Preparation process optimization method and device for diamond reinforced metal matrix composite

Abstract

The invention discloses a preparation process optimization method and device for a diamond reinforced metal matrix composite material, and relates to the technical field of composite material preparation. The method comprises the following steps: carrying out double-coating surface metallization modification treatment on diamond particles to form a composite coating; mixing the to-be-mixed powder and the to-be-mixed matrix powder according to a preset proportion to obtain composite matrix powder, and uniformly mixing the composite coating and the composite matrix powder to form a mixed raw material; real-time recording of pressureless sintering is carried out, a preparation record log is generated, feedback optimization is carried out on sintering process parameters, and sintering optimization process parameters are generated; and alloying treatment parameters are reconfigured to adjust sintering process parameters of subsequent batches of mixed raw materials, and preparation of the diamond reinforced metal matrix composite is achieved. The technical problem of unstable material performance caused by insufficient bonding strength of diamond and a metal matrix in the prior art is solved, and the technical effect of improving the performance of the diamond reinforced metal matrix composite material is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of composite material preparation, and in particular to a preparation process optimization method and device for diamond-reinforced metal-based composite materials. Background Art

[0002] Diamond-reinforced metal matrix composites are a new type of heat dissipation material suitable for the preparation of microchannel heat sink materials for increasingly integrated microelectronic components. However, the preparation of diamond-reinforced metal matrix composites still faces many challenges. On the one hand, the wettability between diamond and the metal matrix is ​​poor, and the interfacial bonding strength is low, which leads to problems such as debonding and cracking at the interface during stress or thermal cycling, seriously affecting the overall performance of the composite material. On the other hand, the optimization of the preparation process parameters is still imperfect. For example, slight fluctuations in key parameters such as sintering temperature, pressure, and time may have a significant impact on the microstructure and properties of the composite material, making it difficult to prepare a composite material with stable and excellent performance. Therefore, how to optimize the preparation process of diamond-reinforced metal matrix composites and improve the bonding strength between diamond and the metal matrix has become a key issue that needs to be solved urgently. Summary of the Invention

[0003] The present application provides a method and apparatus for optimizing the preparation process of diamond-reinforced metal-based composite materials, which solves the technical problem in the prior art of unstable material properties caused by insufficient bonding strength between diamond and metal matrix.

[0004] In a first aspect of the present application, a method for optimizing the preparation process of a diamond-reinforced metal matrix composite material is provided, the method comprising: Diamond particles are subjected to a double-layer surface metallization modification treatment to form a composite coating, wherein the composite coating includes bonding strength data; a powder to be mixed and a matrix powder to be mixed are mixed in a preset ratio to obtain a composite matrix powder, and the composite coating and the composite matrix powder are uniformly mixed based on the bonding strength data to form a mixed raw material; a preparation record log is generated based on real-time recording of pressureless sintering of the mixed raw material, and sintering process parameters are feedback-optimized based on the preparation record log to generate sintering optimized process parameters; alloying treatment parameters are reconfigured according to the sintering optimized process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials to achieve the preparation of diamond-reinforced metal-based composite materials.

[0005] In a second aspect of the present application, a device for optimizing the preparation process of a diamond-reinforced metal-based composite material is provided, the device comprising: A processing module is used to perform double-layer surface metallization modification treatment on diamond particles to form a composite coating, wherein the composite coating includes bonding strength data; a mixing module is used to mix the powder to be mixed with the matrix powder to be mixed in a preset ratio to obtain a composite matrix powder, and the composite coating and the composite matrix powder are uniformly mixed based on the bonding strength data to form a mixed raw material; an optimization module is used to generate a preparation record log based on real-time recording of pressureless sintering of the mixed raw material, and feedback optimize the sintering process parameters based on the preparation record log to generate sintering optimization process parameters; a parameter adjustment module is used to reconfigure the alloying treatment parameters according to the sintering optimization process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials to achieve the preparation of diamond-reinforced metal-based composite materials.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: First, the diamond particles are subjected to a double-layer surface metallization modification treatment to form a composite coating, which includes bonding strength data. Next, the powder to be mixed and the matrix powder to be mixed are mixed in a preset ratio to obtain a composite matrix powder. Based on the bonding strength data, the composite coating and the composite matrix powder are evenly mixed to form a mixed raw material. Then, based on the real-time record of pressureless sintering of the mixed raw material, a preparation record log is generated. Based on the preparation record log, the sintering process parameters are feedback-optimized to generate sintering optimized process parameters. Finally, the alloying treatment parameters are reconfigured according to the sintering optimized process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials to achieve the preparation of diamond-reinforced metal-based composite materials. This solves the technical problem in the prior art of insufficient bonding strength between diamond and metal matrix leading to unstable material performance, and achieves the technical effect of improving the performance of diamond-reinforced metal-based composite materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0008] Figure 1 A schematic flow chart of a method for optimizing the preparation process of a diamond-reinforced metal-based composite material provided in an embodiment of the present application; Figure 2 Schematic diagram of the structure of the preparation process optimization device for diamond-reinforced metal-based composite materials provided in an embodiment of the present application.

[0009] Description of the reference numerals: processing module 11 , mixing module 12 , optimization module 13 , parameter adjustment module 14 . DETAILED DESCRIPTION

[0010] The present application solves the technical problem in the prior art of unstable material properties caused by insufficient bonding strength between diamond and metal matrix by providing a method and device for optimizing the preparation process of diamond-reinforced metal-based composite materials.

