First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis

Xu, Rui; Meisner, Jan; Chang, Alexander M.; Thompson, Keiran C.; Martínez, Todd J.

doi:10.1039/d3sc01202f

First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis

Journal Article · Fri Jun 09 00:00:00 EDT 2023 · Chemical Science

DOI:https://doi.org/10.1039/d3sc01202f· OSTI ID:1995997

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Stanford University, CA (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); SLAC
Stanford University, CA (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Heinrich Heine University, Düsseldorf (Germany)
Stanford University, CA (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)

Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of the methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling.

View Accepted Manuscript (DOE)

Research Organization:: SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)

Sponsoring Organization:: US Department of the Navy, Office of Naval Research (ONR); USDOE

Grant/Contract Number:: AC02-76SF00515

OSTI ID:: 1995997

Journal Information:: Chemical Science, Journal Name: Chemical Science Journal Issue: 27 Vol. 14; ISSN 2041-6520

Publisher:: Royal Society of ChemistryCopyright Statement

Country of Publication:: United States

Language:: English

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