Abstract

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)