Suivre
Fabian Thiemann
Fabian Thiemann
IBM Research
Adresse e-mail validée de ibm.com - Page d'accueil
Titre
Citée par
Citée par
Année
Machine learning potentials for complex aqueous systems made simple
C Schran, FL Thiemann, P Rowe, EA Müller, O Marsalek, A Michaelides
Proceedings of the National Academy of Sciences 118 (38), e2110077118, 2021
1672021
Water flow in single-wall nanotubes: Oxygen makes it slip, hydrogen makes it stick
FL Thiemann, C Schran, P Rowe, EA Müller, A Michaelides
ACS nano 16 (7), 10775-10782, 2022
582022
Machine learning potential for hexagonal boron nitride applied to thermally and mechanically induced rippling
FL Thiemann, P Rowe, EA Müller, A Michaelides
The Journal of Physical Chemistry C 124 (40), 22278-22290, 2020
502020
Defect-dependent corrugation in graphene
FL Thiemann, P Rowe, A Zen, EA Muller, A Michaelides
Nano Letters 21 (19), 8143-8150, 2021
362021
Classical quantum friction at water–carbon interfaces
AT Bui, FL Thiemann, A Michaelides, SJ Cox
Nano Letters 23 (2), 580-587, 2023
302023
Introduction to machine learning potentials for atomistic simulations
FL Thiemann, N O’neill, V Kapil, A Michaelides, C Schran
Journal of Physics: Condensed Matter 37 (7), 073002, 2024
12024
Defects induce phase transition from dynamic to static rippling in graphene
FL Thiemann, C Scalliet, EA Müller, A Michaelides
arXiv preprint arXiv:2406.04775, 2024
12024
On the increase of the melting temperature of water confined in one-dimensional nano-cavities
F Della Pia, A Zen, V Kapil, FL Thiemann, D Alfè, A Michaelides
The Journal of Chemical Physics 161 (22), 2024
2024
Properties of low-dimensional materials explored with machine learning potentials
FL Thiemann
UCL (University College London), 2022
2022
Gaussian Approximation Potential for Hexagonal Boron Nitride (hBN-GAP)
FL Thiemann, P Rowe, EA Müller, A Michaelides
2021
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–10