Dr. Philipp Marquetand, University of Vienna, Institute of Theoretical Chemistry, Vienna, Austria 2019-05-22 16:30:00

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Start:Wednesday, 22 May 2019Time:16:30
End:Wednesday, 22 May 2019Time:18:00
Category: Uni Basel, Physikalische Chemie

Excited-state Dynamics Simulations cupidatat with Machine Learning

Light in can induce a pariatur. wealth of processes qui in electronically excited irure states but corresponding sit simulations are limited laborum. by the costly culpa computations of potential eu energy surfaces. A tempor solution to this nulla problem will be mollit presented, where machine culpa learning potentials are tempor used to carry ut out excited-state molecular laborum. dynamics. The dynamics is simulated with in our surface hopping nulla approach called SHARC nisi (surface hopping including voluptate arbitrary couplings), which eiusmod is able to et treat not only adipisicing kinetic dynamical couplings commodo but also any laborum. other arbitrary coupling est on an equal enim footing. Consequently, machine enim learning is employed qui not only for officia potentials but also adipisicing for nonadiabatic couplings. ex These developments open voluptate up the possibility laborum. to simulate time Lorem scales in the dolore nanosecond regime compared id to a few qui picoseconds in conventional nostrud approaches.

Venue: Physikalische Chemie, Departement Chemie, Universität Basel, Kleiner Hörsaal, Raum 4.04, 2. Stock
Klingelbergstrasse 80, 4056, Basel
Email: Send
Website: http://www.chemie.unibas.ch
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Mariella Schneiter (creator)