8 pags., 11 figs. ; We present a set of self-consistent cross sections for electron transport in gaseous tetrahydrofuran (THF), that refines the set published in our previous study [1] by proposing modifications to the quasielastic momentum transfer, neutral dissociation, ionisation and electron attachment cross sections. These adjustments are made through the analysis of pulsed-Townsend swarm transport coefficients, for electron transport in pure THF and in mixtures of THF with argon. To automate this analysis, we employ a neural network model that is trained to solve this inverse swarm problem for realistic cross sections from the LXCat project. The accuracy, completeness and self-consistency of the proposed refined THF cross section set is assessed by comparing the analyzed swarm transport coefficient measurements to those simulated via the numerical solution of Boltzmann’s equation. ; The authors gratefully acknowledge the financial support of the Australian Research Council through the Discovery Projects Scheme (Grant #DP180101655). JdeU thanks PAPIIT-UNAM, Project IN118520 for support. GG acknowledges support from the Spanish Ministerio de Ciencia, Innovacion y Universidades-MICIU (Projects FIS2016-80440 and PID2019-104727RB-C21) and CSIC (Project LINKA 20085).


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    Title :

    Self-consistent electron–THF cross sections derived using data-driven swarm analysis with a neural network model



    Publication date :

    2020-10-16



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




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