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SUMMARY:Machine learning potentials and excited-state molecular dynamics
DTSTART:20170210T100000
DTEND:20170210T110000
DTSTAMP:20260407T043455Z
UID:c5e90b5deb3840ebcc25ccba69ff43acbd1e5475c58b92bd549b35bf
CATEGORIES:Conferences - Seminars
DESCRIPTION:Philipp Marquetand\nUniversity of Vienna\, Institute of Theore
 tical Chemistry\, Währinger Str. 17\, 1090 Vienna\, Austria.\nphilipp.mar
 quetand@univie.ac.at\nArtificial neural networks can learn the relationshi
 p between the nuclear geometry of a molecule and the corresponding potenti
 al energy and\, in this way\, serve as a highly accurate and extremely fas
 t tool for predicting potential energy surfaces [1]. As an application\, t
 he simulation of an organic reaction with such a machine learning algorith
 m is presented [2]. Furthermore\, with the right neural network setup\, th
 e chemical locality is inherently exploited\, where the local region of a 
 large molecule is only weakly influenced by the atoms that are far from th
 e region of interest [3]. As a result\, a vast amount of computational tim
 e can be saved when generating the so-called reference data from which the
  neural network learns the shape of the potential energy surfaces. Such im
 provements will enable us to perform on-the-fly dynamics calculations of l
 arge systems and long time scales in the future.\nCurrently\, we still use
  highly accurate but time-consuming ab initio calculations in semiclassica
 l molecular dynamics. Here\, we study molecules in their excited electroni
 c states by the surface hopping method\, where the nuclei move classically
  on potentials computed by quantum mechanics. We have modified the surface
  hopping approach to incorporate not only kinetic dynamical couplings but 
 also any other arbitrary coupling in our so-called SHARC (surface hopping 
 including arbitrary couplings) method [4\, 5]. The corresponding code is a
 lso publicly available [6]. Especially spin-orbit couplings can now be tre
 ated in on-the-fly simulations. The method is applied to a variety of syst
 ems\, showing e.g. that intersystem crossing can take place on a femtoseco
 nd timescale even in organic molecules with only relatively small spin-orb
 it couplings (see [5] and references therein).\n\nReferences\n[1] J. Behle
 r\, J. Phys.: Condens. Matter\, 26 (2014) 183001.\n[2] M. Gastegger\, P. M
 arquetand J. Chem. Theory Comput.\, 11 (2015) 2187-2198.\n[3] M. Gastegger
 \, C. Kauffmann\, J. Behler\, P. Marquetand\, J. Chem. Phys.\, 144 (2016) 
 194110.\n[4] M. Richter\, P. Marquetand\, J. González-Vázquez\, I. Sola\
 , L. González\, J. Chem. Theory\, Comput.\, 7 (2011) 1253-1258.\n[5] S. M
 ai\, P. Marquetand\, L. González\, Int. J. Quantum Chem.\, 115 (2015) 121
 5-1231.\n[6] S. Mai\, M. Richter\, M. Ruckenbauer\, M. Oppel\, P. Marqueta
 nd\, L. González\, SHARC\, Program Package for Non-Adiabatic Dynamics\, s
 harc-md.org (2014).
LOCATION:BCH 3118 https://plan.epfl.ch/?room==BCH%203118
STATUS:CONFIRMED
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