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Extracting Reaction Kinetics for Complex Reaction Systems

Goddard, William A., III (2021) Extracting Reaction Kinetics for Complex Reaction Systems. In: Computational Materials, Chemistry, and Biochemistry: From Bold Initiatives to the Last Mile. Springer Series in Materials Science. No.284. Springer International Publishing , Cham, pp. 1097-1108. ISBN 978-3-030-18777-4. https://resolver.caltech.edu/CaltechAUTHORS:20210127-073755455

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Abstract

A valuable aspect of reactive MD is to provide rate constants of complex reactions. We give some examples for cases of detonation and pyrolysis. For the general case we need a good machine learning model to collect together the reactions at any one temperature so that we can extract rate constants. Since a reactive force field such as ReaxFF, describes all possible reactions of a system, it could be the basis for general approaches to extract the fundamental kinetic parameters to describe combustion (say of diesel full, gasoline, or JP-10 Hydrocarbon Jet Fuel) or shock-induced decompositions. Although great progress has been achieved in first principles modeling of low-pressure gas-phase reactions, it has been difficult to provide first principles predictions of Combustion and Shock processes for condensed phases. We will discuss several activities we have been pursuing to accomplish this.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-3-030-18778-1_49DOIArticle
ORCID:
AuthorORCID
Goddard, William A., III0000-0003-0097-5716
Additional Information:© Springer Nature Switzerland AG 2021. First Online: 26 January 2021.
Other Numbering System:
Other Numbering System NameOther Numbering System ID
WAG1444
Series Name:Springer Series in Materials Science
Issue or Number:284
DOI:10.1007/978-3-030-18778-1_49
Record Number:CaltechAUTHORS:20210127-073755455
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210127-073755455
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107750
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:27 Jan 2021 18:44
Last Modified:16 Nov 2021 19:06

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