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      Theoretical perspectives on non-Born–Oppenheimer effects in chemistry

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          Abstract

          The Born–Oppenheimer approximation, which assumes that the electrons respond instantaneously to the motion of the nuclei, breaks down for a wide range of chemical and biological processes. The rate constants of such nonadiabatic processes can be calculated using analytical theories, and the real-time nonequilibrium dynamics can be described using numerical atomistic simulations. The selection of an approach depends on the desired balance between accuracy and efficiency. The computational expense of generating potential energy surfaces on-the-fly often favours the use of approximate, robust and efficient methods such as trajectory surface hopping for large, complex systems. The development of formally exact non-Born–Oppenheimer methods and the exploration of well-defined approximations to such methods are critical for providing benchmarks and preparing for the next generation of faster computers. Thus, the parallel development of rigorous but computationally expensive methods and more approximate but computationally efficient methods is optimal. This Perspective briefly summarizes the available theoretical and computational non-Born–Oppenheimer methods and presents examples illustrating how analytical theories and nonadiabatic dynamics simulations can elucidate the fundamental principles of chemical and biological processes. These examples also highlight how theoretical calculations are able to guide the interpretation of experimental data and provide experimentally testable predictions for nonadiabatic processes.

          This article is part of the theme issue ‘Chemistry without the Born–Oppenheimer approximation’.

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
                Phil. Trans. R. Soc. A.
                The Royal Society
                1364-503X
                1471-2962
                May 16 2022
                March 28 2022
                May 16 2022
                : 380
                : 2223
                Affiliations
                [1 ]Department of Chemistry, Yale University, New Haven, CT 06520, USA
                Article
                10.1098/rsta.2020.0377
                4d8a8c41-5164-4dd8-bd4f-5bf199f9f167
                © 2022

                https://royalsociety.org/journals/ethics-policies/data-sharing-mining/

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