Tailoring material properties often requires understanding the solidification process.Herein,we introduce the geometric descriptor Soliquidy,which numerically captures the Euclidean transport cost between the translat...Tailoring material properties often requires understanding the solidification process.Herein,we introduce the geometric descriptor Soliquidy,which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials.As a testbed,we apply Soliquidy to the classification of glass-forming metal alloys.By extending and combining an experimental library of metallic thin films(glass/no-glass)with the aflow.org computational database(geometrical and energetic information of mixtures)we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation.Such a classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.展开更多
基金supported by the Office of Naval Research under grants N00014-20-1-2200 and N00014-20-1-2225supported by high-performance computer time and resources from the DoD High-Performance Computing Modernization Program(Frontier).We acknowledge Auro Scientific,LLC for computational support.
文摘Tailoring material properties often requires understanding the solidification process.Herein,we introduce the geometric descriptor Soliquidy,which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials.As a testbed,we apply Soliquidy to the classification of glass-forming metal alloys.By extending and combining an experimental library of metallic thin films(glass/no-glass)with the aflow.org computational database(geometrical and energetic information of mixtures)we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation.Such a classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.
