Lars Schaaf

Publications

17O NMR spectroscopy reveals CO2 speciation and dynamics in hydroxide-based carbon capture materials.

B Rhodes, L Schaaf, M Zick, S Pugh, J Hilliard, S Sharma, C Wade, G Csanyi, P Milner, A Forse

(2024)

(doi: 10.26434/chemrxiv-2024-c0vmg)

A foundation model for atomistic materials chemistry

I Batatia, P Benner, Y Chiang, AM Elena, DP Kovács, J Riebesell, XR Advincula, M Asta, M Avaylon, WJ Baldwin, F Berger, N Bernstein, A Bhowmik, SM Blau, V Cărare, JP Darby, S De, FD Pia, VL Deringer, R Elijošius, Z El-Machachi, F Falcioni, E Fako, AC Ferrari, A Genreith-Schriever, J George, REA Goodall, CP Grey, P Grigorev, S Han, W Handley, HH Heenen, K Hermansson, C Holm, J Jaafar, S Hofmann, KS Jakob, H Jung, V Kapil, AD Kaplan, N Karimitari, JR Kermode, N Kroupa, J Kullgren, MC Kuner, D Kuryla, G Liepuoniute, JT Margraf, I-B Magdău, A Michaelides, JH Moore, AA Naik, SP Niblett, SW Norwood, N O'Neill, C Ortner, KA Persson, K Reuter, AS Rosen, LL Schaaf, C Schran, BX Shi, E Sivonxay, TK Stenczel, V Svahn, C Sutton, TD Swinburne, J Tilly, CVD Oord, E Varga-Umbrich, T Vegge, M Vondrák, Y Wang, WC Witt, F Zills, G Csányi

(2023)

(link to publication)

Equivariant Matrix Function Neural Networks

I Batatia, LL Schaaf, H Chen, G Csányi, C Ortner, FA Faber

(2023)

(doi: 10.48550/arxiv.2310.10434)

(link to publication)

Accurate energy barriers for catalytic reaction pathways: an automatic training protocol for machine learning force fields

LL Schaaf, E Fako, S De, A Schäfer, G Csányi

– npj Computational Materials

(2023)

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