Cover of the Journal of Chemical Theory and Computation
© 2019 EPFL
The work of Amber Mace and Senja Barthel is on the cover of the Journal of Chemical Theory and Computation
Amber Mace et al. present TuTraSt, a novel algorithm to predict self-diffusion of a mobile guest particle in a crystalline material. It detects the energies at which diffusion paths are formed, allowing for easy identification of diffusive systems, and furthermore partitions the potential energy field into energy basins and transitions states. This TUnnel and TRAnsition STate search algorithm permits a transition state theory based analysis for fast prediction of the diffusion coefficients with an automated multiscale modeling approach. (figure by Amber Mace)
The research of S.B. and B.S. was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 666983, MaGic). Part of the research was supported by the NCCR MARVEL, funded by the Swiss National Science Foundation. A.M. thanks the Swedish Science Council (VR) for financing (project number 2015-06320). The calculations were enabled by the Swiss National Supercomputing Centre (CSCS), under project ID s761. We acknowledge PRACE for awarding access to SuperMUC at GCS@LRZ, Germany.
A. K. Mace, S. D. Barthel, and B. Smit, An automated multi-scale approach to predict self-diffusion from a potential energy field J. Chem. Theory Comput. 15, 2127−2141 (2019) DOI: 10.1021/acs.jctc.8b01255