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williamdavie/README.md

Quantum materials are materials that exhibit non-trivial exotic properties as a consequence of quantum mechanics.

Supported by the NDA, my PhD’s core focus is the behaviour of helium in plutonium dioxide (Article), a system with strong electronic correlations that give rise to unconventional and exciting physics. I investigate how to train machine-learned interatomic potentials capable of capturing the exotic behaviour of plutonium and other strongly correlated materials.

Broadly, my interests lie in many-body quantum theory and in developing computational tools and algorithms for atomistic modelling, including improving the accuracy and training of machine-learning models.

William Davie, willdavie2002@gmail.com.

Department of Material Science and Metallurgy, University of Cambridge.

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  1. mlipts mlipts Public

    Machine Learned Interatomic Potentials - Training Suite (MPLITS). Seamless generation of DFT data-sets for MLIP training/fine-tuning.

    Python 8