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Gas-evolving photochemical reactions use light and mild conditions to access strained organic compounds irreversibly. Cyclopropenones are a class of light-responsive molecules used in bioorthogonal photoclick reactions; their excited-state decarbonylation reaction mechanisms are misunderstood due to their ultrafast (<100 femtosecond) lifetimes. We have combined multiconfigurational quantum mechanical (QM) calculations and non-adiabatic molecular dynamics (NAMD) simulations to uncover the excited-state mechanism of cyclopropenone and a photoprotected cyclooctyne-(COT)-precursor in gaseous and explicit aqueous environments. We explore the role of H-bonding with fully quantum mechanical explicitly solvated NAMD simulations for the decarbonylation reaction. The cyclopropenones pass through asynchronous conical intersections and have dynamically concerted photodecarbonylation mechanisms. The COT-precursor has a higher quantum yield of 55% than cyclopropenone (28%) because these trajectories prefer to break a σCC bond to avoid the strained trans-cyclooctene geometries. Our solvated simulations show an increased quantum yield (58%) for the systems studied here.
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This content will become publicly available on December 1, 2026
Advancing nonadiabatic molecular dynamics simulations in solids with E(3) equivariant deep neural hamiltonians
Abstract Non-adiabatic molecular dynamics (NAMD) simulations have become an indispensable tool for investigating excited-state dynamics in solids. In this work, we propose a general framework, N2AMD (Neural-Network Non-Adiabatic Molecular Dynamics), which employs an E(3)-equivariant deep neural Hamiltonian to boost the accuracy and efficiency of NAMD simulations. Distinct from conventional machine learning methods that predict key quantities in NAMD, N2AMD computes these quantities directly with a deep neural Hamiltonian, ensuring excellent accuracy, efficiency, and consistency. N2AMD not only achieves impressive efficiency in performing NAMD simulations at the hybrid functional level within the framework of the classical path approximation (CPA), but also demonstrates great potential in predicting non-adiabatic coupling vectors and suggests a method to go beyond CPA. Furthermore, N2AMD demonstrates excellent generalizability and enables seamless integration with advanced NAMD techniques and infrastructures. Taking several extensively investigated semiconductors as the prototypical system, we successfully simulate carrier recombination in both pristine and defective systems at large scales where conventional NAMD often significantly underestimates or even qualitatively incorrectly predicts lifetimes. This framework offers a reliable and efficient approach for conducting accurate NAMD simulations across various condensed materials.
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- Award ID(s):
- 2154367
- PAR ID:
- 10583516
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 16
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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