atomistiC approacHes for plasmOnic Photo Induced phenomeNa

ERC (European Research Council)HORIZON-ERCID: 101219149
EC Contribution
€13,841
Consortium Size
1 orgs
Start Year
2026
Summary

Plasmonic catalysis is the field of chemistry that studies chemical reactions catalyzed by surface plasmons. By exploiting their unique properties, it offers enhanced reaction rates and selectivity. From a theoretical point of view, describing plasmonic catalysis is particularly challenging, because many mechanisms take place simultaneously. Such complexity and the limitations of current theoretical methods hinder a comprehensive understanding of the phenomenon. In fact, current models struggle to capture the interplay between reaction dynamics, nanostructure response, and plasmonic decay, often oversimplifying critical factors such as shape, size, and atomistic features of the plasmonic substrate.CHOPIN aims to bridge the current gaps in the modeling of plasmonic catalysis, by integrating state-of-the-art techniques from theoretical chemistry, condensed matter physics, and quantum electrodynamics. To this end, I will introduce novel, fully atomistic multiscale methodologies to describe the key steps of plasmonic catalysis: adsorption and activation of the reactants upon plasmon photoexcitation, reaction pathways, and desorption of products. The models will permit quantifying and rationalizing the effects of non-uniform spatial plasmonic fields, plasmonic decay, and hot carrier injections on chemical reactions catalyzed by plasmonic structures of any shape, size, and composition.The developed methodologies will be carefully validated and tested against selected pilot applications, focusing on complex nanoreactors with unique features such as highly localized electric fields demanding a fully atomistic description of the system. By demonstrating the robustness, effectiveness, and versatility of the proposed approaches in modeling plasmonic photo-induced phenomena, CHOPIN aims to provide a platform for integrating experimental results with theoretical predictions, thus fostering a deeper understanding of the underlying processes.

Consortium (1)