🚀 New publication in Physical Review E!
👉 “Bridge function as a functional of the radial distribution function: Operator learning and application”, https://journals.aps.org/pre/abstract/10.1103/4962-9rch

We present a machine-learning approach that improves the prediction of structural and thermodynamic properties of liquids. By training a deep operator network on simulation data, we can accurately infer the bridge function — a long-standing challenge in statistical mechanics.

🔍 Why it matters for industry:
Enables faster and more accurate modeling of complex fluids
Reduces reliance on costly simulations
Supports innovation in areas like materials design, chemical engineering, and pharmaceuticals
This work demonstrates how AI can bridge fundamental theory and industrial application.
👏 Thanks to my co-authors and collaborators for making this possible!