[0011] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0012] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0013] Example 1, as Figure 1 As shown, the present application provides a method for optimizing the preparation process of diamond-reinforced metal-based composite materials, wherein the method comprises: The diamond particles are subjected to a double-layer surface metallization modification treatment to form a composite coating, wherein the composite coating includes bonding strength data.

[0014] In the embodiments of the present application, a transition metal layer is deposited on the surface of the diamond particles by chemical plating or physical vapor deposition (PVD) methods. The function of the transition metal layer is to provide good bonding between the diamond and the metal matrix. Then, a bonding metal layer is further deposited on the transition metal layer. The bonding metal layer is used to improve the bonding force between the diamond particles and the metal matrix. The bonding strength data between the composite coating and the diamond particles is obtained by performing mechanical property tests such as tensile, shear, and peeling on the composite coating.

[0015] By forming a composite coating including a transition metal layer and a bonding metal layer on the surface of the diamond particles, the transition metal layer can form a good chemical bond with the diamond surface, and the bonding metal layer has good wettability and bonding with the metal matrix, thereby effectively enhancing the bonding strength between the diamond and the metal matrix.

[0016] Furthermore, the diamond particles are subjected to a double-layer surface metallization modification treatment to form a composite coating, and the method includes: The diamond particles are subjected to surface roughening treatment to obtain pre-treatment surface parameters of the diamond particles; a first metal layer and a second metal layer are simulated and plated on the surfaces of the diamond particles in sequence according to the pre-treatment surface parameters and according to the coating process parameters to form an initial composite coating; the diamond particles are subjected to simulated annealing treatment based on the initial composite coating, and bonding strength data between the initial composite coating and the diamond particles is obtained through an interface shear strength test; the coating process parameters are dynamically optimized according to the bonding strength data, and the first metal layer and the second metal layer are plated on the surfaces of the diamond particles according to the coating optimization process parameters to form the composite coating.

[0017] Preferably, the diamond particles are subjected to surface roughening treatment, such as sandblasting, electrochemical treatment or chemical etching, to increase the surface roughness to improve the adhesion between the diamond particles and the metal layer, thereby obtaining the pre-treated surface parameters of the diamond particles, including surface roughness, porosity, etc. According to the pre-treated surface parameters and the coating process parameters, the first metal layer and the second metal layer are simulated and plated in sequence to form an initial composite coating, wherein the first metal layer is a transition metal layer to enhance the bonding between the surface of the diamond particles and the metal matrix, and the second metal layer is a bonding metal layer to further improve the bonding strength. After the initial composite coating is formed, the diamond particles are subjected to a simulated annealing treatment; the initial composite coating is heat-treated by a simulated annealing process to simulate the high temperature environment that may be encountered in actual use, thereby promoting diffusion between the metal layers and forming a stronger bonding layer; after annealing, the bonding strength between the composite coating and the diamond particles is evaluated by an interface shear strength test to obtain accurate bonding strength data. Based on the bond strength data obtained, the coating process parameters are dynamically optimized, adjusting process parameters such as coating thickness, deposition rate, and annealing temperature to enhance the bond strength between the composite coating and the diamond particles. Based on the optimized process parameters, the first and second metal layers are re-plated to form the final composite coating, ensuring excellent bonding between the diamond particles and the metal matrix, and improving the overall performance of the diamond-reinforced metal matrix composite.

[0018] The powder to be mixed and the matrix powder to be mixed are mixed in a preset ratio to obtain a composite matrix powder, and the composite coating and the composite matrix powder are uniformly mixed based on the bonding strength data to form a mixed raw material.

[0019] In the embodiment of the present application, a powder to be mixed and a matrix powder to be mixed are mixed in a predetermined ratio by mechanical alloying to obtain a composite matrix powder. The powder to be mixed is molybdenum powder, the matrix powder to be mixed is copper matrix powder, and the composite matrix powder is a Mo-Cu composite matrix powder.

[0020] Mechanical alloying is a solid-state reaction synthesis method that uses high-energy ball milling and other techniques to grind molybdenum (Mo) powder and copper (Cu) powder at an appropriate molar ratio for a long time at high speed to achieve effective alloying between the metal powders. During this process, the powders rub and collide with each other, forming a uniform Mo-Cu composite matrix powder.

[0021] Based on the aforementioned bonding strength data, the metallized diamond particles of the composite coating are uniformly mixed with the prepared Mo-Cu composite matrix powder. During this mixing process, mechanical mixing equipment, such as a three-dimensional mixer or ball mill, can be used to ensure that the diamond particles and the composite matrix powder are fully dispersed and evenly distributed, forming a mixed material with optimal bonding strength.

[0022] Furthermore, the powder to be mixed and the matrix powder to be mixed are mixed in a preset ratio to obtain a composite matrix powder, and the composite coating and the composite matrix powder are uniformly mixed based on the bonding strength data to form a mixed raw material. The method includes: The powder to be mixed and the matrix powder to be mixed are mechanically alloyed in a preset ratio to prepare a composite matrix powder; a mixing analysis is performed based on the bonding strength data of the composite coating to determine the mixing ratio and mixing process parameters; the diamond particles of the composite coating and the composite matrix powder are added to a three-dimensional mixer in the mixing ratio, and mixed in stages according to the mixing process parameters to form a mixed raw material.

[0023] The composite matrix powder was prepared by mechanical alloying treatment. Specifically, molybdenum powder and copper matrix powder were mixed in a ratio of 0.5-2.0wt%, and the ball-to-material ratio was set to 8:1 to 12:1. Under an argon protective atmosphere, the mixture was ball milled at a speed of 300-500rpm for 2-4 hours. After ball milling, the obtained powder particle size distribution was between 10 and 50μm, and the molybdenum particles were uniformly dispersed in the copper matrix powder, thereby obtaining a uniform Mo-Cu composite matrix powder.

