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作 者:Nutth Tuchinda Christopher A.Schuh
机构地区:[1]Department of Materials Science and Engineering,Massachusetts Institute of Technology,77 Massachusetts Avenue,Cambridge,MA02139,USA [2]Department of Materials Science and Engineering,Northwestern University,2145 Sheridan Road,Evanston,IL 60208,USA
出 处:《npj Computational Materials》2024年第1期2487-2496,共10页计算材料学(英文)
基 金:supported by the US Department of Energy award No.DE-SC0020180;supported by the U.S.National Science Foundation under Grant No.DMR 2002860.
摘 要:Grain boundary solute segregation influencesmost bulk material properties,and understanding solute thermodynamics at grain boundaries is critical for engineering them.However,the vast grain boundary space in polycrystals is challenging to evaluate due to its size,especially for the intrinsically hard-tocompute segregation excess entropy.Here data science methods are used to generate a database of site-wise grain boundary segregation entropy spectra for 155 dilute binary alloys within the harmonic approximation.The spectral framework allows scale bridging between the calculated atomistic sitewise energy-entropy spectra and macroscopic segregation entropy estimates.The results affirm that macroscopic averaging is not sufficient:a spectral treatment of grain boundary segregation is needed to accurately model bulk temperature dependence of grain boundary solute segregation.The calculated spectral entropy database and thermodynamic framework can be applied for both understanding segregation experiments and alloy design exercises,paving the way to a finitetemperature grain boundary genome.
分 类 号:TG1[金属学及工艺—金属学]
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