2017
DOI: 10.1088/1361-6455/aa640b
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Predicting differential cross sections of electron scattering from tetrahydrofuran

Abstract: A difference algebraic converging method for electron scattering from molecule (DACMe) is suggested based on the recently proposed difference converging method (DCM) to predict unknown differential cross sections (DCSs). The applications of the DACMe to electron scattering from tetrahydrofuran (THF) molecule at energies below 20 eV show that: (1) the DACMe DCSs excellently reproduce all the available experimental data; (2) the DACMe method correctly predicts unknown DCSs that may not be given experimentally; (… Show more

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Cited by 7 publications
(10 citation statements)
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References 29 publications
(93 reference statements)
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“…[1], as shown in Figure 3, and as such agrees reasonably well with the experimental and calculated cross sections of Coyler et al [18], Gauf et al [22], Baek et al [16], Dampc et al [19], and Zhang et al [23]. At very low energies, below 10 −2 eV, the neural network predicts a roughly constant quasielastic MTCS that is about 10% smaller in magnitude compared to that of the de Urquijo et al counterpart in the same energy regime.…”
Section: Quasielastic Momentum Transfer Cross Sectionsupporting
confidence: 86%
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“…[1], as shown in Figure 3, and as such agrees reasonably well with the experimental and calculated cross sections of Coyler et al [18], Gauf et al [22], Baek et al [16], Dampc et al [19], and Zhang et al [23]. At very low energies, below 10 −2 eV, the neural network predicts a roughly constant quasielastic MTCS that is about 10% smaller in magnitude compared to that of the de Urquijo et al counterpart in the same energy regime.…”
Section: Quasielastic Momentum Transfer Cross Sectionsupporting
confidence: 86%
“…In these regimes of very small or very large energies, it is thus expected that the neural network would rely more 8Self-consistent electron-THF cross sections derived using data-driven swarm analysis with a neural network model Figure 3. Previous quasielastic momentum transfer cross sections [1,16,18,19,22,23], compared to that determined from our neural network regression approach.…”
Section: Machine-fitted Thf Cross Sectionsmentioning
confidence: 99%
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“…IV B 3. This cross section is compared with the cross section of I and Garland et al 1 (elastic only), and the measurements and calculations of Fuss et al 24 with and without rotations, Swadia et al, 25,26 Colyer et al, 80 Gauf et al, 81 Baek et al, 82 Dampc et al, 83 Bug et al, 20 and Zhang et al 84 measured under any experimental conditions that can be simulated. Using the cross section set developed in I, we have calculated the transport coefficients of interest in mixtures of THF with argon and N 2 .…”
Section: Comparison Of Transport Coefficients For the Thf Admixturesmentioning
confidence: 99%
“…FIG. 3.The proposed quasielastic momentum-transfer cross section for electron impact on THF, compared with the cross section of I, the (elastic only) estimate of Garland et al1 and the experimental cross sections of Colyer et al,80 Gauf et al,81 Baek et al,82 Dampc et al,83 and Zhang et al84 (the dots based on Dampc et al and the square based on Colyer et al).…”
mentioning
confidence: 97%