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Updated: Jan 14, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
Published on: April 12, 2019
Capturing the Complexities of Catalyst-Support Interactions with the Help of Machine Learning
1Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, 08544, USA.
Abstract:
The structure of metal nanoparticles is central to their catalytic activity, but metal-support interactions are difficult to model via quantum-mechanical calculations. Using a machine-learned potential to model supported silver nanoparticles, it has been shown that the idealized nanoparticle shapes commonly invoked in the literature do not reflect experiments for diameters below 8 nm, as reported by Maxson and Szilvási.
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