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 est with Machine Learning

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