry due to their high specific strength, high specific modulus, high thermal conductivity, low expansion, high damping, and electrical conductivity. However, while reinforcing the matrix (high strength, high modulus, low expansion, high damping, etc.), the introduction of reinforcements inevitably generates numerous complex interfaces, dividing the matrix into near-interface reinforced regions and far-interface unreinforced regions. This significantly reduces the composite material's ductility, toughness, electrical conductivity, and thermal conductivity, making the design and performance prediction of MMCs difficult. This invention proposes a finite element method based on the physical properties and structural parameters of a model composite material, enabling performance-oriented design and performance prediction of MMCs, which is of great significance for the design and fabrication of high-performance MMCs.

[0003] A technical literature search revealed that the published invention patent with application number "201910054500.6," entitled "A Method for Designing and Predicting the Mechanical Properties of Discontinuously Reinforced Metal Matrix Composites," uses finite element method (FEM) simulation to predict the mechanical properties of composite materials. However, it not only fails to consider the influence of interfacial matrix reinforcement micro-regions on the composite material's properties but also cannot effectively reflect the impact of actual interfacial properties and debonding behavior on the composite material's service failure. To date, there are no literature or patent reports on design and performance prediction methods for metal matrix composites based on matrix micro-regions and interfacial properties. Therefore, this invention proposes a finite element method based on the physical properties and structural parameters of a model composite material to achieve performance-oriented design and performance prediction of metal matrix composites, improving the efficiency of metal matrix composite design and fabrication, and reducing trial-and-error costs. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a design and performance prediction method for metal matrix composites. This method comprises four steps: model material design and preparation, property and interface parameter determination, finite element modeling and characteristic parameter determination, and composite material microstructure and performance design and prediction. This enables the design and performance prediction of metal matrix composites. The specific technical solution is as follows:

[0005] (1) Model material design and preparation: Based on the performance requirements of the composite material, the required metal matrix and reinforcement are selected reasonably, and the corresponding technical processes are adopted to prepare the model composite material.

[0006] (2) Determination of physical properties and interface parameters: First, determine the strength, elongation at break, elastic modulus, Poisson's ratio, density, coefficient of thermal expansion, thermal conductivity, morphology, distribution and size of the reinforcement of the model composite material; Second, determine the stress-strain curve of the model composite material, determine the size and properties of the reinforced micro-regions, and statistically analyze the distribution of the reinforcement.

[0007] (3) Finite element modeling and characteristic parameter determination: Based on the physical property parameters obtained in step (2), the composite material properties and reinforcement distribution, a three-dimensional finite element model is established, and the model parameters are simulated and corrected so that the simulation results are consistent with the model composite material measurement results, including stress-strain curves, fracture behavior and near-interface reinforcement zone size.

[0008] (4) Design and prediction of composite material microstructure and properties: Based on the finite element model obtained in step (3), design the content, size, morphology, distribution and interface structure of the composite material reinforcement with the required properties; and further predict the physical properties, mechanical properties and failure behavior of the composite material.

[0009] The method for designing and predicting the performance of a metal matrix composite material is characterized in that: in step (1), the performance requirements include at least one of mechanical properties, thermal conductivity, electrical conductivity, thermal expansion properties, and damping properties.

[0010] The method for designing and predicting the performance of a metal matrix composite material is described above. Its characteristic is that, in step (1), the metal matrix is ​​at least one of aluminum, magnesium, titanium, iron, copper, nickel, zirconium, niobium, tantalum, and their alloys. The reinforcement is Si, C (graphite particles, carbon nanotubes, graphene, fullerene, etc.), SiC, B4C, Al2O3, B2O3, TiB2, ZrB2, Si3N4, or quasicrystalline materials (such as Al...). 65 Cu 23 Fe 12 It is at least one of the following: high-entropy alloys (such as Co-Cr-Fe-Ni-Ti), with a reinforcement size of 0.02 to 200 μm and a reinforcement content of 0.5 to 50 vol.%. The reinforcement morphology is spherical, polyhedral, short rod-shaped, lamellar, needle-shaped, or onion-shaped.

