High cost of raw materials and the insufficient research on alloy systems severely constrained the development of Cu-Be alloys.The complex coupling relationship between composition and preparation process poses challe...High cost of raw materials and the insufficient research on alloy systems severely constrained the development of Cu-Be alloys.The complex coupling relationship between composition and preparation process poses challenges to the use of machine learning methods for the precise design of Cu-Be alloy.This study develops a novel method for integrated design of copper alloy composition and processing based on a Long Short-Term Memory model followed by an Encoder model(LSTM-Encoder)and enriches the framework by integrating phase diagram information.This approach not only capitalizes on the patterns of microstructural evolution during heat treatment as indicated in phase diagrams to reveal their intrinsic links with alloy performance but also eliminates cross-interference within sample data,thus significantly enhancing the model's generalization and predictive accuracy,which achieves high efficient and precise design of low-cost(low Be content) and high-performance Cu-Be alloys.Compared with other models,the LSTM-Encoder model incorporating phase diagram information(LSTM-Encoder-Ⅱ) showed significant superiority in prediction accuracy.After two rounds of experimental verification and iteration,the LSTM-Encoder-Ⅱ model attained prediction accuracies of 96% for hardness and 93% for electrical conductivity.Various Cu-Be-X alloys with excellent comprehensive performance and low cost have been designed,and Cu-1.5Be-0.1Ni-0.3Co alloy achieves a tensile strength of 1211 MPa and an electrical conductivity of 30.3% IACS,and Cu-1.5Be-0.6Ni alloy attains a tensile strength of1290 MPa and an electrical conductivity of 29.3% IACS,both of which are comparable to the C17200 alloy,with raw material cost reduced by more than 14%.展开更多
The influence of Al addition on the microstructure of Cu-B alloys and Cu-ZrB2 composites was investigated using scanning electron microscopy, X-ray diffraction and first-principles calculation. The results show that t...The influence of Al addition on the microstructure of Cu-B alloys and Cu-ZrB2 composites was investigated using scanning electron microscopy, X-ray diffraction and first-principles calculation. The results show that the eutectic B in Cu-B alloys can be modified by Al from coarse needles to fine fibrous structure and primary B will form in hypoeutectic Cu-B alloys. As for Cu-ZrB2 composites, Al can significantly refine and modify the morphology of ZrB2 as well as improve its distribution, which should be due to its selective adsorption on ZrB2 surfaces. The first-principles calculation results indicate that Al is preferentially adsobed on ZrB2■, then on ZrB2■, and finally on ZrB2(0001). As a result, smaller sized ZrB2 with a polyhedron-like, even nearly sphere-like morphology, can form. Due to Al addition, the hardness of Cu-ZrB2 composites is greatly enhanced, but the electrical conductivity of the composites is seriously reduced.展开更多
The influence of aging treatment on the microstructure,mechanical properties and electrical conductivity of Cu-0.5 wt pct Be alloy for connector material applications was investigated.The properties of mechanical stre...The influence of aging treatment on the microstructure,mechanical properties and electrical conductivity of Cu-0.5 wt pct Be alloy for connector material applications was investigated.The properties of mechanical strength and electrical conductivity increase with increasing aging temperature and time.Microstructure of the aged Cu-Be alloy revealed that grain size and fraction of low angle and high angle grain boundary were not greatly changed;however,transmission electron microscopy （TEM） analysis exhibited that beryllides precipitation （CoBe and NiBe） with a size of 50 nm were distributed in grains.It was,therefore concluded that these beryllide precipitates improved the mechanical strength and also it was favor in improvement of electrical conductivity.展开更多
基金financial supplies supported by the National Natural Science Foundation of China(Nos.52371038 and U2202255)the Science and Technology Innovation Program of Hunan Province(No.2023RC1019)
文摘High cost of raw materials and the insufficient research on alloy systems severely constrained the development of Cu-Be alloys.The complex coupling relationship between composition and preparation process poses challenges to the use of machine learning methods for the precise design of Cu-Be alloy.This study develops a novel method for integrated design of copper alloy composition and processing based on a Long Short-Term Memory model followed by an Encoder model(LSTM-Encoder)and enriches the framework by integrating phase diagram information.This approach not only capitalizes on the patterns of microstructural evolution during heat treatment as indicated in phase diagrams to reveal their intrinsic links with alloy performance but also eliminates cross-interference within sample data,thus significantly enhancing the model's generalization and predictive accuracy,which achieves high efficient and precise design of low-cost(low Be content) and high-performance Cu-Be alloys.Compared with other models,the LSTM-Encoder model incorporating phase diagram information(LSTM-Encoder-Ⅱ) showed significant superiority in prediction accuracy.After two rounds of experimental verification and iteration,the LSTM-Encoder-Ⅱ model attained prediction accuracies of 96% for hardness and 93% for electrical conductivity.Various Cu-Be-X alloys with excellent comprehensive performance and low cost have been designed,and Cu-1.5Be-0.1Ni-0.3Co alloy achieves a tensile strength of 1211 MPa and an electrical conductivity of 30.3% IACS,and Cu-1.5Be-0.6Ni alloy attains a tensile strength of1290 MPa and an electrical conductivity of 29.3% IACS,both of which are comparable to the C17200 alloy,with raw material cost reduced by more than 14%.
基金Project(51774212)supported by the National Natural Science Foundation of ChinaProjects(E2019502060,E2019502057)supported by the Natural Science Foundation of Hebei Province,China。
文摘The influence of Al addition on the microstructure of Cu-B alloys and Cu-ZrB2 composites was investigated using scanning electron microscopy, X-ray diffraction and first-principles calculation. The results show that the eutectic B in Cu-B alloys can be modified by Al from coarse needles to fine fibrous structure and primary B will form in hypoeutectic Cu-B alloys. As for Cu-ZrB2 composites, Al can significantly refine and modify the morphology of ZrB2 as well as improve its distribution, which should be due to its selective adsorption on ZrB2 surfaces. The first-principles calculation results indicate that Al is preferentially adsobed on ZrB2■, then on ZrB2■, and finally on ZrB2(0001). As a result, smaller sized ZrB2 with a polyhedron-like, even nearly sphere-like morphology, can form. Due to Al addition, the hardness of Cu-ZrB2 composites is greatly enhanced, but the electrical conductivity of the composites is seriously reduced.
文摘The influence of aging treatment on the microstructure,mechanical properties and electrical conductivity of Cu-0.5 wt pct Be alloy for connector material applications was investigated.The properties of mechanical strength and electrical conductivity increase with increasing aging temperature and time.Microstructure of the aged Cu-Be alloy revealed that grain size and fraction of low angle and high angle grain boundary were not greatly changed;however,transmission electron microscopy （TEM） analysis exhibited that beryllides precipitation （CoBe and NiBe） with a size of 50 nm were distributed in grains.It was,therefore concluded that these beryllide precipitates improved the mechanical strength and also it was favor in improvement of electrical conductivity.
