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

Back to Events

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

Excited-state Dynamics Simulations dolor with Machine Learning

Light cupidatat can induce a sunt wealth of processes culpa in electronically excited officia states but corresponding sit simulations are limited liqua. by the costly occaecat computations of potential ullamco energy surfaces. A cupidatat solution to this incididunt problem will be Excepteur presented, where machine minim learning potentials are eiusmod used to carry reprehenderit out excited-state molecular incididunt dynamics. The dynamics dolore is simulated with our surface hopping incididunt approach called SHARC minim (surface hopping including in arbitrary couplings), which ad is able to qui treat not only veniam, kinetic dynamical couplings nulla but also any sit other arbitrary coupling adipisicing on an equal do footing. Consequently, machine et learning is employed aliquip not only for dolore potentials but also cupidatat for nonadiabatic couplings. dolore These developments open Duis up the possibility esse to simulate time do scales in the in nanosecond regime compared mollit to a few deserunt picoseconds in conventional est 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
This event is public. Anyone can attend and invite others to attend.
Mariella Schneiter (creator)