[0024] After obtaining the composite matrix powder, a mixing analysis is performed based on the bonding strength data of the composite coating to determine the mixing ratio and mixing process parameters. Interfacial shear strength testing of the composite coating (the coating after metallization of the diamond particles) is performed to obtain data on the bonding strength between the diamond particles and the coating. This bonding strength reflects the strength of the bond between the diamond particles and the composite coating, directly affecting the dispersion and stability of the diamond particles during the mixing process. Depending on the bonding strength, different diamond volume fractions are set. The optimal mixing ratio of diamond particles to the metal matrix is ​​determined based on the interfacial shear strength. For example, if the interfacial shear strength is ≥150 MPa, the diamond volume fraction is set to 50%-60%; if the interfacial shear strength is between 100 and 150 MPa, the diamond volume fraction is set to 40%-50%; if the interfacial shear strength is less than 100 MPa, the diamond volume fraction should be reduced to 30%-40%, and the coating process should be re-optimized to ensure good bonding between the diamond particles and the metal matrix. Based on the bond strength data, the volume fraction of diamond particles is determined and then proportioned with the composite matrix powder to achieve the optimal mixing ratio. Based on the determined mixing ratio and bond strength data, the mixing process parameters are further optimized, including the selection of mixing equipment, mixing time, and mixing speed. This ensures that the diamond particles and composite matrix powder are evenly dispersed during the mixing process, avoiding particle agglomeration or uneven distribution, thereby ensuring the uniformity of the final mixed raw materials and the stability of the material.

[0025] Based on the determined mixing ratio and mixing process parameters, the composite-coated diamond particles and composite matrix powder are added to a three-dimensional mixer in the set proportions. The three-dimensional mixer uses multi-axis rotation to ensure uniform mixing of the diamond particles and composite matrix powder. A phased mixing process is employed, initially with dry mixing followed by wet mixing, to ensure uniformity of the mixed materials. Throughout the mixing process, based on real-time monitoring of mixing uniformity and the coefficient of variation, mixing parameters are further adjusted to ensure uniform dispersion of the diamond particles and composite matrix powder, resulting in a highly uniform mixed material, providing a stable foundation for subsequent sintering or other molding processes.

[0026] Furthermore, the diamond particles of the composite coating and the composite matrix powder are added to a three-dimensional mixer according to the mixing ratio, and mixed in stages according to the mixing process parameters to form a mixed raw material. The method includes: Dry mixing is performed in a three-dimensional mixer according to the mixing process parameters to generate dry mixing stage parameters; wet mixing is performed in a three-dimensional mixer according to the mixing process parameters to generate wet mixing stage parameters; real-time monitoring is performed based on the dry mixing stage parameters and the wet mixing stage parameters to obtain real-time mixing uniformity, and the real-time mixing uniformity includes a mixing variation coefficient; when the mixing variation coefficient is less than a preset threshold value, the mixed raw material is formed according to the real-time mixing uniformity.

[0027] Dry mixing is performed in a three-dimensional mixer according to the set mixing process parameters to generate dry mixing stage parameters, including powder particle size distribution and bulk density. Specifically, the mixer speed is set to 20-30 rpm and the mixing time is set to 30-60 minutes to ensure initial dispersion of the diamond particles and the Mo-Cu composite matrix powder and prevent aggregation between particles.

[0028] After dry mixing is complete, wet mixing is continued in a three-dimensional mixer according to the mixing process parameters to determine the wet mixing stage parameters, including particle morphology, moisture content, and adhesion after wet mixing. During this stage, 0.5-1.0 vol% zinc stearate is added to the mixer as a dispersant. Zinc stearate effectively reduces adhesion between particles and further improves the dispersion of diamond particles. During wet mixing, increase the mixer speed to 50-80 rpm and continue mixing for 20-40 minutes.

[0029] Throughout the mixing process, a laser particle size analyzer provides real-time monitoring to analyze mixing uniformity. Using the principle of laser scattering, the laser particle size analyzer accurately measures the particle size distribution and size during mixing, providing real-time information on the size, shape, and distribution of each particle. By monitoring the particle size distribution, the laser particle size analyzer provides a detailed particle size distribution curve, reflecting the distribution of particles within the mixed raw materials and helping to identify problems such as particle aggregation and uneven dispersion. Based on this data, the coefficient of variation (CV) can be calculated to quantify the uniformity of the mixed raw materials. The CV is the ratio of the standard deviation of the particle size distribution to the average particle size. A smaller value indicates a more uniform mix. Conversely, a larger CV indicates poor mixing performance and insufficient particle dispersion, necessitating adjustment of mixing process parameters. The CV is calculated as σ / μ × 100%, where σ is the standard deviation of the particle size distribution, reflecting the degree of particle size dispersion, and μ is the average particle size, indicating the tendency of particle size concentration.

[0030] When the real-time mixing uniformity meets the standard, that is, the mixing coefficient of variation is less than the preset threshold, it means that the mixing process has been completed and the expected uniformity has been achieved, forming the required mixed raw material.

[0031] A preparation record log is generated based on the real-time record of the pressureless sintering of the mixed raw materials, and feedback optimization of sintering process parameters is performed based on the preparation record log to generate sintering optimized process parameters.

