The discovery of new materials is one of the driving forces to promote the development of modern society and technology innovation,the traditional materials research mainly depended on the trial-and-error method,which...The discovery of new materials is one of the driving forces to promote the development of modern society and technology innovation,the traditional materials research mainly depended on the trial-and-error method,which is time-consuming and laborious.Recently,machine learning(ML)methods have made great progress in the researches of materials science with the arrival of the big-data era,which gives a deep revolution in human society and advance science greatly.However,there exist few systematic generalization and summaries about the applications of ML methods in materials science.In this review,we first provide a brief account of the progress of researches on materials science with ML employed,the main ideas and basic procedures of this method are emphatically introduced.Then the algorithms of ML which were frequently used in the researches of materials science are classified and compared.Finally,the recent meaningful applications of ML in metal materials,battery materials,photovoltaic materials and metallic glass are reviewed.展开更多
The criteria of process parameters(μ≤4),atomic size difference(ε≤5.8,δ≤11 andα≤2),thermodynamic(-14.5≤△Hmix≤6.5 andΩ≥1.8)in the prediction of the phase stability for laser-clad high-entropy alloy coatings...The criteria of process parameters(μ≤4),atomic size difference(ε≤5.8,δ≤11 andα≤2),thermodynamic(-14.5≤△Hmix≤6.5 andΩ≥1.8)in the prediction of the phase stability for laser-clad high-entropy alloy coatings are studied in detail.Besides,the criteria of valence electron concentration(VEC)applied to distinguish the stability of different solid solution phases are as follows:VEC<7.65 for simple BCC,VEC≥7.65 for simple face-centered cubic(FCC),7.14<VEC<7.78 for dual-phase BCC and FCC.Among them,μandεproposed firstly separate the phase stability of laserclad high-entropy alloy coatings quite precisely.The other modified criteria(δ,α,△Hmix,Ω,VEC)are proved to be different from those of the high-entropy alloys synthesized by the traditional casting and smelting processes.展开更多
基金This work was financially supported by the National Natural Science Foundation of China(No.51627802)。
文摘The discovery of new materials is one of the driving forces to promote the development of modern society and technology innovation,the traditional materials research mainly depended on the trial-and-error method,which is time-consuming and laborious.Recently,machine learning(ML)methods have made great progress in the researches of materials science with the arrival of the big-data era,which gives a deep revolution in human society and advance science greatly.However,there exist few systematic generalization and summaries about the applications of ML methods in materials science.In this review,we first provide a brief account of the progress of researches on materials science with ML employed,the main ideas and basic procedures of this method are emphatically introduced.Then the algorithms of ML which were frequently used in the researches of materials science are classified and compared.Finally,the recent meaningful applications of ML in metal materials,battery materials,photovoltaic materials and metallic glass are reviewed.
基金the National Natural Science Foundation of China (No. 51627802)。
文摘The criteria of process parameters(μ≤4),atomic size difference(ε≤5.8,δ≤11 andα≤2),thermodynamic(-14.5≤△Hmix≤6.5 andΩ≥1.8)in the prediction of the phase stability for laser-clad high-entropy alloy coatings are studied in detail.Besides,the criteria of valence electron concentration(VEC)applied to distinguish the stability of different solid solution phases are as follows:VEC<7.65 for simple BCC,VEC≥7.65 for simple face-centered cubic(FCC),7.14<VEC<7.78 for dual-phase BCC and FCC.Among them,μandεproposed firstly separate the phase stability of laserclad high-entropy alloy coatings quite precisely.The other modified criteria(δ,α,△Hmix,Ω,VEC)are proved to be different from those of the high-entropy alloys synthesized by the traditional casting and smelting processes.
