Ben Afflerbach

Machine learning predictions of irradiation embrittlement in reactor pressure vessel steels

Henry H. Wu, D. Morgan, P. Wells, 2022, npj Computational Materials.

Exploration of characteristic temperature contributions to metallic glass forming ability

Paul M. Voyles, Dane Morgan, Izabela Szlufarska, 2021, 2107.14157.

Error assessment and optimal cross-validation approaches in machine learning applied to impurity diffusion

Dane Morgan, Ben Afflerbach, Ryan Jacobs, 2019, Computational Materials Science.

The Materials Simulation Toolkit for Machine learning (MAST-ML): An automated open source toolkit to accelerate data-driven materials research

Ryan Jacobs, Tam Mayeshiba, Dane Morgan, 2019, Computational Materials Science.

Molecular dynamic characteristic temperatures for predicting metallic glass forming ability

D. Morgan, I. Szlufarska, Ben Afflerbach, 2021, Computational Materials Science.

Exploring effective charge in electromigration using machine learning

D. Morgan, R. Jacobs, S. Lin, 2019, MRS Communications.

Machine Learning Prediction of the Critical Cooling Rate for Metallic Glasses from Expanded Datasets and Elemental Features

Logan T. Ward, D. Morgan, I. Szlufarska, 2022, Chemistry of Materials.

Molecular simulation-derived features for machine learning predictions of metal glass forming ability

D. Morgan, I. Szlufarska, P. Voyles, 2021, 2108.08766.