[0032] Real-time recording of pressureless sintering based on mixed raw materials, i.e., detailed data collection of the sintering process, generating a preparation log. The preparation log records key process parameters during the sintering process, such as sintering temperature, holding time, atmosphere pressure, temperature ramp rate, etc.

[0033] After generating a preparation log, feedback optimization of the sintering process parameters is performed based on this log. By comparing the actual process data in the log with the preset ideal process parameters, the strengths and weaknesses of the current sintering process can be analyzed and potential areas for improvement can be identified. Through this feedback optimization process, the optimized sintering process parameters are generated.

[0034] Furthermore, based on the real-time record of the pressureless sintering of the mixed raw material, a preparation record log is generated, and based on the preparation record log, feedback optimization is performed on the sintering process parameters to generate sintering optimized process parameters. The method includes: The pressureless sintering process of the mixed raw materials is collected in real time through multiple sensors to generate a dynamic sintering parameter data set; a preparation record log is constructed based on the dynamic sintering parameter data set, and a correlation analysis is performed between the sintering process parameters and the composite material properties of the mixed raw materials based on the preparation record log to determine a process-performance mapping network; an optimization target is set according to the process-performance mapping network, and the sintering process parameters are optimized and solved based on the optimization target to generate the sintering optimized process parameters.

[0035] The pressureless sintering process of the mixed raw materials is monitored in real time using multiple sensors. These sensors primarily monitor key process parameters, such as sintering temperature, holding time, atmosphere pressure, and interfacial reaction data. This data forms a dynamic sintering parameter dataset. Sensors, including temperature sensors, atmosphere pressure sensors, and gas composition analyzers, continuously monitor environmental changes during the sintering process and transmit data in real time. This real-time data is stored and organized into a dynamic sintering parameter dataset, providing a complete dynamic record for process analysis and optimization.

[0036] Based on the collected dynamic sintering parameter data set, a preparation record log was constructed. The preparation record log contains all the key data of the sintering process, including the rise and fall of the sintering temperature, the control of the holding time, the change of the atmosphere pressure, and the interface reaction data during the sintering process.

[0037] Based on the data from the preparation log, a correlation analysis is performed between sintering process parameters and the properties of the composite material of the mixed raw materials. A process-performance mapping network is determined, which shows the specific impact of different sintering process parameters on material properties. Optionally, a machine learning model is used to correlate sintering process parameters with composite material performance indicators. First, key process parameters (such as sintering temperature, holding time, and atmosphere pressure) and composite material performance indicators (such as hardness, compressive strength, wear resistance, and thermal stability) are collected and preprocessed, including removing outliers, filling missing values, and standardizing the data. Next, feature selection methods are used to extract significant features from the process parameters and performance indicators, generating feature engineering to improve the model's predictive ability. Then, an appropriate machine learning model (such as a regression model, neural network, or random forest) is selected for training, and cross-validation is used to optimize the model parameters to ensure that the model can accurately predict the composite material's properties. During the model evaluation phase, the model's predictive ability is verified using metrics such as mean squared error and coefficient of determination, and the model is optimized to improve accuracy. The trained model can predict the composite material's properties based on the input sintering process parameters.

[0038] Based on the established process-performance mapping network, optimization goals are set, such as improving the material's hardness, compressive strength, or thermal stability. Through goal setting, the sintering process parameters are optimized and solved based on the process-performance mapping network. Optimization algorithms (such as particle swarm optimization and genetic algorithms) can be used to adjust parameters such as sintering temperature, holding time, and atmosphere pressure to obtain the optimized sintering process parameters.

[0039] Furthermore, a preparation record log is constructed based on the dynamic sintering parameter data set, the method comprising: Decomposition is performed based on the dynamic sintering parameter data set to obtain sintering temperature data, holding time data, atmosphere pressure data, and interface reaction data; the sintering temperature data, the holding time data, and the atmosphere pressure data are stored as a structured data table in time series; feature extraction is performed based on the interface reaction data, and the interface reaction data is associated with a timestamp according to the interface reaction characteristics to obtain reaction time associated parameters; anomaly analysis is performed based on the reaction time associated parameters in combination with the structured data table, and abnormal results are automatically marked to determine abnormal data segments; data integration is performed on the abnormal data segments, the reaction time associated parameters, and the structured data table to construct the preparation record log.

[0040] Based on the dynamic sintering parameter dataset, the core parameters of the sintering process were decomposed and extracted, including sintering temperature data, holding time data, atmosphere pressure data, and interface reaction data. The sintering temperature data, holding time data, and atmosphere pressure data reflect the effects of temperature control, time management, and the atmosphere environment on material reactions during the sintering process, respectively. The interface reaction data reflects the interface reaction between the diamond particles and the metal matrix. Next, the sintering temperature data, holding time data, and atmosphere pressure data were stored in a structured data table in a time series format to accurately record the timing of the sintering process.

[0041] Based on the interface reaction data, feature extraction is performed, primarily focusing on features related to the interface reaction, such as the thickness of the Mo2C layer, the carbon diffusion depth at the diamond edge, and the porosity. These features are important indicators of the reaction between the diamond particles and the metal matrix during sintering and directly affect the performance of the composite material. Based on the extracted interface reaction features, the interface reaction data is correlated with the timestamp to obtain the reaction time correlation parameter.

[0042] By performing an anomaly analysis on the obtained reaction time-related parameters and structured data tables, we can identify unusual fluctuations or inconsistencies in the data, such as excessive temperature fluctuations or abnormal atmosphere pressure. Based on the anomaly analysis results, we automatically mark anomalous data segments, which may indicate instabilities or process errors during the sintering process. Finally, we integrate the anomalous data segments, reaction time-related parameters, and structured data tables to generate a complete preparation log.

