Automating the generation of detailed kinetic models for halocarbon combustion with the Reaction Mechanism Generator

Automating the generation of detailed kinetic models for halocarbon combustion with the Reaction Mechanism Generator
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使用反应机制生成器自动生成卤化碳燃烧的详细动力学模型

DOI:
10.1016/j.proci.2022.07.204
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发表时间:
2023
影响因子:
3.4
通讯作者:
West, Richard H.
West, Richard H.
中科院分区:
工程技术1区
文献类型:
--
作者:
Farina, David S.;Sirumalla, Sai Krishna;West, Richard H.

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反应机理生成器(RMG)最初是为了通过自动生成详细的反应机理来预测碳氢化合物燃烧的化学动力学而开发的,它包含了C、H、O化学的大量热动力学数据,最近已扩展到氮和硫。在这项工作中,我们提出了添加卤素(氟,氯,溴)化学RMG,使自动生成详细的动力学模型的卤代烃燃烧。RMG现有的反应模板被更新,包括卤素,并创建了11个新的反应家族,具体到卤素化学。值得注意的是,超过1000个基元反应的动力学是通过从头算方法和过渡态理论计算的,这些动力学数据与文献来源的动力学相结合,以训练速率规则决策树估计器。此外,卤素基团被添加到RMG的统计力学数据库,使模型生成与RMG的压力依赖性模块和自动计算微正则速率常数的单分子网络。卤素基团也被纳入RMG的运输数据库,以提供估计参数的Lennard-Jones潜力,重要的运输相关的模拟,包括层流火焰速度。为了验证RMG预测卤化碳燃烧的能力,利用RMG建立了2-BTP(CH 2= CBrCF 3)在甲烷火焰中的火焰抑制模型.在各种反应条件下,RMG的2-BTP模型的层流火焰速度与已发表的模型显示出良好的一致性。自动生成卤化碳燃烧的详细动力学模型将有助于探索以前未探索的反应途径,从而加速开发更环保的制冷剂和抑制剂,并推进自动化机制生成领域。
Originally developed to predict the chemical kinetics of hydrocarbon combustion via automated generation of detailed reaction mechanisms, Reaction Mechanism Generator (RMG) contains extensive thermokinetic data for C, H, O chemisty, and has more recently been expanded to nitrogen and sulfur. In this work, we present the addition of halogen (fluorine, chlorine, and bromine) chemisty to RMG to enable automated generation of detailed kinetic models for halocarbon combustion. RMG’s existing reaction templates are updated to include halogens, and 11 new reactions families are created specific to halogen chemistry. Notably, kinetics for more than 1000 elementary reactions are calculated via ab inito methods and transition state theory, and these kinetic data are combined with kinetics from literature sources to train rate rule decision tree estimators. Additionally, halogen groups are added to RMG’s statistical mechanics database, enabling model generation with RMG’s pressure dependence module and automated computation of microcanonical rate constants for unimolecular networks. Halogen groups are also incorporated in RMG’s transport database to provide estimated parameters for the Lennard-Jones potential, important for transport-dependent simulations including laminar flame speeds. To demonstrate RMG’s capability for predicting halocarbon combustion, RMG is used to build a flame suppression model for 2-BTP (CH 2= CBrCF 3) in methane flames. The laminar flame speeds of RMG’s 2-BTP model show good agreement with a published model under a variety of reaction conditions. Automating the generation of detailed kinetic models for halocarbon combustion will facilitate the exploration of previously unexplored reaction pathways, thereby accelerating the development of greener refrigerants and suppressants, as well as advancing the field of automated mechanism generation.
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DOI: 10.1021/acs.iecr.1c03076
发表时间: 2021-10-22
影响因子: 4.2
作者:
Farina, David S., Jr.;Sirumalla, Sai Krishna;West, Richard H.
通讯作者: West, Richard H.