most citedMachine Learning Prediction of Critical Cooling Rate for Metallic Glasses From Expanded Datasets and Elemental Features

24 citations · 24 across the 1 of their papers we have counts for

collaborators

1 paper

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…