Patrick Rowe
Title
Cited by
Cited by
Year
Development of a machine learning potential for graphene
P Rowe, G Csányi, D Alfe, A Michaelides
Physical Review B 97 (5), 054303, 2018
962018
An accurate and transferable machine learning potential for carbon
P Rowe, VL Deringer, P Gasparotto, G Csányi, A Michaelides
The Journal of Chemical Physics 153 (3), 034702, 2020
292020
Importance and nature of short-range excitonic interactions in light harvesting complexes and organic semiconductors
RP Fornari, P Rowe, D Padula, A Troisi
Journal of chemical theory and computation 13 (8), 3754-3763, 2017
182017
Structure-Dynamics Relation in Physically-Plausible MultiChromophore Systems
AD George C. Knee, Patrick Rowe, Luke D. Smith, Alessandro Troisi
Journal of Physical Chemistry Letters 8, 2328, 2017
162017
Cation-controlled wetting properties of vermiculite membranes and its promise for fouling resistant oil–water separation
K Huang, P Rowe, C Chi, V Sreepal, T Bohn, KG Zhou, Y Su, E Prestat, ...
Nature communications 11 (1), 1-10, 2020
132020
Machine Learning Potential for Hexagonal Boron Nitride Applied to Thermally and Mechanically Induced Rippling
FL Thiemann, P Rowe, EA Muller, A Michaelides
The Journal of Physical Chemistry C, 2020
32020
Cation controlled wetting properties of vermiculite membranes and its potential for fouling resistant oil-water separation
K Huang, P Rowe, C Chi, V Sreepal, T Bohn, KG Zhou, Y Su, E Prestat, ...
arXiv preprint arXiv:2002.04522, 2020
2020
Correction to “Structure-Dynamics Relation in Physically-Plausible Multi-Chromophore Systems”
GC Knee, P Rowe, LD Smith, A Troisi, A Datta
The journal of physical chemistry letters 8 (14), 3178-3178, 2017
2017
Making sense of charge and exciton dynamics in organic materials via model reduction
A Troisi, D Padula, K Claridge, M Lee, R Fornari, P Rowe
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Articles 1–9