The design of more durable materials is key to reduce the carbon emissions of construction, transportation and energy production. This requires an understanding of 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 

MLassisted DFT for dislocationdefect interations 

Vibrational free energies beyond harmonicity: PAFI 

Surrogate ML models for defect entropics 

Analysis of Markov Models: PyGT 

Meanfield models for lattice vibrations: BLaSa 
Team

10/18:
CNRS researcher, CINaM 04/1706/18: Postdoc, T1, LANL 03/1503/17: EuroFusion fellow, CCFE 10/1103/15: MSc+PhD, Imperial College London Curriculum Vitae 


2023:
Postdoc, Machine learning assisted DFT methods Funded by ANR MEMOPAS (PI: TDS) Personal Website 


09/1801/22: PhD, Machine learning for defect entropics. Joint with Dr MC Marinica, CEA Saclay  

09/2009/23: PhD, mean field vibration models. External with Prof J Neugebauer, MPIE Dusseldorf 
Main Collaborators

Analysis and convergence of highly metastable systems; Markov models e.g. JCTC 2020 PyGT 

Linear machine learning models, free energy calculation e.g. PRMat 2020 PRL 2018 PAFI 

Massively parallel sampling of metastable systems e.g. NPJ Comp. Mat 2020 TAMMBER 

Hybrid DFT/empirical methods e.g. PRB 2017 arXiv 2021/2 LMLretrain 

Mean field models for anharmonic lattice vibrations PRB RC 2020 BLaSa 
Past Members

2121: M2 project, Learning of transition states, AixMarseille University.  

2021: MSc project, reducing Markov Chains. With Prof DJ Wales, Cambridge. Now PhD, MIT. 
News
Recent Publications
† = corresponding author(s). Full list at Google Scholar.
Software
 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)  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 (2021)
 BLaSa Bond Lattice Sampling and Analytics
 Execution and analysis of bond lattice dynamics
Physical Review B Rapid Communications 2020
Funding
 ANR MeMoPas (20202022)
PI on ANR JCJC project, Mesoscale models from massively parallel atomistic simulations: uncertainty driven, selfoptimizing strategies for hard materials
 EuroFusion / IREMEV program
Computational resources (20202021) for studies of timescale estimation of microstructural evolution
 GENCI / IDRIS national supercomputing centers
Computational resources (20192020,20202021) for highthroughput studies of defect diffusion mechanisms
Job Openings
Some Presentations
 Kink limited motion of line defects: multiscale simulation and analysis
 Applied analysis seminar, Imperial College London, February 2019 (Invited)
Slides  Kink limited Orowan strengthening and the brittle to ductile transition of bcc metals
 Oxford MFFP Meeting, September 2018 (Invited)
Slides  Uncertaintydriven construction of Markov models from accelerated molecular dynamics
 Advances in Computational Statistical Physics, CIRM, France, September 2018 (Invited)
Slides  Fast, vacancyfree climb of dislocation loops in bcc metals
 NUMAT conference, Montpellier, France, 2016
Slides  Multiscale analysis of nonlinear dislocation models
 MMM conference, Berkeley, USA, 2014
Slides