24 citations · 28 across the 3 of their papers we have counts for
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cond-mat.mtrl-sci2023★ 24 cited
Machine Learning Prediction of Critical Cooling Rate for Metallic Glasses From Expanded Datasets and Elemental Features
Benjamin T. Afflerbach, Carter Francis, Lane E. Schultz +9
We use a random forest model to predict the critical cooling rate (RC) for glass formation of various alloys from features of their constituent elements. The random forest model wa…
cond-mat.mtrl-sci2023
Origin of ultra-low thermal conductivity in unconventional clathrates: Strong scattering from extremely low-frequency rattling modes
Kamil M. Ciesielski, Brenden R. Ortiz, Lidia C. Gomes +6
Recent discoveries of materials with ultra-low thermal conductivity open a pathway to significant developments in the field of thermoelectricity. Here, we conduct a comparative stu…