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

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Date :
Début :Mercredi, 22 Mai 2019Heure :16:30
Fin :Mercredi, 22 Mai 2019Heure :18:00
Catégorie : Uni Basel, Physikalische Chemie
Description :

Excited-state Dynamics Simulations ad with Machine Learning

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

Lieu : Physikalische Chemie, Departement Chemie, Universität Basel, Kleiner Hörsaal, Raum 4.04, 2. Stock
Klingelbergstrasse 80, 4056, Basel
Pays :Switzerland
Adresse mail : Expédier
Site Web : http://www.chemie.unibas.ch
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