A rigid, stacked aromatic scaffold that relaxes fast, then stubbornly refuses to leave the excited state.
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Better electron correlation can improve nonadiabatic dynamics—but it also introduces new numerical fragilities that we can’t ignore.
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Active learning turns costly surface-hopping into a push-button workflow.
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How a smart feature and a pinch of phase-fixing let machine learning predict nonadiabatic couplings like a pro.
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A bridge between molecular and solid-state photochemistry, enabling excited-state dynamics in extended systems.
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A community perspective on benchmarking and challenges of simulations beyond the Born-Oppenheimer approximation.
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A new AI-powered protocol learns excited states with accuracy that finally makes it practical.
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A new software for multiple spawning in the Newton-X framework.
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New Software Unveils Hidden Patterns in Nonadiabatic Dynamics.
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Hydrogen migration quickly kills DPP dimer’s excited states.
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MD simulations can be 10x faster by replacing files with socket communication.
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