[0011] The method for designing and predicting the performance of a metal matrix composite material is characterized by the following: In step (1), the technical processes include liquid casting, semi-solid casting, extrusion casting, powder metallurgy, spray molding, pressureless infiltration, pressure infiltration, and 3D printing. The model composite material refers to a composite material initially prepared based on the aforementioned metal matrix, reinforcement characteristics, and technical processes according to performance requirements.

[0012] The method for designing and predicting the performance of a metal matrix composite material is characterized by the following: In step (2), the determination of physical properties and interface parameters, including elongation at break, elastic modulus, Poisson's ratio, density, coefficient of thermal expansion, thermal conductivity, morphology, distribution, and size of the reinforcement, and the stress-strain curve of the model composite material, adopts industry standard measurement methods; the size and performance of the reinforced micro-regions are determined by nanoindentation, with 20 indentations on each side of the interface (interval: 500-800 nm, indentation depth: 50-100 nm, indentation rate: 0.01-0.05 nm·s). -1 ).

[0013] The method for designing and predicting the performance of a metal matrix composite material is characterized in that: in step (2), the modified modulus E is used. r To correct the influence of the non-perfectly rigid indenter on the indentation experiment in nanoindentation. r With respect to the material's elastic modulus E and the indenter's elastic modulus E i The relationship is as follows:

[0014] Where υ and υ i These are the Poisson's ratios of the tested material and the indenter, respectively. The stiffness of the material can be calculated using the formula:

[0015] S (stiffness) is the slope of the highest point of the unloading curve in the experiment, h is the indentation depth, and E... r This is the defined modified modulus, where A is the projected area of ​​the elastic deformation contact surface, P is the maximum load, and the material hardness is calculated using the formula:

[0016] H represents Vickers hardness, P MAX Where A is the maximum load and A is the indentation area.

[0017] The method for designing and predicting the performance of a metal matrix composite material is characterized by the following: In step (3), the morphology, size, and distribution of the reinforcement are obtained by scanning electron microscopy (SEM). Based on the SEM image of the composite material, the distribution of the reinforcement in the finite element model is constructed using Image-Pro. The three-dimensional finite element model is a coupled model of force, heat, electricity, and damping established using commercial finite element software such as Abaqus, ANSYS, COMSOL, MARC, and Hyperworks. The constitutive relationship of the matrix is ​​set using the ductile fracture criterion (Ductile damage), the reinforcement uses the brittle fracture criterion (Brittle cracking), and the interface uses the linear tension-separation criterion.

[0018] The method for designing and predicting the performance of a metal matrix composite material is characterized in that: in step (3), the simulation correction model parameters refer to adjusting the fracture criterion type and parameters, the interface tensile separation criterion type and parameters, the mesh type, and the stress type to make the simulation results consistent with the experimental results, thereby determining the model parameters.

[0019] The method for designing and predicting the performance of a metal matrix composite material is characterized by the following: In step (4), the distribution of the composite material reinforcement is determined by the formula θ=(AB) / A, where A is the average distance between sparsely dispersed adjacent particles, B is the average distance between densely dispersed adjacent particles, and θ∈[0,1]. When θ approaches 0, it indicates that the particles are uniformly dispersed; when θ approaches 1, it indicates that the particles are unevenly dispersed and have agglomeration.

[0020] The method for designing and predicting the performance of metal matrix composites is characterized by the following: Step (4), predicting the performance of the composite material, refers to predicting the mechanical properties, thermal conductivity, electrical conductivity, thermal expansion properties, damping, and fracture failure mode of the designed composite material by changing the size, shape, volume fraction, distribution, and matrix strength of the reinforcement, based on the finite element model of the composite material's physical properties and structural parameters. This is combined with analytical methods such as the "response surface methodology" with multiple variables to provide guidance for the design and preparation of metal matrix composites.

