Real wavepacket code for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:mi mathvariant="normal">ABC</mml:mi><mml:mo>+</mml:mo><mml:mi mathvariant="normal">D</mml:mi><mml:mo>→</mml:mo><mml:mi mathvariant="normal">AB</mml:mi><mml:mo>+</mml:mo><mml:mi mathvariant="normal">CD</mml:mi></mml:math> reactive scattering

Mayneris, Jordi; González, Miguel; Gray, Stephen K.

doi:10.1016/j.cpc.2008.09.005

Cited by 19 publications

(3 citation statements)

References 41 publications

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“…This already makes clear that a realistic representation of this object

V ((), \overset{false\to}{x})

, where

\overset{x}{true}

is a 3 N dimensional vector containing all Cartesian coordinates, is a formidable undertaking. Following the dynamics on the PES is either done based on Newtonian mechanics (“molecular dynamics simulations”) or by solving the time‐independent or time‐dependent Schrödinger equation (SE) for a quantum mechanical approach. In recent years, path‐integral‐based approaches and variants thereof have also been explored.…”

Section: Introductionmentioning

confidence: 99%

Reactive molecular dynamics: From small molecules to proteins

Meuwly

2018

WIREs Comput Mol Sci

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The current status of reactive molecular dynamics (MD) simulations is summarized. Both, methodological aspects and applications to problems ranging from gas phase reaction dynamics to ligand‐binding in solvated proteins are discussed, focusing on extracting information from simulations that cannot easily be obtained from experiments alone. One specific example is the structural interpretation of the ligand rebinding time scales extracted from state‐of‐the art time‐resolved experiments. Atomistic simulations employing validated reactive interaction potentials are capable of providing structural information about the time scales involved. Both, merits and shortcomings of the various methods are discussed and the outlook summarizes possible future avenues such as reactive potentials based on machine learning techniques. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Theoretical and Physical Chemistry > Reaction Dynamics and Kinetics Molecular and Statistical Mechanics > Molecular Interactions

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“…This already makes clear that a realistic representation of this object

V ((), \overset{false\to}{x})

, where

\overset{x}{true}

Section: Introductionmentioning

confidence: 99%

Reactive molecular dynamics: From small molecules to proteins

Meuwly

2018

WIREs Comput Mol Sci

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“…Lots of new mechanistic effects appear in polyatomic reactions, such as bond selectivity, mode specificity and multiple reaction pathways. The first extensions to treat four-atom systems also used time-independent approaches [15][16][17][18], but the superior scaling of the wave packet approach with basis set size (in particular, the linear scaling with increase in the total angular momentum) means that the majority of attempts to calculate accurate cross sections and rates used time-dependent methods [19][20][21][22][23][24][25][26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

State-to-state reactive scattering using reactant–product decoupling

Cvitaš

Althorpe

2009

Phys. Scr.

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In this paper, we review a quantum wave packet method for computing state-to-state quantum dynamics of three-atom and four-atom bimolecular reactions using the reactant–product decoupling (RPD) approach. The long propagation times needed in order to extract state-to-state observables cover geometries at which the fragments are far apart on the reactant and product side of the reaction valley. To alleviate the coordinate problem, we partition the coordinate space into three regions, describing reactants, products and the interaction region each using a basis set optimized for the particular region. The wave packet is propagated simultaneously over all three regions, and it is transferred between the regions using a system of artificial reflecting and absorbing potentials. We review the accuracy and efficiency of the method and comment on its prospects for yielding accurate differential cross sections of four-atom reactions in the near future.

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“…This already makes clear that a realistic representation of this object V( x), where x is a 3N dimensional vector containing all Cartesian coordinates, is a formidable undertaking [14,15]. Following the dynamics on the PES is either done based on Newtonian mechanics [16] ('molecular dynamics simulations') or by solving the time-independent [17] or time-dependent [18,19] Schrödinger equation for a quantum mechanical approach. In recent years, path-integral-based approaches and variants thereof [20] have also been explored to sample configurational space [21][22][23].…”

mentioning

confidence: 99%

Reactive molecular dynamics for the [Cl–CH₃–Br]⁻reaction in the gas phase and in solution: a comparative study using empirical and neural network force fields

Brickel¹,

Das²,

Unke³

et al. 2019

Electron. Struct.

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Understanding atomistic and molecular aspects of chemical reactions is one of the cornerstones in chemistry and biology. Characterizing reactions in time and space is challenging due to the different length-and time-scales on which the nuclear dynamics takes place [1]. For example, typical reaction times for the Claisen rearrangement [2] in solution are on the order of seconds [3] or milliseconds (in the protein) [4]. However, the chemical step (i.e. C-C bond formation and C-O bond breaking) [5] occurs on the femtosecond time scale. In other words, during 10 9 to 10 15 vibrational periods energy is redistributed in the system until sufficient energy has accumulated along the relevant 'progression coordinate' for the reaction to occur. Because the 'chemical step' is so rapid and the system concentration at the transition state is negligible, direct experimental characterization of the transition state and the dynamics between reactant and product is extremely challenging even with current state-of-the art methods, including NMR, [6] IR, [7] or x-ray [8,9] spectroscopies.Atomistic simulations have shown to provide molecular-level insight into the energetics and dynamics of chemical reactions for systems ranging from small (triatomic) molecules to proteins in the condensed phase [1,[10][11][12][13]]. An essential requirement for a meaningful contribution of computer-based work to characterize chemical reactions is a correct description of the intermolecular interactions along the entire reaction path including the degrees of freedom orthogonal to it. This involves regions around the reactants, products and the transition state(s). Intermolecular interactions in molecular systems are often represented as a Born-Oppenheimer

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Real wavepacket code for ABC+D→AB+CD reactive scattering

Cited by 19 publications

References 41 publications

Reactive molecular dynamics: From small molecules to proteins

Reactive molecular dynamics: From small molecules to proteins

State-to-state reactive scattering using reactant–product decoupling

Reactive molecular dynamics for the [Cl–CH₃–Br]⁻reaction in the gas phase and in solution: a comparative study using empirical and neural network force fields

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Real wavepacket code for ABC+D→AB+CD reactive scattering

Cited by 19 publications

References 41 publications

Reactive molecular dynamics: From small molecules to proteins

Reactive molecular dynamics: From small molecules to proteins

State-to-state reactive scattering using reactant–product decoupling

Reactive molecular dynamics for the [Cl–CH3–Br]−reaction in the gas phase and in solution: a comparative study using empirical and neural network force fields

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Reactive molecular dynamics for the [Cl–CH₃–Br]⁻reaction in the gas phase and in solution: a comparative study using empirical and neural network force fields