[0043] Furthermore, an optimization target is set according to the process-performance mapping network, and sintering process parameters are optimized and solved based on the optimization target to generate sintering optimized process parameters. The method includes: A multi-objective solution is performed on the sintering process parameters based on the optimization objectives to determine an initialized particle group, where each particle in the initialized particle group contains a set of sintering process parameters; an adaptive inertia weight is introduced to calculate the initialized particle group to determine the fitness values ​​of multiple particles; and the particle positions of the initialized particle group are iteratively updated according to the fitness values ​​of the multiple particles until a convergence condition is reached, thereby obtaining the sintering optimization process parameters.

[0044] Based on the set optimization objectives, a multi-objective solution is applied to the sintering process parameters. The multi-objective optimization aims to simultaneously maximize thermal conductivity and interfacial shear strength while minimizing porosity, and a comprehensive optimization objective is obtained through a weighted combination.

[0045] An initial particle swarm is determined. Each particle in the initial particle swarm contains a set of sintering process parameters, including sintering temperature, holding time, and atmosphere pressure. Each particle in the initial particle swarm represents a possible solution. These particles are searched in the solution space using an optimization algorithm, gradually adjusting the sintering process parameters to meet the optimization goal.

[0046] In the process of particle swarm optimization, adaptive inertia weight is used to calculate the initialization particle swarm; adaptive inertia weight can dynamically adjust the search pace according to the current state of the particle swarm, so that particles can find a balance between global search and local search, avoiding falling into the local optimal solution; usually in the optimization process, as the number of iterations increases, the adaptive inertia weight will gradually decrease to encourage particles to conduct more local searches when approaching the optimal solution. Adaptive inertia weight: ;in, is the inertia weight of the kth iteration, and are the initial and final inertia weight values, k is the current iteration number, and K is the maximum iteration number.

[0047] According to the sintering process parameters represented by each particle, its fitness value is calculated. The fitness value is a measure of the degree to which the set of process parameters meets the optimization target. The higher the fitness value, the better the performance of the set of process parameters on multiple optimization targets. Exemplarily, the performance of each target is calculated by the sintering process parameters corresponding to the particles. For example, the thermal conductivity is calculated using a heat conduction model, the interface shear strength is determined by experiments or simulations, and the porosity is calculated based on the sintering process; then, the performance indicators of each target are normalized; then, different weights are assigned to each target according to its importance, for example, the weights of thermal conductivity and interface shear strength are 0.4, and the weight of porosity is 0.2; the normalized target values ​​are multiplied by the corresponding weights and weighted combined to obtain a comprehensive fitness value, which represents the comprehensive performance of the set of sintering process parameters.

[0048] Based on the fitness values ​​of multiple particles, the particle positions of the particle swarm are iteratively updated. In each iteration, particles update their positions based on inertia, individual experience, and global optimal experience. The particle positions represent the new sintering process parameters. This process continues until the convergence condition is met, that is, the fitness change is less than 1% for 10 consecutive generations. At this point, the search results of the particle swarm have stabilized, and the obtained sintering process parameters are the final optimized results.

[0049] The alloying treatment parameters are reconfigured according to the sintering optimization process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials to achieve the preparation of diamond-reinforced metal-based composite materials.

[0050] Based on the optimized sintering process parameters, the alloying treatment parameters are reconfigured and the sintering process parameters of subsequent batches of mixed raw materials are adjusted to achieve the preparation of diamond-reinforced metal-matrix composites. Specifically, the target parameters are determined based on the optimized sintering process parameters, and the alloying treatment conditions are then adjusted to ensure that each batch of mixed raw materials achieves optimal performance during the sintering process. Subsequently, the adjusted alloying treatment parameters are mixed with the diamond particles of the composite coating to form a new uniform mixed raw material, and pressureless sintering is performed according to the optimized sintering process parameters.

[0051] Furthermore, the sintering process parameters of subsequent batches of mixed raw materials are adjusted by reconfiguring alloying treatment parameters according to the sintering optimization process parameters, and the method includes: Reverse deduction is performed based on the sintering optimization process parameters to determine target parameters, and mechanical alloying treatment conditions of subsequent batches are adjusted based on the target parameters to prepare composite matrix powder optimization parameters; the composite matrix powder optimization parameters are mixed with diamond particles of the composite coating to form a new batch of mixed raw materials; the new batch of mixed raw materials is pressurelessly sintered according to the sintering optimization process parameters to achieve the preparation of diamond-reinforced metal-based composite materials.

[0052] Preferably, reverse deduction is performed based on the obtained sintering optimization process parameters to determine target parameters. These target parameters include key process conditions such as sintering temperature, holding time, and atmosphere pressure, aiming to ensure that each batch of sintering process can achieve the expected performance targets. Based on these target parameters, the mechanical alloying treatment conditions of subsequent batches are adjusted to optimize the preparation process of the composite matrix powder. Adjustment of the mechanical alloying treatment parameters includes changing the ball milling time, rotation speed, ball-to-material ratio, etc., so as to prepare a composite matrix powder that meets the optimization target. Next, the obtained composite matrix powder optimization parameters are mixed with the diamond particles of the composite coating to ensure that the diamond particles are evenly distributed in the metal matrix to form a new batch of mixed raw materials. Finally, the new batch of mixed raw materials is pressurelessly sintered according to the sintering optimization process parameters to ensure that the preparation of diamond-reinforced metal matrix composite materials is achieved under optimized sintering conditions. During the sintering process, parameters such as temperature, time, and atmosphere pressure are precisely controlled to ensure that the bonding strength between the diamond particles and the metal matrix is ​​optimized, ultimately obtaining a diamond-reinforced metal matrix composite material with excellent thermal conductivity, interfacial shear strength, and low porosity.

