Jochen Rohrer

Modelling atomic and nanoscale structure in the silicon–oxygen system through active machine learning

Volker L. Deringer, K. Albe, Linus C. Erhard, 2023, Nature communications.

Understanding phase transitions of $\alpha$-quartz under dynamic compression conditions by machine-learning driven atomistic simulations

C. Prescher, Linus C. Erhard, C. Otzen, 2024, 2406.17676.

From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows

M. Mrovec, Sarath Menon, Minaam Qamar, 2024, npj Computational Materials.

From electrons to phase diagrams with classical and machine learning potentials: automated workflows for materials science with pyiron

R. Drautz, M. Mrovec, K. Albe, 2024, 2403.05724.

General purpose potential for glassy and crystalline phases of Cu-Zr alloys based on the ACE formalism

Jochen Rohrer, Karsten Albe, Niklas Leimeroth, 2024, Physical Review Materials.