Surface Hopping Molecular Dynamics

Mai, Sebastian; Marquetand, Philipp; González, Leticia

doi:10.1002/9781119417774.ch16

Cited by 25 publications

(40 citation statements)

References 141 publications

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“…Consequently, many semiclassical and fully quantum schemes were developed entailing various levels of computational complexity and controlled approximations with respect to an exact result (we refer the reader to references in recent reviews − ). Here, the commonly used methods are multiconfigurational time-dependent Hartree (MC-TDH) and the related variational multiconfiguration Gaussian (vMCG) method, ab initio multiple spawning (AIMS), coupled-trajectory mixed quantum–classical method of exact factorization (CT-MQC), and multiconfigurational Ehrenfest with ab initio multiple cloning (MCE-AIMC), − to name a few. As a result, the past couple of decades have witnessed a merging of electronic structure techniques (that provide estimates for electronic energies, wave functions, gradients of potential energy surfaces, and nonadiabatic couplings between levels) and various nonadiabatic algorithms (being essential dynamical propagators), producing versatile computational packages permitting direct atomistic dynamics to address a broad spectrum of problems.…”

Section: Ehrenfest Mean Fieldmentioning

confidence: 99%

“…As a result, the past couple of decades have witnessed a merging of electronic structure techniques (that provide estimates for electronic energies, wave functions, gradients of potential energy surfaces, and nonadiabatic couplings between levels) and various nonadiabatic algorithms (being essential dynamical propagators), producing versatile computational packages permitting direct atomistic dynamics to address a broad spectrum of problems. We further refer the reader to recent comprehensive reviews − ,,, outlining various nonadiabatic methods and the current state of the field.…”

Section: Ehrenfest Mean Fieldmentioning

confidence: 99%

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Nonadiabatic Excited-State Molecular Dynamics Methodologies: Comparison and Convergence

Freixas

White

Nelson

et al. 2021

J. Phys. Chem. Lett.

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Direct atomistic simulation of nonadiabatic molecular dynamics is a challenging goal that allows important insights into fundamental physical phenomena. A variety of frameworks, ranging from fully quantum treatment of nuclei to semiclassical and mixed quantum−classical approaches, were developed. These algorithms are then coupled to specific electronic structure techniques. Such diversity and lack of standardized implementation make it difficult to compare the performance of different methodologies when treating realistic systems. Here, we compare three popular methods for large chromophores: Ehrenfest, surface hopping, and multiconfigurational Ehrenfest with ab initio multiple cloning (MCE-AIMC). These approaches are implemented in the NEXMD software, which features a common computational chemistry model. The resulting comparisons reveal the method performance for population relaxation and coherent vibronic dynamics. Finally, we study the numerical convergence of MCE-AIMC algorithms by considering the number of trajectories, cloning thresholds, and Gaussian wavepacket width. Our results provide helpful reference data for selecting an optimal methodology for simulating excited-state molecular dynamics.

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Section: Ehrenfest Mean Fieldmentioning

confidence: 99%

Section: Ehrenfest Mean Fieldmentioning

confidence: 99%

Nonadiabatic Excited-State Molecular Dynamics Methodologies: Comparison and Convergence

Freixas

White

Nelson

et al. 2021

J. Phys. Chem. Lett.

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“…The good agreement between the experimental and the computed absorption spectrum of [1] + validates this computational approach (Figure ). The computed spectrum is obtained within the nuclear ensemble approach via a Wigner sampling of 200 geometries. The spectrum is then decomposed into the different contributions according to charge-transfer numbers using the TheoDORE software. , …”

Section: Resultsmentioning

confidence: 99%

“…The computed spectrum is obtained within the nuclear ensemble approach via a Wigner sampling of 200 geometries. The spectrum is then decomposed into the different contributions according to charge-transfer numbers using the TheoDORE software. , …”

Section: Resultsmentioning

confidence: 99%

Luminescent Iridium Complexes with a Sulfurated Bipyridine Ligand: PCET Thermochemistry of the Disulfide Unit and Photophysical Properties