[0053] Furthermore, the new batch of mixed raw materials is subjected to pressureless sintering according to the sintering optimization process parameters to achieve the preparation of diamond-reinforced metal matrix composite materials, and the method includes: Based on the new batch of mixed raw materials, continuous batches of pressureless sintering are carried out according to the sintering optimization process parameters to prepare diamond-reinforced metal matrix composite materials; performance tests are performed on the diamond-reinforced metal matrix composite materials to obtain performance test results; if the performance test results do not reach a preset threshold, the weights of the process-performance mapping network are corrected, and iterative optimization is performed until the performance test results reach the preset threshold, completing the adjustment of the sintering process parameters and realizing the preparation of diamond-reinforced metal matrix composite materials.

[0054] Based on the new batch of mixed raw materials, continuous batches of pressureless sintering are carried out according to the sintering optimization process parameters to ensure that the diamond particles and the metal matrix are optimally bonded during the sintering process. The prepared diamond-reinforced metal matrix composite material is subjected to performance testing, including testing of indicators such as the thermal conductivity, interface shear strength, and porosity of the composite material; based on the performance test results, it is evaluated whether the prepared material meets the design requirements and preset standards. If the performance test results do not reach the preset threshold, the sintering process needs to be adjusted. By correcting the weights of the process-performance mapping network, the sintering process parameters are updated to optimize the relationship between process and performance. By continuously iteratively optimizing the sintering process parameters, the sintering temperature, time and other process conditions are gradually adjusted until the performance test results reach the preset threshold requirements.

[0055] In summary, the embodiments of the present application have at least the following technical effects: First, the diamond particles are subjected to a double-layer surface metallization modification treatment to form a composite coating, which includes bonding strength data. Next, the powder to be mixed and the matrix powder to be mixed are mixed in a preset ratio to obtain a composite matrix powder. Based on the bonding strength data, the composite coating and the composite matrix powder are evenly mixed to form a mixed raw material. Then, based on the real-time record of pressureless sintering of the mixed raw material, a preparation record log is generated. Based on the preparation record log, the sintering process parameters are feedback-optimized to generate sintering optimized process parameters. Finally, the alloying treatment parameters are reconfigured according to the sintering optimized process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials to achieve the preparation of diamond-reinforced metal-based composite materials. This solves the technical problem in the prior art of insufficient bonding strength between diamond and metal matrix leading to unstable material performance, and achieves the technical effect of improving the performance of diamond-reinforced metal-based composite materials.

[0056] Example 2, based on the same inventive concept as the preparation process optimization method of the diamond-reinforced metal matrix composite material in the above embodiment, Figure 2 As shown, the present application provides a preparation process optimization device for diamond-reinforced metal matrix composite materials, wherein the device includes: A processing module 11 is used to perform double-layer surface metallization modification treatment on diamond particles to form a composite coating, wherein the composite coating includes bonding strength data; a mixing module 12 is used to mix the powder to be mixed with the matrix powder to be mixed in a preset ratio to obtain a composite matrix powder, and to uniformly mix the composite coating with the composite matrix powder based on the bonding strength data to form a mixed raw material; an optimization module 13 is used to perform real-time recording of pressureless sintering of the mixed raw material, generate a preparation record log, perform feedback optimization on the sintering process parameters based on the preparation record log, and generate sintering optimized process parameters; a parameter adjustment module 14 is used to reconfigure the alloying treatment parameters according to the sintering optimized process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials, thereby realizing the preparation of diamond-reinforced metal-based composite materials.

[0057] Furthermore, the processing module 11 is used to execute the following method: The diamond particles are subjected to surface roughening treatment to obtain pre-treatment surface parameters of the diamond particles; a first metal layer and a second metal layer are simulated and plated on the surfaces of the diamond particles in sequence according to the pre-treatment surface parameters and according to the coating process parameters to form an initial composite coating; the diamond particles are subjected to simulated annealing treatment based on the initial composite coating, and bonding strength data between the initial composite coating and the diamond particles is obtained through an interface shear strength test; the coating process parameters are dynamically optimized according to the bonding strength data, and the first metal layer and the second metal layer are plated on the surfaces of the diamond particles according to the coating optimization process parameters to form the composite coating.

[0058] Furthermore, the mixing module 12 is configured to perform the following method: The powder to be mixed and the matrix powder to be mixed are mechanically alloyed in a preset ratio to prepare a composite matrix powder; a mixing analysis is performed based on the bonding strength data of the composite coating to determine the mixing ratio and mixing process parameters; the diamond particles of the composite coating and the composite matrix powder are added to a three-dimensional mixer in the mixing ratio, and mixed in stages according to the mixing process parameters to form a mixed raw material.

[0059] Furthermore, the mixing module 12 is configured to perform the following method: Dry mixing is performed in a three-dimensional mixer according to the mixing process parameters to generate dry mixing stage parameters; wet mixing is performed in a three-dimensional mixer according to the mixing process parameters to generate wet mixing stage parameters; real-time monitoring is performed based on the dry mixing stage parameters and the wet mixing stage parameters to obtain real-time mixing uniformity, and the real-time mixing uniformity includes a mixing variation coefficient; when the mixing variation coefficient is less than a preset threshold value, the mixed raw material is formed according to the real-time mixing uniformity.

