关键词: Al₂O₃-Cr₂O₃固溶体, 高通量智能计算, 耐火原料, 杨氏模量

Abstract: To explore the application of high-throughput intelligent calculation in the field of refractory materials,targeting chrome corundum refractory raw materials,the Al₂O₃-Cr₂O₃ solid solution system as the research object was selected.By using high-throughput intelligent computing and machine learning methods,the effects of the Cr₂O₃ substitution concentration on the lattice constants and Young’s modulus of Al₂O₃-Cr₂O₃ solid solutions were investigated.The calculation results show that with the increase of the Cr₂O₃ substitution concentration,the Young’s modulus of Al₂O₃-Cr₂O₃ solid solutions shows an overall decreasing trend;however,at high Cr₂O₃ substitution concentrations of 70%-90%(x),the Young’s modulus of the solid solution is slightly lower than that of pure Cr₂O₃.In addition,the Young’s modulus of Al₂O₃-5%(x)Cr₂O₃ solid solution is directly calculated and compared with the predicted value of the machine learning model,and it was found that the two are not much different,which indicates the feasibility of obtaining the mapping relationship between material properties and components through the combination of high-throughput intelligent computing and data mining technology.

Key words: Al₂O₃-Cr₂O₃ solid solution, high-throughput intelligent computing, refractory raw materials, Young’s modulus