Context-Driven Exploration of Complex Chemical Reaction Networks

Hernández-Lobato, José Miguel; Reiher, Markus

doi:10.1021/acs.jctc.7b00945

Cited by 113 publications

(158 citation statements)

References 116 publications

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“…When studying a complex network of reactions, TST is commonly used to obtain a rate for the many possible reaction steps. 79 By evaluating the crossover temperature for each step, it can be easily determined whether tunnelling is likely to play a role, and instanton calculations can be run for these steps only. As there are typically many more steps for which tunnelling is not important, than those for which it is, the number of ab initio calculations needed for the instanton calculations would be small in comparison to the overall total.…”

Section: Discussionmentioning

confidence: 99%

Ab initio instanton rate theory made efficient using Gaussian process regression

et al. 2018

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Ab initio instanton rate theory is a computational method for rigorously including tunnelling effects into the calculations of chemical reaction rates based on a potentialenergy surface computed on the fly from electronic-structure theory. This approach is necessary to extend conventional transition-state theory into the deep-tunnelling regime, but it is also more computationally expensive as it requires many more ab initio calculations. We propose an approach which uses Gaussian process regression to fit the potential-energy surface locally around the dominant tunnelling pathway. The method can be converged to give the same result as from an on-the-fly ab initio instanton calculation but it requires far fewer electronic-structure calculations. This makes it a practical approach for obtaining accurate rate constants based on high-level electronic-structure methods. We show fast convergence to reproduce benchmark H + CH 4 results and evaluate new low-temperature rates of H + C 2 H 6 in full dimensionality at a UCCSD(T)-F12b/cc-pVTZ-F12 level.

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Section: Discussionmentioning

confidence: 99%

Ab initio instanton rate theory made efficient using Gaussian process regression

et al. 2018

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“…The protocol described so far was implemented into our program package Chemoton and carried out in a fully automated fashion. Icosahedral meshes were generated with the C++ library OpenMesh .…”

Section: Computational Detailsmentioning

confidence: 99%

“…However, as the configuration space can become very large, computational costs of carrying out first‐principles calculations grow rapidly. As a result, they cannot be performed for every intermediate in large reaction networks . This issue can be overcome by the application of a reactive force‐field .…”

Section: Introductionmentioning

confidence: 99%

Systematic microsolvation approach with a cluster‐continuum scheme and conformational sampling

2020

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Solvation is a notoriously difficult and nagging problem for the rigorous theoretical description of chemistry in the liquid phase. Successes and failures of various approaches ranging from implicit solvation modeling through dielectric continuum embedding and microsolvated quantum chemical modeling to explicit molecular dynamics highlight this situation. Here, we focus on quantum chemical microsolvation and discuss an explicit conformational sampling ansatz to make this approach systematic. For this purpose, we introduce an algorithm for rolling and automated microsolvation of solutes. Our protocol takes conformational sampling and rearrangements in the solvent shell into account. Its reliability is assessed by monitoring the evolution of the spread and average of the observables of interest.

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“…(Note that this implies 1, 000 conformers to be generated and 10, 000 elementary steps to be calculated.) The challenges of the visualization and analysis of such an amount of data and the transferability of sub-spaces of the network have only been touched upon (23,24). Overall, however, important developments have been accomplished and key steps haven been taken (see Sec.…”

Section: Assessment Of the Current Statusmentioning

confidence: 99%