Literature DB >> 27730243

Uncertainty quantification for quantum chemical models of complex reaction networks.

Jonny Proppe1, Tamara Husch1, Gregor N Simm1, Markus Reiher1.   

Abstract

For the quantitative understanding of complex chemical reaction mechanisms, it is, in general, necessary to accurately determine the corresponding free energy surface and to solve the resulting continuous-time reaction rate equations for a continuous state space. For a general (complex) reaction network, it is computationally hard to fulfill these two requirements. However, it is possible to approximately address these challenges in a physically consistent way. On the one hand, it may be sufficient to consider approximate free energies if a reliable uncertainty measure can be provided. On the other hand, a highly resolved time evolution may not be necessary to still determine quantitative fluxes in a reaction network if one is interested in specific time scales. In this paper, we present discrete-time kinetic simulations in discrete state space taking free energy uncertainties into account. The method builds upon thermo-chemical data obtained from electronic structure calculations in a condensed-phase model. Our kinetic approach supports the analysis of general reaction networks spanning multiple time scales, which is here demonstrated for the example of the formose reaction. An important application of our approach is the detection of regions in a reaction network which require further investigation, given the uncertainties introduced by both approximate electronic structure methods and kinetic models. Such cases can then be studied in greater detail with more sophisticated first-principles calculations and kinetic simulations.

Entities:  

Year:  2016        PMID: 27730243     DOI: 10.1039/c6fd00144k

Source DB:  PubMed          Journal:  Faraday Discuss        ISSN: 1359-6640            Impact factor:   4.008


  7 in total

Review 1.  Kinetic isotope effects and how to describe them.

Authors:  Konstantin Karandashev; Zhen-Hao Xu; Markus Meuwly; Jiří Vaníček; Jeremy O Richardson
Journal:  Struct Dyn       Date:  2017-12-13       Impact factor: 2.920

2.  Efficient prediction of reaction paths through molecular graph and reaction network analysis.

Authors:  Yeonjoon Kim; Jin Woo Kim; Zeehyo Kim; Woo Youn Kim
Journal:  Chem Sci       Date:  2017-12-12       Impact factor: 9.825

Review 3.  A Trajectory-Based Method to Explore Reaction Mechanisms.

Authors:  Saulo A Vázquez; Xose L Otero; Emilio Martinez-Nunez
Journal:  Molecules       Date:  2018-11-30       Impact factor: 4.411

4.  Uncertainty quantification in classical molecular dynamics.

Authors:  Shunzhou Wan; Robert C Sinclair; Peter V Coveney
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2021-03-29       Impact factor: 4.226

5.  Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis.

Authors:  Miguel Steiner; Markus Reiher
Journal:  Top Catal       Date:  2022-01-13       Impact factor: 2.910

6.  Uncertainty Quantification of Reactivity Scales.

Authors:  Jonny Proppe; Johannes Kircher
Journal:  Chemphyschem       Date:  2022-03-18       Impact factor: 3.520

7.  Towards theoretical spectroscopy with error bars: systematic quantification of the structural sensitivity of calculated spectra.

Authors:  Tobias G Bergmann; Michael O Welzel; Christoph R Jacob
Journal:  Chem Sci       Date:  2019-12-27       Impact factor: 9.825

  7 in total

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