[0060] Furthermore, the optimization module 13 is used to perform the following method: The pressureless sintering process of the mixed raw materials is collected in real time through multiple sensors to generate a dynamic sintering parameter data set; a preparation record log is constructed based on the dynamic sintering parameter data set, and a correlation analysis is performed between the sintering process parameters and the composite material properties of the mixed raw materials based on the preparation record log to determine a process-performance mapping network; an optimization target is set according to the process-performance mapping network, and the sintering process parameters are optimized and solved based on the optimization target to generate the sintering optimized process parameters.

[0061] Furthermore, the optimization module 13 is used to perform the following method: Decomposition is performed based on the dynamic sintering parameter data set to obtain sintering temperature data, holding time data, atmosphere pressure data, and interface reaction data; the sintering temperature data, the holding time data, and the atmosphere pressure data are stored as a structured data table in time series; feature extraction is performed based on the interface reaction data, and the interface reaction data is associated with a timestamp according to the interface reaction characteristics to obtain reaction time associated parameters; anomaly analysis is performed based on the reaction time associated parameters in combination with the structured data table, and abnormal results are automatically marked to determine abnormal data segments; data integration is performed on the abnormal data segments, the reaction time associated parameters, and the structured data table to construct the preparation record log.

[0062] Furthermore, the optimization module 13 is used to perform the following method: A multi-objective solution is performed on the sintering process parameters based on the optimization objectives to determine an initialized particle group, where each particle in the initialized particle group contains a set of sintering process parameters; an adaptive inertia weight is introduced to calculate the initialized particle group to determine the fitness values ​​of multiple particles; and the particle positions of the initialized particle group are iteratively updated according to the fitness values ​​of the multiple particles until a convergence condition is reached, thereby obtaining the sintering optimization process parameters.

[0063] Furthermore, the parameter adjustment module 14 is used to perform the following method: Reverse deduction is performed based on the sintering optimization process parameters to determine target parameters, and mechanical alloying treatment conditions of subsequent batches are adjusted based on the target parameters to prepare composite matrix powder optimization parameters; the composite matrix powder optimization parameters are mixed with diamond particles of the composite coating to form a new batch of mixed raw materials; the new batch of mixed raw materials is pressurelessly sintered according to the sintering optimization process parameters to achieve the preparation of diamond-reinforced metal-based composite materials.

[0064] Furthermore, the parameter adjustment module 14 is used to perform the following method: Based on the new batch of mixed raw materials, continuous batches of pressureless sintering are carried out according to the sintering optimization process parameters to prepare diamond-reinforced metal matrix composite materials; performance tests are performed on the diamond-reinforced metal matrix composite materials to obtain performance test results; if the performance test results do not reach a preset threshold, the weights of the process-performance mapping network are corrected, and iterative optimization is performed until the performance test results reach the preset threshold, completing the adjustment of the sintering process parameters and realizing the preparation of diamond-reinforced metal matrix composite materials.

[0065] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0066] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0067] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A method for optimizing the preparation process of diamond-reinforced metal matrix composite materials, characterized in that: The method comprises: Performing a double-layer surface metallization modification treatment on the diamond particles to form a composite coating, wherein the composite coating includes bonding strength data; Mixing the powder to be mixed with the matrix powder to be mixed in a preset ratio to obtain a composite matrix powder, and uniformly mixing the composite coating and the composite matrix powder based on the bonding strength data to form a mixed raw material; generating a preparation record log based on a real-time record of the pressureless sintering of the mixed raw materials, performing feedback optimization on sintering process parameters based on the preparation record log, and generating sintering optimized process parameters; The alloying treatment parameters are reconfigured according to the sintering optimization process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials to achieve the preparation of diamond-reinforced metal-based composite materials.

2. The method for optimizing the preparation process of diamond-reinforced metal matrix composite material according to claim 1, wherein: The diamond particles are subjected to a double-layer surface metallization modification treatment to form a composite coating, the method comprising: performing surface roughening treatment on diamond particles to obtain pre-treated surface parameters of the diamond particles; According to the pre-treatment surface parameters, the surface of the diamond particles is simulated to be plated with a first metal layer and a second metal layer in sequence according to the plating process parameters to form an initial composite plating layer; Performing a simulated annealing process on the diamond particles based on the initial composite coating, and obtaining bonding strength data between the initial composite coating and the diamond particles through an interface shear strength test; The coating process parameters are dynamically optimized according to the bonding strength data, and the first metal layer and the second metal layer are plated on the surface of the diamond particles according to the coating optimization process parameters to form the composite coating.

3. The method for optimizing the preparation process of diamond-reinforced metal matrix composite materials according to claim 1, wherein: The powder to be mixed and the matrix powder to be mixed are mixed in a preset ratio to obtain a composite matrix powder, and the composite coating and the composite matrix powder are uniformly mixed based on the bonding strength data to form a mixed raw material. The method includes: Mechanically alloying the powder to be mixed and the matrix powder to be mixed according to a preset ratio to prepare a composite matrix powder; Performing a mixing analysis based on the bonding strength data of the composite coating to determine a mixing ratio and mixing process parameters; The diamond particles of the composite coating and the composite matrix powder are added into a three-dimensional mixer according to the mixing ratio, and mixed in stages according to the mixing process parameters to form a mixed raw material.

