| 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 | 126 | 2021 |
| 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 | 42 | 2022 |
| 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 | 41 | 2020 |
| Defect-dependent corrugation in graphene FL Thiemann, P Rowe, A Zen, EA Muller, A Michaelides Nano Letters 21 (19), 8143-8150, 2021 | 30 | 2021 |
| Classical quantum friction at water–carbon interfaces AT Bui, FL Thiemann, A Michaelides, SJ Cox Nano Letters 23 (2), 580-587, 2023 | 21 | 2023 |
| 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 arXiv preprint arXiv:2406.18448, 2024 | | 2024 |
| 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 | | 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 |
Angelos MichaelidesUniversity of Cambridge在 cam.ac.uk 的电子邮件经过验证