[0021] Compared with existing technologies, this invention adopts the finite element method based on the physical properties and structural parameters of the composite material. During the model building process, it fully considers the influence of the interface matrix reinforcement micro-region on the performance of the composite material, and effectively reflects the influence of the real interface properties and debonding behavior on the service failure of the composite material. It truly restores the internal situation of the composite material, realizes the performance-oriented design and performance prediction of metal matrix composites, and has the characteristics of truly restoring the composite material characteristics and accurate performance prediction. Attached Figure Description

[0022] Figure 1 Flowchart of a method for designing and predicting the performance of ceramic particle-reinforced metal matrix composites

[0023] Figure 2 a. SEM image of 10 vol% B4C (20 μm) / AA6016; b. 3D model of the reinforcing particles; c. 3D model of 10 vol% B4C (20 μm) / AA6016.

[0024] Figure 3 Comparing the simulated 10 vol% B4C (20 μm) / AA6016 matrix dislocation strain-strengthened region with the actual material, it can be seen that the interface strengthening region simulated by the model corresponds to the experimental result.

[0025] Figure 4Comparing the simulated cross-section of the 10 vol% B4C (20 μm) / AA6016 composite material with the actual material, it can be seen that the material failure behavior corresponds to the experiment, and the particle fracture behavior also corresponds to the experiment.

[0026] Figure 5 Comparison of the simulated stress-strain curves of 10 vol% B4C (20 μm) / AA6016 with experimental data.

[0027] Figure 6 Simulated stress distribution diagram of 10 vol% B4C / Al (A. Matrix is ​​pure aluminum B. Matrix is ​​AA6016), B4C grain size D 50 =21μm. As can be seen from the figure, when the tensile displacement ratio is 0.03, the maximum stress on the material and the maximum stress that the particles and their interfaces can withstand gradually decrease with the increase of the matrix strength. Moreover, as can be seen from the color of the stress distribution in the figure, when the matrix is ​​AA6016, the stress distribution range of the matrix is ​​wider and the co-deformation ability is better.

[0028] Figure 7 The stress-strain curves obtained from the simulation of 10 vol% B4C / AA6016 (B4C: 1~50 μm) show that, for composite materials with 10 vol% B4C and AA6016 matrix, to achieve a tensile strength ≥400 MPa and an elongation ≥10%, the particle size of the B4C reinforcement should not exceed D during the preparation process. 50 =12μm. Detailed Implementation

[0029] This invention is implemented according to the following examples, but is not limited to the following instances: The terms used in this invention, unless otherwise stated, generally have the meanings commonly understood by those skilled in the art. It should be understood that these examples are merely illustrative of the invention and are not intended to limit the scope of the invention in any way; In the following embodiments, various processes and methods not described in detail are conventional methods known in the art.

[0030] Example 1

[0031] Objective: To design and prepare B4C / AA6016 composite materials with tensile strength ≥400 MPa and elongation ≥10% using commercially available AA6016 aluminum ingots and B4C powder.

