Jun Ding

Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning

A. Shapeev, Qi Wang, Jun Ding, 2020, npj Computational Materials.

Ab initio modeling of the energy landscape for screw dislocations in body-centered cubic high-entropy alloys

R. Ritchie, Jun Ding, M. Asta, 2019, npj Computational Materials.

Ab initio modeling of the role of local chemical short-range order on the Peierls potential of screw dislocations in body-centered cubic high-entropy alloys

R. Ritchie, Jun Ding, M. Asta, 2019, 1912.10506.

Computational modeling sheds light on structural evolution in metallic glasses and supercooled liquids

Jun Ding, E. Ma, J. Ding, 2017, npj Computational Materials.

One-dimensional stringlike cooperative migration of lithium ions in an ultrafast ionic conductor

Ming Xu, Evan Ma, Jun Ding, 2012 .