ArticleJournal of the American Chemical Society2024
Machine Learning for Polaritonic Chemistry: Accessing Chemical Kinetics.
Article in Journal of the American Chemical Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- A macroscopic condensation theory for vibrational strong coupling effects.Nature communications · 2026Article
- Polaritonic Coupled Cluster Theory for Unpolarized Cavities Exploiting Point-Group Symmetry.Journal of chemical theory and computation · 2026Article
- Collectively-Modified Intermolecular Electron Correlations: The Connection of Polaritonic Chemistry and Spin Glass Physics.Chemical reviews · 2026Review
- Two-dimensional layered metal oxides (2D LMOs) for next-generation electronic devices.Nanoscale advances · 2026Review
- Mini Review: Synergizing Driven Quantum Dynamics, AI, and Quantum Computing for Next-Gen Materials Science.The journal of physical chemistry letters · 2025Review
- Theoretical and quantum mechanical deconstruction of vibrational energy transfer pathways modified by collective vibrational strong coupling.Nature communications · 2025Article
- Unveiling the role of dark states in dynamic control of azopyrrole photoisomerization by light-matter interaction.Communications chemistry · 2025Article
- Controlling Plasmonic Catalysis via Strong Coupling with Electromagnetic Resonators.Nano letters · 2024Article
- Microfluidics and Nanofluidics in Strong Light-Matter Coupling Systems.Nanomaterials (Basel, Switzerland) · 2024Review
- Tensorial Properties via the Neuroevolution Potential Framework: Fast Simulation of Infrared and Raman Spectra.Journal of chemical theory and computation · 2024Article
- A Quantum Chemistry Approach to Linear Vibro-Polaritonic Infrared Spectra with Perturbative Electron-Photon Correlation.The journal of physical chemistry letters · 2024Article
- Collective Strong Coupling Modifies Aggregation and Solvation.The journal of physical chemistry letters · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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-2-trimethylsilylacetylene, which has been studied previously both experimentally and using
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.