21 citations · 65 across the 10 of their papers we have counts for
Showing 2021 · cond-mat.mtrl-sciShow all
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cond-mat.mtrl-sci2021★ 10 cited
Inorganic Synthesis Reaction Condition Prediction with Generative Machine Learning
Christopher Karpovich, Zach Jensen, Vineeth Venugopal +1
Data-driven synthesis planning with machine learning is a key step in the design and discovery of novel inorganic compounds with desirable properties. Inorganic materials synthesis…
cond-mat.mtrl-sci2021
Development of structural descriptors to predict dissolution rate of volcanic glasses: molecular dynamic simulations
Kai Gong, Elsa Olivetti
Establishing the composition-structure-property relationships for amorphous materials is critical for many important natural and engineering processes, including the dissolution of…
cond-mat.mtrl-sci2021
Learning the Crystal Structure Genome for Property Classification
Yiqun Wang, Xiao-Jie Zhang, Fei Xia +3
Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structu…