Neural DFT: A transformative approach to multiscale modelling

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• Dr Stephen J Cox (Durham University)
• Monday 17 March 2025, 14:30-15:00
• https://zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT09.

If you have a question about this talk, please contact Alexander R Epstein.

Many problems across biology, chemistry, physics, and materials science are inherently multiscale in nature. In this talk, I will discuss how classical density functional techniques, combined with deep learning methods, offer new and exciting ways to probe emergent physics across length scales. Not only can we now understand structure and thermodynamics accurately and efficiently, and across much larger length scales than with molecular simulations, but we can also investigate new physics. For example, I will introduce “dielectrocapillarity”—- that is, how electric field gradients impact phase behavior and criticality of fluids.

AT Bui & SJ Cox, Learning classical density functionals for ionic fluids, arXiv.2410.02556 (2024) [accepted in Phys. Rev. Lett.]
AT Bui & SJ Cox, Dielectrocapillarity for exquisite control of fluids, arXiv.2503.09855 (2025)
AT Bui & SJ Cox, A first principles approach to electromechanics in liquids, arXiv.2503.09768 (2025)
Sammüller et al., Neural functional theory for inhomogeneous fluids: Fundamentals and applications, Proc. Natl. Acad. Sci. USA, 120, e2312484120 (2023)
Sammüller et al., Hyperdensity Functional Theory of Soft Matter, Phys. Rev. Lett. 133, 098201 (2024)

This talk is part of the Lennard-Jones Centre series.

This talk is included in these lists:

• Hanchen DaDaDash
• Lennard-Jones Centre
• https://zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT09

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