An improved set of electron-THFA cross sections refined through a neural network-based analysis of swarm data

Stokes, P.W., Foster, S.P., Casey, M.J.E., Cocks, D.G., González-Magaña, O., de Urquijo, J., García, G., Brunger, M.J., and White, R. D. (2021) An improved set of electron-THFA cross sections refined through a neural network-based analysis of swarm data. Journal of Chemical Physics, 154. 084306.

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We review experimental and theoretical cross sections for electron transport in α-tetrahydrofurfuryl alcohol (THFA) and, in doing so, propose a plausible complete set. To assess the accuracy and self-consistency of our proposed set, we use the pulsed-Townsend technique to measure drift velocities, longitudinal diffusion coefficients, and effective Townsend first ionization coefficients for electron swarms in admixtures of THFA in argon, across a range of density-reduced electric fields from 1 to 450 Td. These measurements are then compared to simulated values derived from our proposed set using a multi-term solution of Boltzmann’s equation. We observe discrepancies between the simulation and experiment, which we attempt to address by employing a neural network model that is trained to solve the inverse swarm problem of unfolding the cross sections underpinning our experimental swarm measurements. What results from our neural network-based analysis is a refined set of electron-THFA cross sections, which we confirm is of higher consistency with our swarm measurements than that which we initially proposed. We also use our database to calculate electron transport coefficients in pure THFA across a range of reduced electric fields from 0.001 to 10000 Td.

Item ID: 70519
Item Type: Article (Research - C1)
ISSN: 1089-7690
Copyright Information: © 2021 Author(s). This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in J. Chem. Phys. 154, 084306 (2021) and may be found at
Date Deposited: 31 Mar 2022 03:28
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