David Williams

28
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Présentation

ORCID: 0000-0001-9627-5647 Web of Science: AFR-4512-2022

Past Employment

Postdoctoral researcher with a focus on developing efficient artificial neural network based approaches for accurate, high dimensional excited state dynamics.

  • Sep 2023 – Present European MCSA-Bienvenue postdoctoral fellow at the Institute of Physics Rennes (IPR), France
  • Spring 2023 collaborating visit at the IPR, Rennes, France
  • Year 2022 postdoctoral researcher in the Martínez group at Stanford University, CA, USA
  • Year 2021 postdoctoral reseacher in the Eisfeld group at the University of Bielefeld, Germany
  • Jan 2021 PhD under Wolfgang Eisfeld at the University of Bielefeld, Germany

Research Interests

  • Photochemical processes in atmospheric and astrochemistry: Particular focus on isolated molecules in the gas phase at finite temperature, with research experience in the modelling of photodetachment processes.
  • Numerical method development based on artificial neural networks: Developed and refined schemes for the construction of diabatic potential energy surfaces using artificial neural networks. Particularly focused on preconditioning techniques to imbue models with physical information, reducing the strain of the network.
  • Efficient, modularized models of complex systems: Continued efforts to provide schemes that allow for models to be extended to the full-dimensional problem by building upon restricted-dimensional models to mitigate innate problems of high-dimensional coordinate spaces (curse of dimensionality).
  • Molecular quantum dynamics of excited states: Conducted in-depth theoretical studies of Jahn-Teller type systems and the impact of the geometric phase effect on their spectroscopy.
  • Mechanochemistry and photoswitches: General interest in the development of high quantum yield photoswitches and molecular machines.

Education

  • 2016 – Jan. 2021 Dr. rer. nat. (PhD), Theoretical Chemistry, Bielefeld University, Germany
    • "Conquering coupled diabatic potential energy surfaces with artificial neural networks for nonadiabatic dynamics''
  • 2014 – 2016 Master of Science, Theoretical Chemistry, Bielefeld University, Germany
    • "Neural Network Based Methods for the Representation of Diabatic Potential Energy Surfaces''


Compétences

Excited state modeling Nonadiabatically coupled potential method development Artificial neural network based models

Publications

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Publications

Image document

Electronic quenching of sulfur induced by argon collisions

David M. G. Williams , Nicole Weike , Manuel Lara , Kevin Dunseath , Alexandra Viel
Physical Chemistry Chemical Physics, 2025, 27 (7), pp.3722-3731. ⟨10.1039/D4CP04586F⟩
Article dans une revue hal-04907815 v2
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Geometric phase in coupled cluster theory

David Williams , Eirik Kjønstad , Todd Martínez
The Journal of Chemical Physics, 2023, 158 (21), ⟨10.1063/5.0151856⟩
Article dans une revue hal-04179328 v1
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Simulation of the photodetachment spectra of the nitrate anion (NO3-) in the B 2E' energy range and non-adiabatic electronic population dynamics of NO3

David M. G. Williams , Wolfgang Eisfeld , Alexandra Viel
Physical Chemistry Chemical Physics, 2022, 24 (40), pp.24706-24713. ⟨10.1039/D2CP02873E⟩
Article dans une revue hal-03740299 v1
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Accurate quantum dynamics simulation of the photodetachment spectrum of the nitrate anion (NO3−) based on an artificial neural network diabatic potential model

Alexandra Viel , David M. G. Williams , Wolfgang Eisfeld
The Journal of Chemical Physics, 2021, 154 (8), pp.084302. ⟨10.1063/5.0039503⟩
Article dans une revue hal-03149863 v1
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Complete Nuclear Permutation Inversion Invariant Artificial Neural Network (CNPI-ANN) Diabatization for the Accurate Treatment of Vibronic Coupling Problems

David M. G. Williams , Wolfgang Eisfeld
Journal of Physical Chemistry A, 2020, 124 (37), pp.7608-7621. ⟨10.1021/acs.jpca.0c05991⟩
Article dans une revue hal-02984550 v1
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Diabatic neural network potentials for accurate vibronic quantum dynamics -The test case of planar NO3

David M. G. Williams , Wolfgang Eisfeld , Alexandra Viel
The Journal of Chemical Physics, 2019, 151 (16), pp.164118. ⟨10.1063/1.5125851⟩
Article dans une revue hal-02317939 v1
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Quantum dynamics and geometric phase in E ⊗ e Jahn-Teller systems with general Cnv symmetry

Thomas Weike , David M. G. Williams , Alexandra Viel , Wolfgang Eisfeld
The Journal of Chemical Physics, 2019, 151 (7), pp.074302. ⟨10.1063/1.5115396⟩
Article dans une revue hal-02267828 v1
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Neural network diabatization: A new ansatz for accurate high-dimensional coupled potential energy surfaces

David M. G. Williams , Wolfgang Eisfeld
The Journal of Chemical Physics, 2018, 149 (20), pp.204106. ⟨10.1063/1.5053664⟩
Article dans une revue hal-02906091 v1
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A new approach for the development of diabatic potential energy surfaces: Hybrid block-diagonalization and diabatization by ansatz