et al. 2022

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Molecular systems combining light harvesting and charge storage are receiving great attention in the context of, for example, artificial photosynthesis and solar fuel generation. As part of ongoing efforts to develop new concepts for photoinduced proton-coupled electron transfer (PCET) reactivities, we report a cyclometallated iridium(III) complex [Ir(ppy) 2 ( S−S bpy)](PF 6 ) ([1]PF 6 ) equipped with our previously developed sulfurated bipyridine ligand S−S bpy. A new one-step synthetic protocol for S−S bpy is developed, starting from commercially available 2,2′bipyridine, which significantly facilitates the use of this ligand. [1] + features a two-electron reduction with potential inversion (|E 1 | > | E 2 |) at moderate potentials (E 1 = −1.12, E 2 = −1.11 V versus. Fc +/0 at 253 K), leading to a dithiolate species [1] − . Protonation with weak acids allows for determination of pK a = 23.5 in MeCN for the S−H•••S − unit of [1H]. The driving forces for both the H atom and the hydride transfer are calculated to be ∼60 kcal mol −1 and verified experimentally by reaction with a suitable H atom and a hydride acceptor, demonstrating the ability of [1] + to serve as a versatile PCET reagent, albeit with limited thermal stability. In MeCN solution, an orange emission for [1]PF 6 from a triplet-excited state was found. Density functional calculations and ultrafast absorption spectroscopy are used to give insight into the excited-state dynamics of the complex and suggest a significantly stretched S−S bond for the lowest triplet-state T 1 . The structural responsiveness of the disulfide unit is proposed to open an effective relaxation channel toward the ground state, explaining the unexpectedly short lifetime of [1] + . These insights as well as the quantitative ground-state thermochemistry data provide valuable information for the use of S−S bpy-functionalized complexes and their disulfide-/dithiol-directed PCET reactivity.

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“…The costs are negligible compared with the same-level QC calculation. 12,29 Thus, many studies have used ML potentials as a prominent accelerator for nonadiabatic molecular dynamics (NAMD) simulations, for instance, multiconfigurational time-dependent Hartree (MCTDH) 30 and trajectory surface hopping (TSH) 31 calculations. Several groups have developed ML mixed quantum−classical NAMD approaches (called ML photodynamics in this Account), such as MLAtom 32 with Newton-X 33 and SchNarc 34 with SHARC.…”

Section: Introductionmentioning

confidence: 99%

A Look Inside the Black Box of Machine Learning Photodynamics Simulations

Lopez

2022

Acc. Chem. Res.

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Metrics & MoreArticle Recommendations * sı Supporting Information CONSPECTUS: Photochemical reactions are of great importance in chemistry, biology, and materials science because they take advantage of a renewable energy source, mild reaction conditions, and high atom economy. Light absorption can excite molecules to a higher energy electronic state of the same spin multiplicity. The following nonadiabatic processes induce molecular transformations that afford exotic molecular architectures and high-energy-isomers that are inaccessible by thermal means. Computational simulations now complement time-resolved instrumentation to reveal ultrafast excited-state mechanistic information for photochemical reactions that is essential in disentangling elusive spectroscopic features, excitedstate lifetimes, and excited-state mechanistic critical points. Nonadiabatic molecular dynamics (NAMD), powered by surface hopping techniques, is among the most widely applied techniques to model the photochemical reactions of medium-sized molecules. However, the computational efficiency is limited because of the requisite thousands of multiconfigurational quantum-chemical calculations multiplied by hundreds of trajectories. Machine learning (ML) has emerged as a revolutionary force in computational chemistry to predict the outcome of the resource-intensive multiconfigurational calculations on the fly. An ML potential trained with a substantial set of quantum-chemical calculations can predict the energies and forces with errors under chemical accuracy at a negligible cost. The integration of ML potentials in NAMD dramatically extends the maximum simulation time scale by ∼10 000fold to the nanosecond regime.In this Account, we present a comprehensive demonstration of ML photodynamics simulations and summarize our most recent applications in resolving complex photochemical reactions. First, we address three fundamental components of ML techniques for photodynamics simulations: the quantum-chemical data set, the ML potential, and NAMD. Second, we describe best practices in building training data and our procedure toward training the ML photodynamics model with our recent literature contributions. We introduce a convenient training data generation scheme combining Wigner sampling and geometrical interpolation. It trains reliable and effective ML potentials suitable for subsequent active learning to detect undersampled data. We demonstrate how active learning automatically discovers new mechanistic pathways and reproduces experimental results. We point out that atomic permutation is an essential data augmentation approach to improve the learnability of distance-based molecular descriptors for highly symmetric molecules. Third, we demonstrate the utility of ML-photodynamics by showing the results of ML photodynamics simulations of (1) photo-torquoselective 4π disrotatory electrocyclic ring closing of norbornyl cyclohexadiene, which reveals a thermal conversion from experimentally unobserved intermediates to the reactant in 1 ns; (2) [2 + 2] ph...

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Surface Hopping Molecular Dynamics

Cited by 25 publications

References 141 publications

Nonadiabatic Excited-State Molecular Dynamics Methodologies: Comparison and Convergence

Nonadiabatic Excited-State Molecular Dynamics Methodologies: Comparison and Convergence

Luminescent Iridium Complexes with a Sulfurated Bipyridine Ligand: PCET Thermochemistry of the Disulfide Unit and Photophysical Properties

A Look Inside the Black Box of Machine Learning Photodynamics Simulations

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