[0032] Commercially available 6016 aluminum ingots and B4C powder (D) were used. 50=22.4μm), B4C was first dried at 200℃ for 2h to remove adsorbed water vapor on the surface. A 5 vol.% B4C / AA6016 model composite material was prepared by melt stirring. The elongation of AA6016 was measured to be 0.1087, elastic modulus to be 83 GPa, Poisson's ratio to be 0.3, and density to be 2.89 g / cm³. 3 Yield strength 280 MPa, ultimate tensile strength 340 MPa, coefficient of thermal expansion 2.1 e -5 / ℃, thermal conductivity 180W / K·m; B4C elongation 0.01, elastic modulus 430GPa, Poisson's ratio 0.17, ultimate tensile strength 1100MPa, density 2.52g / cm³ 3 The coefficient of thermal expansion is 3.4e. -6 The model composite material has a temperature of ℃ and a thermal conductivity of 67 W / K·m. The interfacial elastic modulus of the composite material was determined to be 230 GPa using nanoindentation, and the interfacial bond strength was set at 1000 MPa. The stress-strain curve of the model composite material was determined by uniaxial tensile testing (yield strength 280 MPa, ultimate tensile strength 360 MPa, elongation at break 10.8%). The particle distribution of the model composite material was obtained by scanning electron microscopy (θ = 0.23). The range of the dislocation reinforcement zone (2.1-3 μm) near the interface of the B4C reinforcing particles in the model composite material was obtained by nanoindentation. The physical properties of AA6016, B4C, and the interface parameters were imported into a representative volume element model established using Abaqus / CAE based on the particle distribution of the model composite material. The matrix constitutive relation was set using the ductile fracture criterion (Ductiledamage), the reinforcement using the brittle fracture criterion (Brittle cracking), the interface using the linear tension-separation criterion, the mesh type using C3D4 (four-node tetrahedron), and the mesh stress type using 3D Stress. The loading method was set as follows: ① Cooling from 470℃ to 25℃; ② Uniaxial tension (displacement / representative volume element size = 0.3); ③ Adjustment (fracture criterion type and parameters, interface tensile separation criterion type and parameters, mesh type, stress type) to ensure consistency between simulation and experimental results; ④ Design of composite material reinforcement content, size, morphology, distribution, and interface structure. The composite material was designed to meet the following requirements: tensile strength ≥ 400 MPa, elongation ≥ 10%. The final design of the B4C / AA6016 composite material met the following requirements: reinforcement size ≤ 12 μm, reinforcement content 6.5 vol.%~12.5 vol.%, and reinforcement uniformity (θ = 0.2). The preparation method can be achieved using electromagnetic ultrasonic assisted melt stirring (electromagnetic stirring frequency 12 Hz, ultrasonic power 5 kW).

[0033] Example 2

[0034] Objective: To design and prepare Al2O3 / 2024Al composite materials with tensile strength ≥350 MPa and elongation ≥8% using commercially available 2024Al aluminum ingots and Al2O3 powder.

[0035] First, commercially available 2024Al aluminum ingots and Al2O3 powder (D) were used. 50 =49 μm), a 10 vol.% Al2O3 / 2024Al model composite material was prepared by a semi-solid stirring method. The elongation of 2024Al was measured to be 0.1836, the elastic modulus was 72 GPa, the Poisson's ratio was 0.31, and the density was 2.81 g / cm³. 3 Yield strength 289 MPa, ultimate tensile strength 432 MPa, coefficient of thermal expansion 2.1 e -5 Temperature range: ℃, thermal conductivity 175 W / K·m, elongation of Al2O3 0.02, elastic modulus 373 GPa, Poisson's ratio 0.17, ultimate tensile strength 1100 MPa, density 3.98 g / cm³ 3 The coefficient of thermal expansion is 8.1e. -6The model composite material has a temperature of ℃ and a thermal conductivity of 28 W / K·m. The interfacial elastic modulus of the composite material was determined to be 171 GPa by nanoindentation. The interfacial bond strength was set to 1200 MPa. The stress-strain curve of the model composite material was determined by uniaxial tensile test (yield strength 270 MPa, ultimate tensile strength 330 MPa, elongation at break 6.8%). The particle distribution of the model composite material was obtained by scanning electron microscopy (θ = 0.17). The range of the dislocation reinforcement zone (1.7-2.5 μm) of Al2O3 reinforcing particles near the interface matrix was obtained by nanoindentation. The physical properties of Al2O3, 2024Al and the interface parameters were imported into a representative volume element model established by ANSYS based on the particle distribution of the model composite material. The matrix constitutive relation adopted the ductile fracture criterion (Ductile damage), the reinforcement adopted the brittle fracture criterion (Brittlecracking), the interface adopted the linear tension-separation criterion, the mesh type adopted C3D4 (four-node tetrahedron) and the mesh stress type adopted 3D Stress. ① Cooling from 440℃ to 25℃; ② Performing uniaxial tension (displacement / representative volume element size = 0.2); ③ Adjusting (fracture criterion type and parameters, interface tensile separation criterion type and parameters, mesh type, stress type) to ensure consistency between simulation and experimental results; ④ Designing the content, size, and distribution of the composite material reinforcement. Obtaining simulated stress-strain curve data, and processing the data using the "response surface methodology," it can be determined that if preparing Al2O3 / 2024Al composite materials with tensile strength ≥350 MPa and elongation ≥8%, the Al2O3 particle size should be ≤35 μm, the volume fraction should not exceed 25 vol.%, and the reinforcement uniformity (θ = 0.15) can be achieved using a semi-solid mechanical stirring method (stirring speed 200 r / min).

