Computational materials science, 0927-0256
Journal
| ISSNs | 0927-0256 |
|---|
41 - 42 out of 42Page size: 10
Research output
- 2024
- Published
Descriptors based on the density of states for efficient machine learning of grain-boundary segregation energies
Dösinger, C. A., Hammerschmidt, T., Peil, O. E., Scheiber, D. & Romaner, L., 13 Nov 2024, In: Computational materials science. 247.2025, 31 January 2025, 10 p., 113493.Research output: Contribution to journal › Article › Research › peer-review
- 2025
- Published
Accurate prediction of structural and mechanical properties on amorphous materials enabled through machine-learning potentials: A case study of silicon nitride
Nayak, G. K., Srinivasan, P., Todt, J., Daniel, R., Nicolini, P. & Holec, D., 6 Jan 2025, In: Computational materials science. 249.2025, 5 February, 11 p., 113629.Research output: Contribution to journal › Article › Research › peer-review
