TD Swinburne


Designing more durable materials is key to reduce carbon emissions of construction, transportation and energy production. This requires understanding mechanical strength and toughness at the level of jiggling atoms.

We design atomic simulation methods to discover how metals bend and break.

The range of atomic deformation mechanisms is vast- the challenge is to discover and characterize the most influential. A short summary is below; for more detail please see our publications and open source software.


  Main Research Themes

Autonomous exploration at scale: TAMMBER
TAMMBER uses Bayesian methods to build kMC/Markov models with robust UQ on sampling incompleteness. We use this UQ to optimize resourse allocation in parallel computation, and bound predictions of diffusion models.
TDS and D Perez, MSMSE (2022)
TDS and D Perez, NPJ Computational Materials (2020) TAMMBER
TDS and D Perez, PR Materials (2018)

ML-assisted QM/MM simulations
We use retrained ML potentials to embed DFT simulations in large-scale MD with seamless coupling. This permits DFT calculations at unprecedented scales.
P Grigorev et al., TDS, Acta Materialia (2023) LML-retrain
TDS and JR Kermode, PRB (2017)

Vibrational free energies beyond HTST: PAFI
PAFI is a path-constrained sampling routine, giving exact vibrational free energy differences for linear-scaling effort. This enables evaluation of activation free energies for very large systems which can not be treated by HTST approximations.
TDS and M-C Marinica, PRL (2018) PAFI

Surrogate ML models for defect entropics
(PhD of Clovis Lapointe, with M-C Marinica)
Descriptor models typically used for energetics can predict the formation and migration entropy of defects. Allows a geometric interpretation of e.g. the Meyer-Neldel compensation law.
C Lapointe, TDS et al. PRMaterials (2022)
C Lapointe, TDS et al. PRMaterials (2020)

Analysis of Markov Models: PyGT
Much atomic data is a large network of metastable states. The Markov dynamics cannot be treated by usual routines (LAPACK) due to conditioning issues; PyGT provides a solution for these challenging networks.
TDS and DJ Wales, JCTC (2020) PyGT

Mean-field models for lattice vibrations: BLaSa
Analytic mean-field approach for local anharmonic models, evaluating anharmonic vibrational phase free energies for milliseconds of effort. Current developments are within the PhD of R Dsouza since 2021.
TDS et al., J Neugebauer PRB Rapid Communications (2020) BLaSa


  • Tom Swinburne
  • me 10/18-:  CNRS researcher, CINaM
    04/17-06/18:  Postdoc, T-1, LANL
    03/15-03/17:  EuroFusion fellow, CCFE
    10/11-03/15:  MSc+PhD, Imperial College London
    Curriculum Vitae
  • Petr Grigorev
  • Petr Grigorev 20-23:  Postdoc, Machine learning assisted DFT methods
    Funded by ANR MEMOPAS (PI: TDS)
    2024- CNRS researcher
    Personal Website
  • Raynol Dsouza
  • 09/20-09/23:  PhD, mean field vibration models. External with Prof J Neugebauer, MPIE Dusseldorf
  • Reza Namakian
  • -03/23:  PhD, anharmonic effects in plasticity. External with Prof D Moldovan, Louisiana State University, USA

      Past Members

  • Clovis Lapointe
  • 18-22:  PhD, Machine learning defect entropics. With Dr MC Marinica, CEA Saclay
    now: Postdoc, U Lorraine
  • Deepti Kannan
  • 20-21:  MSc, reducing Markov Chains. With Prof DJ Wales, Cambridge.
    now: PhD, MIT

      Main Collaborators

  • Prof David Wales FRS, Univ. Cambridge, UK
  • Analysis and convergence of highly metastable systems; Markov models
    JCTC 2020 PyGT
  • Dr Mihai-Cosmin Marinica, SRMP, CEA Saclay, FR
  • Linear machine learning models, free energy calculation
    PRMat 2020 PRL 2018 PAFI
  • Dr Danny Perez, T-1, Los Alamos, USA
  • Massively parallel sampling of metastable systems
    NPJ Comp. Mat 2020 TAMMBER
  • Prof James Kermode, Univ. Warwick, UK
  • Hybrid DFT/empirical methods
    PRB 2017 arXiv 2021/2 LML-retrain
  • Prof Jörg Neugebauer, Max Planck für Eisenforschung, DE
  • Mean field models for anharmonic lattice vibrations
    PRB RC 2020 BLaSa

      Recent Publications

    = corresponding author(s). Full list at Google Scholar.


  • PAFI- Projected Average Force Integrator
  • Anharmonic free energy barrier evaluations using in LAMMPS/MPI/C++   
    Physical Review Letters 2018   

    Works using PAFI (more coming soon...)
    Y Sato et al., D Rodney MRL (2021)   
    R Namakian et al. Computational Material Science (2022, accepted)   

  • TAMMBER- Temperature Accelerated Markov Models, Bayesian Estimation of Rates
  • Massively parallel, autonmous exploration of atomic systems   
    Physical Review Materials 2018  
    TDS and D Perez, NPJ Computational Materials (2020)   

    Works using TAMMBER (more coming soon...)
    K Ferasat et al., Materialia (2021)   

  • PyGT- Graph Transformation in Python
  • Stable analysis of metastable Markov chains     
    J Chem. Th. Comp. 2020 

    Works using PyGT (more coming soon...)
    TDS et al. JCP (2020)  
    D Kannan et al. JCP (2020)  
    E Woods et al. Proc. Roy. Soc. (2022, accepted)  

  • BLaSa- Bond Lattice Sampling and Analytics
  • Execution and analysis of bond lattice dynamics  
    Physical Review B Rapid Communications 2020  

    Works using BLaSa (coming soon!)
    PhD of Raynol Dsouza (MPIE Dusseldorf)


  • CEA PTC ANEMONE (2022-2024)
  • Co-PI with Dr L Ventelon, CEA Saclay, developing ML-assisted DFT for ab initio accuracy in large scale simulations of extended defects.

  • ANR MeMoPas (2020-2022)
  • PI on ANR JCJC project, Mesoscale models from massively parallel atomistic simulations: uncertainty driven, self-optimizing strategies for hard materials

  • EuroFusion / IREMEV program
  • Computational resources (2020-2022) for studies of timescale estimation of microstructural evolution

  • GENCI / IDRIS national supercomputing centers
  • Computational resources (2019-2023) for multiple studies of defect diffusion and plasticity mechanisms

      Job Openings

    CNRS "Emergence" Postdoc: Automatic Differentiation of Energy Landscapes We currently have an opening for a 12 month postdoctoral project concerning uncertainty quantification of diffusion models, which will use emerging automatic differentation tools. Start date October 2023.
    If this sounds interesting, please email me with a CV and motivation letter.

    If you are interested in masters or docotral projects at funded by the AMU doctoral school, please email me.

      Some Presentations

  • Kink limited motion of line defects: multiscale simulation and analysis
  • Applied analysis seminar, Imperial College London, February 2019 (Invited)

  • Kink limited Orowan strengthening and the brittle to ductile transition of bcc metals
  • Oxford MFFP Meeting, September 2018 (Invited)

  • Uncertainty-driven construction of Markov models from accelerated molecular dynamics
  • Advances in Computational Statistical Physics, CIRM, France, September 2018 (Invited)

  • Fast, vacancy-free climb of dislocation loops in bcc metals
  • NUMAT conference, Montpellier, France, 2016

  • Multiscale analysis of nonlinear dislocation models
  • MMM conference, Berkeley, USA, 2014


       thomas "." swinburne cnrs "." fr

       CINaM, Campus de Luminy, 13288 Marseille, FRANCE