[0036] Example 3

[0037] Objective: To design and prepare SiC / Al composite materials with interface-reinforced micro-region size ≥2μm and tensile strength ≥120MPa using commercial pure aluminum powder and SiC powder.

[0038] Commercially available pure aluminum powder and SiC powder (D) were used. 50 =23.7 μm), a 10 vol.% SiC / Al model composite material was prepared by powder metallurgy. The elongation of pure aluminum was 0.3187, the elastic modulus was 63 GPa, the Poisson's ratio was 0.33, and the density was 2.71 g / cm³. 3 Yield strength 55 MPa, ultimate tensile strength 68 MPa, coefficient of thermal expansion 2.3°C -5Temperature: ℃; Thermal conductivity: 180 W / K·m; Elongation: 0.01; Elastic modulus: 380 GPa; Poisson's ratio: 0.17; Ultimate tensile strength: 1200 MPa; Density: 3.2 g / cm³ 3 The coefficient of thermal expansion is 3.4e. -6 The model composite material was tested at a temperature of ℃ and a thermal conductivity of 75 W / K·m. The interfacial elastic modulus of the composite material was determined to be 89 GPa using nanoindentation. The interfacial bond strength was set at 400 MPa. The stress-strain curve of the composite material was determined by uniaxial tensile testing (yield strength 70 MPa, ultimate tensile strength 85 MPa, elongation at break 16.2%). The particle distribution of the sample was obtained by scanning electron microscopy (θ = 0.13). The size of the dislocation reinforcement zone near the interface of the SiC reinforcing particles in the model composite material was obtained by nanoindentation (1.3-2.1 μm). The physical properties of pure aluminum, SiC, and the interface were imported into a representative volume element model established by Abaqus / CAE based on the particle distribution of the composite material. The matrix constitutive relation was set to ductile damage, the reinforcement to brittle cracking, the interface to linear tension-separation, the mesh type to C3D4 (four-node tetrahedron), and the mesh stress type to 3D Stress. ① Cooling from 450℃ to 25℃; ② Performing uniaxial tension (displacement / representative volume element size = 0.4); ③ Adjusting (fracture criterion type and parameters, interface tensile separation criterion type and parameters, mesh type, stress type) to ensure consistency between simulation and experimental results; ④ Continuously changing the size (1~200μm) and volume fraction of the reinforcing SiC powder for simulation. Simulation analysis shows that smaller particle size leads to a wider interface-reinforced micro-region and higher tensile strength. When particle size ≤3μm, the width of the near-interface-reinforced micro-region tends to a constant value of approximately 2.8μm, and the uniformity of the reinforcement θ = 0.08. To prepare SiC / Al composites with interface-reinforced micro-region size ≥2μm and tensile strength ≥120MPa, D-type SiC should be selected. 50 The particle size should be ≤7μm and the volume fraction should be 2-15 vol.%. The preparation method adopts powder metallurgy. The matrix and SiC powder should be mixed and ball-milled for 48h, cold-pressed at 350MPa for 5min, the reaction sintering temperature is 525℃, the hot pressing axial pressure is 100MPa, and the holding time is 1h.

[0039] Example 4

[0040] Objective: To design and prepare TiB2 / Cu composite materials with conductivity ≥85% IACS and tensile strength ≥250MPa using commercial pure copper and TiB2 powder.

