Study On Optimization Of Technological Parameters For Multi-wire Cutting Of Bismuth Telluride-based Thermoelectric Materials

Bismuth telluride(Bi₂Te₃)-based alloy has the best thermoelectric conversion near room temperature in currently,and is widely used in the fields of thermoelectric refrigeration and waste heat power generation.In the preparation of thermoelectric devices of this material,the shape accuracy of the bismuth telluride-based crystal grains is the most important factor affecting the stability of its quality and size.Therefore,as an important process of using bismuth telluride-based crystal rods to prepare thermoelectric devices,the control and optimization of process parameters when cutting the bismuth telluride-based crystal rods into regular grains is very important.In this process,the bismuth telluride crystal rod must first be cut into wafers,and then cut into crystal grains.The upper and lower surfaces of the wafer are the upper and lower surfaces of the crystal grains.The crystal grains are in contact with the copper sheet through the upper and lower surfaces.The fitting degree,that is the degree of warp of the wafer,is an important factor affecting the quality of thermoelectric devices.In this paper,through in-depth analysis of the multi-wire cutting process of Bi₂Te₃based thermoelectric materials,combining with ABAQUS numerical analysis and experimental research,the non-dominant sorting genetic algorithm(NSGA-?)was used to optimize the main process parameters,and the combination of processing parameters with the greatest cutting efficiency under the condition of meeting the requirements of warp was obtained.The main research contents were as follows:(1)Based on the secondary development of ABAQUS,this paper established a sequential coupled thermal stress-strain analysis finite element model,calculated the heat flux during the cutting process,determined the heat dissipation conditions on the surface of the ingot and the slit,and used the life and death element method to simulate ingot cutting process;then simulated and analyzed the influence of ingot diameter,feed speed,wire saw speed,wafer thickness,tension force on wafer temperature field distribution and warp deformation by changing the numerical value of the processing parameters.Finally,a cutting test was performed on the ingot,and the test results were compared with the simulation results to verify the reliability of the model.These laid the foundation for the analysis of warp and cutting efficiency.(2)The second-order response mathematical models between warp,cutting efficiency and related processing parameters were established by response surface method(RSM),and the combination was used as the objective function of the fast non-dominant sorting genetic algorithm,and the reliability of the mathematical model was verified by the analysis of variance method.(3)The fast non-dominated sorting genetic algorithm was used to simulate and optimize the mathematical model,and a set of non-dominated frontier solutions were obtained.The ingot cutting test was performed using the parameters in the front solutions.The simulation results and test results were compared to verify the feasibility of the algorithm.Compared with before optimization,the optimized processing parameters could reduce the warp value by 3.70%and increase the cutting efficiency by 9.68%.