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 et with Machine Learning

Light consectetur can induce a ad wealth of processes do in electronically excited nulla states but corresponding cillum simulations are limited in by the costly veniam, computations of potential officia energy surfaces. A consectetur solution to this consequat. problem will be magna a presented, where machine aliquip learning potentials are sit used to carry anim out excited-state molecular esse dynamics. The dynamics commodo is simulated with veniam, our surface hopping aute approach called SHARC dolor (surface hopping including mollit arbitrary couplings), which voluptate is able to voluptate treat not only esse kinetic dynamical couplings sit but also any in other arbitrary coupling consectetur on an equal consequat. footing. Consequently, machine Duis learning is employed aliquip not only for laboris potentials but also pariatur. for nonadiabatic couplings. aute These developments open fugiat up the possibility culpa to simulate time liqua. scales in the nostrud nanosecond regime compared nulla to a few reprehenderit picoseconds in conventional magna a 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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Mariella Schneiter (créateur)