[0041] Commercially available pure copper and TiB2 particles (D) were used. 50=10 μm), a 10 vol.% TiB2 / Cu model composite material was prepared by melt stirring. The elongation of pure copper was 0.3923, the elastic modulus was 101 GPa, the Poisson's ratio was 0.33, and the density was 8.7 g / cm³. 3 Yield strength 62 MPa, ultimate tensile strength 213 MPa, coefficient of thermal expansion 1.6 e -5 / ℃, thermal conductivity 395W / K·m, resistivity 1.8e -8 Ω·m; TiB2 has an elongation of 0.01, an elastic modulus of 483 GPa, a Poisson's ratio of 0.19, an ultimate tensile strength of 1000 MPa, and a density of 4.52 g / cm³. 3 The coefficient of thermal expansion is 4.8e. -6 / ℃, thermal conductivity 82W / K·m, resistivity 1.4e -7 The interfacial elastic modulus of the model composite material was determined to be 123 GPa using nanoindentation, and the interfacial bond strength was set to 1200 MPa. The stress-strain curve of the model composite material was determined by uniaxial tensile testing (yield strength 65 MPa, ultimate tensile strength 236 MPa, elongation at break 18.7%). The particle distribution of the sample was obtained by scanning electron microscopy (θ = 0.16). The size of the dislocation reinforcement zone near the interface of the TiB2 reinforcing particles in the model composite material (1.4-2.3 μm) was obtained by nanoindentation. The physical properties of pure copper, TiB2, and the interface parameters were imported into a representative volume element model established by Abaqus / CAE based on the particle distribution of the model composite material. The constitutive relation of the matrix was set to ductile fracture criterion (Ductile damage), the reinforcement to brittle fracture criterion (Brittle cracking), the interface to linear tension-separation criterion, the mesh type to C3D4 (four-node tetrahedron), and the mesh stress type to 3D Stress. ① Cooling from 450℃ to 25℃; ② Performing uncoupled thermoelectric analysis (applied current density of 2A / μm). 2 ) and uniaxial tension (displacement / representative volume element size = 0.4); ③ Adjust (fracture criterion type and parameters, interface tensile separation criterion type and parameters, mesh type, stress type) to make the simulation results consistent with the experimental results; ④ Continuously change the size (1~200μm) and volume fraction of the reinforcing TiB2 powder to perform load-displacement simulation and uncoupled thermoelectric analysis, and finally design and prepare TiB2 / Cu composite material with conductivity ≥85%IACS and tensile strength ≥250MPa. The TiB2 particle size should be ≤2μm, the volume fraction is 5-8 vol.%, and the uniformity of the reinforcement (θ = 0.1). The preparation method can be achieved by electromagnetic ultrasonic assisted melt stirring (where the electromagnetic stirring frequency is 10Hz and the ultrasonic power is 3kW).

Claims

1. A method for designing and predicting the performance of metal matrix composites, characterized in that, The method includes four steps: model material design and preparation, property and interface parameter determination, finite element modeling and characteristic parameter determination, and composite material microstructure and performance design and prediction. This enables the design and performance prediction of metal matrix composites. The specific steps are as follows: (1) Model material design and preparation: Based on the performance requirements of composite materials, the required metal matrix and reinforcement are selected in a reasonable manner, and the corresponding technical processes are adopted to prepare the model composite material; (2) Determination of physical properties and interface parameters: First, determine the strength, elongation at break, elastic modulus, Poisson's ratio, density, coefficient of thermal expansion, thermal conductivity, morphology, distribution and size of the reinforcement of the model composite material; Second, determine the stress-strain curve of the model composite material, determine the size and properties of the reinforced micro-regions, and statistically analyze the distribution of the reinforcement. (3) Finite element modeling and characteristic parameter determination: Based on the physical property parameters obtained in step (2), the composite material properties and reinforcement distribution, a three-dimensional finite element model is established, and the model parameters are simulated and corrected so that the simulation results are consistent with the model composite material measurement results, including stress-strain curves, fracture behavior and near-interface reinforcement zone size. (4) Design and prediction of composite material microstructure and properties: Based on the finite element model obtained in step (3), design the content, size, morphology, distribution and interface structure of the composite material reinforcement with the required properties; and further predict the physical properties, mechanical properties and failure behavior of the composite material.

2. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (1), the performance requirements include at least one of mechanical properties, thermal conductivity, electrical conductivity, thermal expansion properties, and damping properties.

3. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (1), the metal matrix is ​​at least one of aluminum, magnesium, titanium, iron, copper, nickel, zirconium, niobium, tantalum and their alloys; the reinforcement is at least one of Si, C, SiC, B4C, Al2O3, B2O3, TiB2, ZrB2, Si3N4, quasicrystalline, high-entropy alloy, the reinforcement size is 0.02~200μm, the reinforcement content is 0.5~50 vol.%, and the reinforcement morphology is spherical, polyhedral, short rod-shaped, lamellar, needle-shaped or onion-shaped.

4. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (1), the technical process includes liquid casting, semi-solid casting, extrusion casting, powder metallurgy, spray molding, pressureless infiltration, pressure infiltration and 3D printing; the model composite material refers to the composite material initially prepared based on the above-mentioned metal matrix, reinforcement characteristics and technical process according to performance requirements.

5. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (2), the determination of physical properties and interface parameters includes the following: elongation at break, elastic modulus, Poisson's ratio, density, coefficient of thermal expansion, thermal conductivity, morphology, distribution, and size of the reinforcement, and the stress-strain curve of the model composite material are measured using industry standard methods; the size and properties of the reinforced micro-regions are determined using nanoindentation, with 20 indentations on each side of the interface; spacing: 500~800nm, indentation depth: 50-100nm, and indentation rate: 0.01~0.05nm·s. -1 .

6. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (2), the modulus E r is used to correct the effect of the non-fully rigid indenter in nanoindentation on the indentation experiment, E r is related to the elastic modulus E of the material and the elastic modulus E i of the indenter as follows: ； Where v and v i These are the Poisson's ratios of the tested material and the indenter, respectively; the stiffness of the material can be calculated using the formula: ； The stiffness S is the slope of the highest point of the unloading curve in the experiment. h E represents the indentation depth. r This is the defined modified modulus, where A is the projected area of ​​the elastic deformation contact surface, P is the maximum load, and the material hardness is calculated using the following formula: ； H represents Vickers hardness, P MAX A0 represents the maximum load and the indentation area.

7. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (3), the morphology, size and distribution of the reinforcement are obtained by scanning electron microscopy (SEM). Based on the SEM image of the composite material, the distribution of the reinforcement in the finite element model is constructed with the help of Image-Pro. The three-dimensional finite element model is a coupled model of force, heat, electricity and damping established by commercial finite element software such as Abaqus, ANSYS, COMSOL, MARC or Hyperworks. The constitutive relationship of the matrix adopts the ductile fracture criterion, the reinforcement adopts the brittle fracture criterion, and the interface adopts the linear tension-separation criterion.

8. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (3), the simulation correction model parameters refer to adjusting the fracture criterion type and parameters, the interface tensile separation criterion type and parameters, the mesh type, and the stress type to make the simulation results consistent with the experimental results, thereby determining the model parameters.

9. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: In step (4), the distribution of the composite material reinforcement is determined by the formula ɵ=(AB) / A, where A is the average distance between sparsely dispersed adjacent particles, B is the average distance between densely dispersed adjacent particles, and ɵ∈[0,1]. When ɵ approaches 0, it indicates that the particles are uniformly dispersed; when ɵ approaches 1, it indicates that the particles are unevenly dispersed and have agglomeration.

10. The method for designing and predicting the performance of a metal matrix composite material as described in claim 1, characterized in that: Step (4), predicting the performance of composite materials, refers to predicting the mechanical properties, thermal conductivity, electrical conductivity, thermal expansion properties, damping, and fracture failure modes of the designed composite materials by changing the size, shape, volume fraction, distribution, and matrix strength of the reinforcement, based on the finite element model of the composite material's physical properties and structural parameters; combined with the "response surface methodology" analysis method with multiple variables, it provides guidance and suggestions for the design and preparation of metal matrix composite materials.

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