Nils Wittenbrink , Florian Venghaus , David M. G. Williams , Wolfgang Eisfeld
The Journal of Chemical Physics, 2016, 145 (18), pp.184108. ⟨10.1063/1.4967258⟩
Article dans une revue hal-02906093 v1

A "post vibronic coupling ansatz" for accurate diabatic potentials

David M. G. Williams
THEMOSIA Western Pole scientific day (2024), Dec 2024, Rennes, France
Communication dans un congrès hal-04822824 v1

Accurate coupled potential energy surfaces: transcending vibronic coupling with artificial neural networks

David M. G. Williams
Invited seminar, CIMAP, Nov 2024, Caen, France
Communication dans un congrès hal-04830615 v1

Beyond Ultra-Fast Processes: Accurate Coupled Potential Energy Surfaces

David M. G. Williams
Invited seminar, Strasbourg Institute of Chemistry, Nov 2024, Strasbourg, France
Communication dans un congrès hal-04830634 v1

Analytical and Numerical Pathways Towards Understanding Nonadiabatic Dynamics

David M. G. Williams
Invited seminar, Institut Charles Gerhardt Montpellier, Dec 2023, Montpellier, France
Communication dans un congrès hal-04718452 v1

Efficient Nonadiabatic Dynamics with Neural Network Based Coupled Potential Energy Surfaces

David M. G. Williams
Invited Seminar, CEISAM Lab, Mar 2023, Nantes, France
Communication dans un congrès hal-04718438 v1

Artificial Neural Networks: Toward Efficient Nonadiabatic Dynamics with Coupled Potential Energy Surfaces

David M. G. Williams , Alexandra Viel , Wolfgang Eisfeld , Todd J Martínez
American Conference on Theoretical Chemistry, https://www.actc2022.com/, Jul 2022, Palisades Tahoe, United States
Communication dans un congrès hal-03976934 v1

Dynamics on accurate coupled artificial neural network based potential surfaces : NO_3^- photodetachment spectra

Alexandra Viel , David M. G. Williams , Wolfgang Eisfeld
7th High Dimensional Quantum Dynamics (HDQD), https://www.hdqd2022.org/, Jul 2022, Groningen, Netherlands
Communication dans un congrès hal-02262273 v1

Photodetachment spectrum of NO3-: Jahn-Teller effect and artificial neuron network

Alexandra Viel , David M. G. Williams , Wolfgang Eisfeld
CECAM2021 : Modeling dilute matter under ultracold solvent: from quantum structure to dynamics and reactivity, May 2021, Grenoble, France
Communication dans un congrès hal-03212344 v1

Symmetry, geometric phase and spectroscopy

Wolfgang Eisfeld , Thomas Weike , David M. G. Williams , Alexandra Viel
Electronic Structure, Dynamics & Spectroscopy (Domcke's 70th Birthday), Apr 2018, Garching, Germany
Communication dans un congrès hal-01773875 v1

The Molecular Foucault Pendulum: What is a "Geometric Phase"?

David M. G. Williams
ERRIE “European Responsible Research and Innovation Event” 2024, Oct 2024, Rennes, France
Poster de conférence hal-04830735 v1

Neural Network coupled potential and dipole surfaces for interstellar molecules

David M. G. Williams , Jean Paul Nshuti , Alexandra Viel
24th European Conference on the Dynamics of Molecular Systems - MOLEC2024, Jun 2024, Aarhus, Denmark
Poster de conférence hal-04597242 v1

Representing non-A_1 Operators:C_nv Diabatic Dipole Transition Surfaces

Jean Paul Nshuti , David M. G. Williams , Alexandra Viel
THEMOSIA Western Pole scientific day (2024), Dec 2024, Rennes, France
Poster de conférence hal-04816579 v1

Diabatic potential energy surfaces for Renner-Teller systems using Artificial Neural Networks

David M. G. Williams , Alexandra Viel
8th High Dimensional Quantum Dynamics (HDQD), Jul 2024, Hamburg, Germany
Poster de conférence hal-04579831 v1

On the vibronic level structure of cubic point groups

Alexis Texier , David M. G. Williams , Alexandra Viel
8th High Dimensional Quantum Dynamics (HDQD), Jul 2024, Hamburg, Germany
Poster de conférence hal-04579829 v1

Representing non-A_1 Operators:C_nv Diabatic Dipole Transition Surfaces

Jean Paul Nshuti , David M. G. Williams , Alexandra Viel
8th High Dimensional Quantum Dynamics (HDQD), Jul 2024, Hamburg, Germany
Poster de conférence hal-04579830 v1

Efficient Nonadiabatic Dynamics with Artificial Neural Networks

David M. G. Williams , Alexandra Viel , Wolfgang Eisfeld , Todd J Martínez
American Conference on Theoretical Chemistry, Jul 2022, Palisades Tahoe, United States
Poster de conférence hal-03976949 v1

Accurate vibronic quantum dynamics of NO3 using a diabatic neural network potential

David M. G. Williams , Wolfgang Eisfeld
22nd European Conference on the Dynamics of Molecular Systems, Aug 2018, Dinard, France
Poster de conférence hal-03976972 v1

Neural Network Diabatization: A new ansatz for high-dimensional coupled potential energy surfaces

David M. G. Williams , Wolfgang Eisfeld
Symposium on Theoretical Chemistry, Aug 2017, Basel, Switzerland
Poster de conférence hal-03976989 v1