Montag, 24. April 2017, 16:00 - 18:00 iCal

Dr. Philipp Marquetand /

Universität Wien, Fakultät für Chemie, Institut für Theoretische Chemie
"Artificial Neural Networks and Dynamics in Excited States"

Joseph Loschmidt Hörsaal der Fakultät für Chemie
Währinger Straße 42, 1090 Wien


Artificial Neural Networks and Dynamics in Excited States


Arti?cial neural networks can learn the relationship between the nuclear geometry of a molecule and the corresponding potential energy. The neural networks then serve as a highly accurate and extremely fast tool for predicting potential energy surfaces. Different applications of such neural network potentials will be shown, e.g. the computation of an organic reaction or the calculation of infrared spectra. In the future, the technique will be extended to excited states.

Currently, we still use highly accurate but time-consuming ab initio calculations to provide potentials for excited-state dynamics simulations. In the latter, we study molecules by our so-called SHARC (surface hopping including arbitrary couplings) method. The method is applied to a variety of systems, showing e.g. that intersystem crossing can take place on a femtosecond timescale even in organic molecules with only relatively small spin-orbit couplings.


Fakultät für Chemie


Brigitte Schwarz
Fakultät für Chemie der Universität Wien