Laboratory for Materials Simulations (LMS)

LMS banner by Leonid Kahle and Nicola Marzari — ©Leonid Kahle and Nicola Marzari

The Laboratory for Materials Simulations develops the theory, algorithms, software and data required for the study of advanced materials at PSI.

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Lab News & Scientific Highlights

25.06.2024

•Future Technologies

International collaboration lays the foundation for future AI for materials via the OPTIMADE standard

Materials research

Data Science

Artificial intelligence (AI) is accelerating the development of new materials. A prerequisite for AI in materials research is large-scale use and exchange of data on materials, which is facilitated by a broad international standard. A major international collaboration including researchers from the LMS laboratory now presents an extended version of the OPTIMADE standard.

04.04.2024

•Technologies d’avenir

•16 min

Un raccourci possible

Data Science

L’apprentissage machine et l’intelligence artificielle font désormais partie des outils de la plupart des scientifiques du PSI. Ces méthodes modifient parfois en profondeur la science.

26.01.2024

"Magnetostriction-Driven Muon Localization in an Antiferromagnetic Oxide" published in Phys. Rev. Lett.

A study involving PSI scientists from the LMS lab, and just published in Physical Review Letters has found that in manganese oxide, a textbook antiferromagnetic material, the site of an implanted spin-polarized muon is not well identified, but can change due to a previously neglected effect: magnetostriction.

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Publications

Burgess AC, Linscott E, O'Regan DD
Tilted-plane structure of the energy of finite quantum systems
Physical Review Letters. 2024; 133(2): 026404 (6 pp.). https://doi.org/10.1103/PhysRevLett.133.026404
DORA PSI
Ponet L, Di Lucente E, Marzari N
The energy landscape of magnetic materials
npj Computational Materials. 2024; 10(1): 151 (7 pp.). https://doi.org/10.1038/s41524-024-01310-w
DORA PSI
Evans ML, Bergsma J, Merkys A, Andersen CW, Andersson OB, Beltrán D, et al.
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Digital Discovery. 2024. https://doi.org/10.1039/d4dd00039k
DORA PSI
Beaulieu S, Dong S, Christiansson V, Werner P, Pincelli T, Ziegler JD, et al.
Berry curvature signatures in chiroptical excitonic transitions
Science Advances. 2024; 10(26): eadk3897 (9 pp.). https://doi.org/10.1126/sciadv.adk3897
DORA PSI
Rivano N, Marzari N, Sohier T
Density functional perturbation theory for one-dimensional systems: Implementation and relevance for phonons and electron-phonon interactions
Physical Review B. 2024; 109(24): 245426 (13 pp.). https://doi.org/10.1103/PhysRevB.109.245426
DORA PSI