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 fugiat with Machine Learning

Light voluptate can induce a aliquip wealth of processes ex in electronically excited mollit states but corresponding in simulations are limited nisi by the costly ut computations of potential est energy surfaces. A reprehenderit solution to this laborum. problem will be qui presented, where machine liqua. learning potentials are mollit used to carry est out excited-state molecular proident, dynamics. The dynamics sit is simulated with tempor our surface hopping do approach called SHARC Duis (surface hopping including culpa arbitrary couplings), which reprehenderit is able to sed treat not only in kinetic dynamical couplings adipisicing but also any consectetur other arbitrary coupling deserunt on an equal in footing. Consequently, machine Excepteur learning is employed veniam, not only for irure potentials but also ex for nonadiabatic couplings. id These developments open Lorem up the possibility mollit to simulate time qui scales in the culpa nanosecond regime compared veniam, to a few ad picoseconds in conventional proident, 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
Event Type
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Mariella Schneiter (creator)