David Williams

Identifiants chercheurs

IdHAL :

dmg-williams

Présentation

ORCID:0000-0001-9627-5647Web 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.

2026

postdoctoral researcher at the GREYC and CIMAP labs at Caen University, France

Sep 2023 – 2025

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

&quot;Conquering coupled diabatic potential energy surfaces with artificial neural networks for nonadiabatic dynamics''

2014 – 2016

Master of Science, Theoretical Chemistry, Bielefeld University, Germany

&quot;Neural Network Based Methods for the Representation of Diabatic Potential Energy Surfaces''

Publications

Article dans une revue (11)

Quasi-infinite order vibronic coupling expansions with neural networks for linear systems: the C$_4$H radical David M. G. Williams,Alexandra Viel The Journal of Chemical Physics, 2025, 163 (2), pp.024136-1-10. ⟨10.1063/5.0272604⟩ Article dans une revue hal-05092956v1
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-04907815v2
Universal diabatic representation of operators using C$_{nv}$/D$_{nh}$ symmetry - I. General derivation Jean Paul Nshuti,David M. G. Williams,Alexandra Viel The Journal of Chemical Physics, 2025, 163 (3), pp.034112-1-12. ⟨10.1063/5.0278678⟩ Article dans une revue hal-05115228v1
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-04179328v1
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-03740299v1
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-03149863v1
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-02984550v1
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-02317939v1
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-02267828v1
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-02906091v1
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-02906093v1

Communication dans un congrès (10)

A &quot;post vibronic coupling ansatz&quot; for accurate diabatic potentials David M. G. Williams THEMOSIA Western Pole scientific day (2024), Dec 2024, Rennes, France Communication dans un congrès hal-04822824v1
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-04830615v1
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-04830634v1
Spectroscopy of Radicals: Representation of Operators in presence of Non-adiabatic Effects Jean Paul Nshuti,David M. G. Williams,Alexandra Viel THEMOSIA Western Pole scientific day (2025), https://rfct-pole-ouest.cnrs.fr/scientific-meetings/info-program/, Dec 2024, Nantes, France Communication dans un congrès hal-05404812v1
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-04718452v1
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-04718438v1
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-03976934v1
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-02262273v1
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-03212344v1
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-01773875v1

Poster de conférence (9)

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-04816579v1
The Molecular Foucault Pendulum: What is a &quot;Geometric Phase&quot;? David M. G. Williams ERRIE “European Responsible Research and Innovation Event” 2024, Oct 2024, Rennes, France Poster de conférence hal-04830735v1
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-04597242v1
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-04579831v1
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-04579830v1
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-04579829v1
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-03976949v1
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-03976972v1
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-03976989v1

Thèse (1)

Conquering coupled diabatic potential energy surfaces with artificial neural networks for nonadiabatic dynamics David M. G. Williams Chemical Sciences. University of Bielefed, 2020. English. ⟨NNT : ⟩ Thèse tel-03917774v1