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Graph Theory Applied to Plasma Chemical Reaction Engineering
Plasma Chemistry and Plasma Processing ( IF 3.6 ) Pub Date : 2021-01-19 , DOI: 10.1007/s11090-021-10152-z
Thomas D. Holmes , Rachael H. Rothman , William B. Zimmerman

This work explores the following applications of graph theory to plasma chemical reaction engineering: assembly of a weighted directional graph with the key addition of reaction nodes, from a published set of reaction data for air; graph visualisation for probing the reaction network for potentially useful or problematic reaction pathways; running Dijkstra’s algorithm between all species nodes; further analysis of the graph for useful engineering information such as which conditions, reactions, or species could be enhanced or supressed to favour particular outcomes, e.g. targeted chemical formation. The use of reaction-nodes combined with derived parameters allowed large amounts of key information regarding the plasma chemical reaction network to be assessed simultaneously using a leading open source graph visualisation software (Gephi). A connectivity matrix of Dijkstra’s algorithm between each two species gave a measure of the relative potential of species to be created and destroyed under specific conditions. Further investigation into using the graph for key reaction engineering information led to the development of a graph analysis algorithm to quantify demand for conditions for targeted chemical formation: Optimal Condition Approaching via Reaction-In-Network Analysis (OCARINA). Predictions given by running OCARINA display significant similarities to a well-known electric field strength regime for optimal ozone production in air. Time dependent 0D simulations also showed preferential formation for O· and O3 using the respective conditions generated by the algorithm. These applications of graph theory to plasma chemical reaction engineering show potential in identifying promising simulations and experiments to devote resources.

中文翻译:

图论在等离子体化学反应工程中的应用

这项工作探索了图论在等离子体化学反应工程中的以下应用:从一组已发布的空气反应数据中组装加权方向图,并添加关键的反应节点;用于探索反应网络中潜在有用或有问题的反应途径的图形可视化;在所有物种节点之间运行 Dijkstra 算法;进一步分析图表以获得有用的工程信息,例如可以增强或抑制哪些条件、反应或物种以支持特定结果,例如目标化学形成。使用反应节点与派生参数相结合,可以使用领先的开源图形可视化软件 (Gephi) 同时评估有关等离子体化学反应网络的大量关键信息。每两个物种之间的 Dijkstra 算法的连接矩阵给出了在特定条件下创建和破坏物种的相对潜力的度量。进一步研究使用图表获取关键反应工程信息导致了图表分析算法的开发,以量化目标化学形成条件的需求:通过网络反应分析 (OCARINA) 进行最佳条件逼近。通过运行 OCARINA 给出的预测显示出与众所周知的用于空气中最佳臭氧产生的电场强度机制的显着相似之处。时间相关的 0D 模拟还显示了 O· 和 O3 使用算法生成的相应条件的优先形成。
更新日期:2021-01-19
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