Machine Learning for Polaritonic Chemistry: Accessing Chemical Kinetics

Abstract

Altering chemical reactivity and material structure in confined optical environments is on the rise, and yet, a conclusive understanding of the microscopic mechanisms remains elusive. This originates mostly from the fact that accurately predicting vibrational and reactive dynamics for soluted ensembles of realistic molecules is no small endeavor, and adding (collective) strong light−matter interaction does not simplify matters. Here, we establish a framework based on a combination of machine learning (ML) models, trained using density-functional theory calculations and molecular dynamics to accelerate such simulations. We then apply this approach to evaluate strong coupling, changes in reaction rate constant, and their influence on enthalpy and entropy for the deprotection reaction of 1-phenyl-2trimethylsilylacetylene, which has been studied previously both experimentally and using ab initio simulations. While we find qualitative agreement with critical experimental observations, especially with regard to the changes in kinetics, we also find differences in comparison with previous theoretical predictions. The features for which the ML-accelerated and ab initio simulations agree show the experimentally estimated kinetic behavior. Conflicting features indicate that a contribution of dynamic electronic polarization to the reaction process is more relevant than currently believed. Our work demonstrates the practical use of ML for polaritonic chemistry, discusses limitations of common approximations, and paves the way for a more holistic description of polaritonic chemistry.

Electronic Strong Coupling Modifies the Ground-state Intermolecular Interactions in Chlorin Thin Films

“…Our experiment under ESC, together with other VSC studies, [32][33][34][35][65][66][67] points to the possibility that collective light-matter strong coupling can alter the weak intermolecular interaction forces. Such modifications to the inter-or intramolecular interactions can indeed cause changes to the molecular organization [33][34][35] and alignment of magnetic spin, 68 change the metal to insulator transitions, 69 and may open up new conducting pathways.…”

Tensorial Properties via the Neuroevolution Potential Framework: Fast Simulation of Infrared and Raman Spectra

“…Naturally, this includes the molecular configurations along a chemical reaction such that experimentally observable spectral changes can be connected to metastable complexes. One such complex is PTAF – (see inset in Figure ), the intermediate reaction minimum in the deprotection reaction 1-phenyl-2-trimethylsilylacetylene (PTA) with tetra-n-butylammonium fluoride. − …”

“…One such complex is PTAF – (see inset in Figure 5 ), the intermediate reaction minimum in the deprotection reaction 1-phenyl-2-trimethylsilylacetylene (PTA) with tetra-n-butylammonium fluoride. 78 − 81 …”

Cavity Catalysis of an Enantioselective Reaction under Vibrational Strong Coupling

“…[22,23] A few theoretical studies are available suggesting the collective nature and resonance effect in polaritonic chemistry. [24][25][26][27][28] Recent reviews are also available for the readers to glimpse interesting advances in polaritonic chemistry. [2,[29][30][31] Fabry-Perot (FP) cavity is the simplest configuration available and is used in almost all polaritonic chemistry experiments (including solid-state) reported in the literature.…”