ReviewJournal of chemical theory and computation2025
Perspective: Vibronic Coupling Potentials for Trajectory-Based Excited-State Dynamics.
Review in Journal of chemical theory and computation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed.
- How Structural Subtleties Modulate Excited-State Lifetimes in Cyclometalated Cobalt(III) Complexes: Nonadiabatic Molecular Dynamics Study.Journal of computational chemistry · 2026Article
- Design Principles for Next Generation of Small Organic Molecules for Photodynamics Therapy Revealed by Nonadiabatic Molecular Dynamics.Chemistry (Weinheim an der Bergstrasse, Germany) · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This Perspective reviews the use of vibronic coupling (VC) potentials in trajectory-based excited-state dynamics simulations. Originally developed to provide simplified yet physically grounded representations of nonadiabatic interactions, VC models─particularly their linear version (LVC)─have facilitated extensive investigations of photophysical and photochemical processes, in both molecular and condensed-phase systems. By effectively capturing the coupling between electronic and vibrational motions, VC models enable efficient dynamical simulations, making it feasible to investigate larger and more complex systems, for longer time scales or relying on potential energy surfaces calculated with high levels of theory. These models provide valuable insights into energy and charge transfer mechanisms following photoexcitation, shedding light on excited-state lifetimes and intricate relaxation pathways. Here, we discuss their integration with three trajectory-based computational families of methods: surface hopping, variational multiconfigurational Gaussian, and exact-factorization-derived approaches. We showcase how VC models have helped uncovering key mechanistic insights, including state-specific intersystem crossing pathways and vibrational mode selectivity. As the field progresses, VC-based approaches are expected to be increasingly combined with machine learning, anharmonic corrections, and hybrid LVC/MM frameworks, broadening their applicability to complex, flexible, and solvated environments. We highlight the advantages of VC-based potentials for trajectory-based simulations, emphasizing their computational efficiency and usefulness for benchmarking and exploring photophysical processes in molecular systems.
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Registered trials
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