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Abstract
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.
Highlights
The prospect of chemical reaction engineering using atmospheric pressure plasmas is an increasingly attractive one
"Mathematical Graph Theory Operations on the Plasma Chemistry Graph" section tests the application of mathematical graph algorithms on a plasma chemical graph from an existing dataset [20] to gain useful information for the purposes of plasma chemical reaction engineering, with "Application of Dijkstra’s Shortest Path Algorithm: Relative Potential Reaction-Chain Rate Connectivity Matrix" section demonstrating the application of Dijkstra’s shortest path algorithm, and "Development of a Rudimentary Graph Algorithm for the Estimation of Optimal Condition Sequence for a Target Plasma Chemical Species" section detailing the development and operation of a novel algorithm for optimal condition proposal: Optimal Condition Approaching via Reaction-In-Network Analysis (OCARINA)
Whilst each of the applications need to be further investigated and developed, the results of this study suggest it may be possible to rapidly hone in on favourable conditions for plasma processes which can be tested via simulation or experiment
Summary
The prospect of chemical reaction engineering using atmospheric pressure plasmas is an increasingly attractive one. The wide range of species known to be present, speed with which the plasma energy can be altered, ability to attain high energy conditions without the need for expensive high pressure and temperature equipment, and the sheer abundance and availability of the “raw materials” (atmospheric gases, water, electrical energy and biomass) all justify the interest in this growing field [1, 2]. One problem that each solution must encounter, is the ever-expanding complexity of plasma chemical reaction schemes. The number of possible reactions in air alone can be in excess of 1800 reactions, with over 70 different species being present [13]. This will only increase with the need to simulate plasma reactions involving more complex chemicals and mixtures
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