4. The method for optimizing the preparation process of diamond-reinforced metal matrix composite material according to claim 3, wherein: The diamond particles of the composite coating and the composite matrix powder are added to a three-dimensional mixer according to the mixing ratio, and mixed in stages according to the mixing process parameters to form a mixed raw material. The method includes: Performing dry mixing in a three-dimensional mixer according to the mixing process parameters to generate dry mixing stage parameters; Performing wet mixing in a three-dimensional mixer according to the mixing process parameters to generate wet mixing stage parameters; Performing real-time monitoring based on the dry mixing stage parameters and the wet mixing stage parameters to obtain real-time mixing uniformity, wherein the real-time mixing uniformity includes a mixing variation coefficient; When the mixing variation coefficient is less than a preset threshold, the mixed raw material is formed according to the real-time mixing uniformity.

5. The method for optimizing the preparation process of diamond-reinforced metal matrix composite material according to claim 1, wherein: Generating a preparation record log based on real-time records of pressureless sintering of the mixed raw materials, performing feedback optimization on sintering process parameters based on the preparation record log, and generating sintering optimized process parameters, the method comprising: The pressureless sintering process of the mixed raw materials is collected in real time by multiple sensors to generate a dynamic sintering parameter data set; Building a preparation record log based on the dynamic sintering parameter data set, and performing correlation analysis on the sintering process parameters and the composite material properties of the mixed raw materials based on the preparation record log to determine a process-performance mapping network; An optimization target is set according to the process-performance mapping network, and the sintering process parameters are optimized and solved based on the optimization target to generate the optimized sintering process parameters.

6. The method for optimizing the preparation process of diamond-reinforced metal matrix composite material according to claim 5, characterized in that: Constructing a preparation record log based on the dynamic sintering parameter data set, the method comprising: Decomposing the dynamic sintering parameter data set to obtain sintering temperature data, holding time data, atmosphere pressure data, and interface reaction data; Storing the sintering temperature data, the holding time data, and the atmosphere pressure data in a time series as a structured data table; Extracting features based on the interface reaction data, and associating the interface reaction data with a timestamp according to the interface reaction features to obtain a reaction time association parameter; Performing anomaly analysis based on the reaction time correlation parameters in combination with the structured data table, automatically marking the anomaly results, and determining an abnormal data segment; The abnormal data segment, the reaction time associated parameter, and the structured data table are integrated to construct the preparation record log.

7. The method for optimizing the preparation process of diamond-reinforced metal matrix composite material according to claim 5, characterized in that: The optimization target is set according to the process-performance mapping network, and the sintering process parameters are optimized and solved based on the optimization target to generate the sintering optimized process parameters. The method includes: performing a multi-objective solution on the sintering process parameters based on the optimization objective to determine an initialization particle group, wherein each particle in the initialization particle group comprises a set of sintering process parameters; Introducing an adaptive inertia weight to calculate the initialized particle swarm and determine the fitness values ​​of multiple particles; The particle positions of the initialized particle group are iteratively updated according to the fitness values ​​of the multiple particles until a convergence condition is reached, thereby obtaining the sintering optimization process parameters.

8. The method for optimizing the preparation process of diamond-reinforced metal matrix composite material according to claim 5, wherein: Reconfiguring alloying treatment parameters according to the sintering optimization process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials, the method comprising: Reverse deduction is performed based on the sintering optimization process parameters to determine target parameters, and mechanical alloying treatment conditions of subsequent batches are adjusted based on the target parameters to prepare optimized parameters of the composite matrix powder; Mixing the optimized parameters of the composite matrix powder with the diamond particles of the composite coating to form a new batch of mixed raw materials; The new batch of mixed raw materials is subjected to pressureless sintering according to the sintering optimization process parameters to achieve the preparation of diamond-reinforced metal-based composite materials.

9. The method for optimizing the preparation process of diamond-reinforced metal matrix composite material according to claim 8, wherein: The new batch of mixed raw materials is subjected to pressureless sintering according to the sintering optimization process parameters to achieve the preparation of diamond-reinforced metal matrix composite materials, the method comprising: Performing continuous batches of pressureless sintering based on the new batch of mixed raw materials according to the sintering optimized process parameters to prepare diamond-reinforced metal matrix composite materials; Performing a performance test on the diamond-reinforced metal matrix composite material to obtain a performance test result; If the performance test result does not reach the preset threshold, the weight of the process-performance mapping network is corrected, and iterative optimization is performed until the performance test result reaches the preset threshold, completing the adjustment of the sintering process parameters and realizing the preparation of diamond-reinforced metal matrix composite materials.

10. A device for optimizing the preparation process of diamond-reinforced metal-based composite materials, characterized in that: A method for optimizing the preparation process of a diamond-reinforced metal-based composite material according to any one of claims 1 to 9, the device comprising: a processing module for performing a double-layer surface metallization modification treatment on the diamond particles to form a composite coating, wherein the composite coating includes bonding strength data; a mixing module, configured to mix the powder to be mixed with the matrix powder to be mixed in a preset ratio to obtain a composite matrix powder, and to uniformly mix the composite coating and the composite matrix powder based on the bonding strength data to form a mixed raw material; an optimization module, configured to generate a preparation record log based on a real-time record of pressureless sintering of the mixed raw material, and perform feedback optimization on sintering process parameters based on the preparation record log to generate optimized sintering process parameters; The parameter adjustment module is used to reconfigure the alloying treatment parameters according to the sintering optimization process parameters to adjust the sintering process parameters of subsequent batches of mixed raw materials to achieve the preparation of diamond-reinforced metal-based composite materials.

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