Davis Thomas Daniel

Computational Chemist · Material Scientist · PhD in Chemistry

Bridging molecular modelling, machine learning, and analytical spectroscopy to understand, design and optimise materials.

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About

Scientist. Developer. Innovator.

Computational chemist and material scientist with skills spanning molecular modelling, software development, electrochemistry and magnetic resonance spectroscopy.

My work sits at the intersection of atomistic simulation, machine learning, and in operando EPR/NMR spectroscopy, combining computational methods with experimental techniques for advancing materials research.

I have also developed several open-source scientific software tools including ILTpy and EPRpy, and believe good research software engineering practices are crucial for reproducible research workflows.

5+
Years of research experience
10+
Peer-reviewed publications
4+
Open-source software packages and tools: ILTpy, EPRpy and more.
ILTpy
Inverse Laplace transform in python. Click to know more.
Research Focus

Expertise.

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Computational Modelling
Experience with DFT, ab initio molecular dynamics, nudged elastic band calculations, and classical MD applied to energy materials, polymers, and electrolytes on HPC systems.
DFTAIMDORCAHPCASE
ML
Machine Learning for Materials
Experience with molecular representation learning and design of active-learning workflows integrating ML models with atomistic simulations and experimental data to accelerate materials discovery.
scikit-learnGRUMLIPsPyTorchDeep Learning
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EPR & NMR Spectroscopy
In operando EPR and NMR to track real-time redox states, lithium solvation, and degradation mechanisms in organic radical batteries and solid electrolytes.
EPR spectroscopyNMR spectroscopyIn Operando electrochemistry
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Scientific Software
Lead developer of ILTpy (regularised multi-dimensional inverse Laplace transform) and EPRpy (Bruker EPR data processing).
PythonAlgorithm developmentILTpyEPRpyNumerical methods
Publications

Selected work.

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