Bulletin of the American Physical Society
75th Annual Gaseous Electronics Conference
Volume 67, Number 9
Monday–Friday, October 3–7, 2022;
Sendai International Center, Sendai, Japan
The session times in this program are intended for Japan Standard Time zone in Tokyo, Japan (GMT+9)
Session GF1: Dissociative Electron Attachment and Distribution Functions |
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Chair: Mariusz Piwiński, Institute of Physics, NCU Room: Sendai International Center Shirakashi 2 |
Friday, October 7, 2022 8:00AM - 8:30AM |
GF1.00001: Dissociative Electron Attachment to Amides Invited Speaker: Sylwia Ptasinska A comprehensive picture of the quantum phenomena of electron scattering is essential for the characterization and control of molecular systems driven by low-energy impacts that are elementary and important processes not only in radiation-induced chemical reactions but also in other areas, such as the processing of materials, energy flow in molecular systems, and biochemical transformations. At low energy of electrons, dissociative electron attachment (DEA) is a key process involved in the physical and chemical modifications of any target affected by electron interactions. My group conducted a series of experimental studies of gas-phase DEA measurements of compounds with the peptide bond linkage to model proteins, and we considered several reaction channels responsible for damage to these compounds [1]. We focused on gas-phase amides with increasing complexity, ranging from the simplest amide, formamide, to more complex species such as N-ethylformamide and N-ethylacetamide [2,3], to reveal the nature of amide bond cleavage through the DEA process. The location of different resonant states and their corresponding dissociation channels were identified, and with the assistance of quantum chemistry calculations, threshold energies for each dissociation channel were obtained for all studied compounds. Moreover, our results indicated that in all these molecules, the dissociation of the amide bond results in a double resonant structure with peaks at approximately 5 and 9 eV. Interestingly, such resonant structures for corresponding fragments were also observed in gas-phase peptides. This common finding implies the fundamental characteristic for breakage of the amide bond and is particularly important to formulating a general mechanism for molecular dissociation. |
Friday, October 7, 2022 8:30AM - 8:45AM |
GF1.00002: An Analytic Electron-Impact Ionization Anisotropic Scattering Model for Monte Carlo Plasma and Swarm Applications Mark C Zammit, James Colgan, Ryan Park, Christopher J Fontes, Brett S Scheiner, Eddy M Timmermans, Xianzhu Tang, Nathan Garland Modeling non-equilibrium plasmas or swarm experiments with Monte Carlo collision codes or Boltzmann equation solver codes requires input of comprehensive sets of collision cross sections and or scattering models. However, scattering models utilized for the ionization anisotropic scattering process have generally not been validated against theory or measurements.
Recently we have developed an analytic model for calculating the electron-impact ionization anisotropic angular scattering distribution functions, which can be readily implemented in Monte Carlo simulation codes. Here we present our approach and compare the model to generally utilized scattering models and accurate time-dependent close-coupling scattering calculations. |
Friday, October 7, 2022 8:45AM - 9:00AM |
GF1.00003: Electron Energy Deposition in Molecular Hydrogen : A Simulation Using Molecular Convergent Close Coupling Cross Sections Reese K Horton, Liam H Scarlett, Mark C Zammit, Igor Bray, Dmitry V Fursa We report on the development of a Monte-Carlo simulation of electron energy deposition in a gas of molecular hydrogen. The simulation was produced to use a self-consistent data set generated using a single theoretical method, making use of accurate Molecular Convergent Close Coupling (MCCC) cross sections. The work also demonstrates the viability of a new method for modelling excitations to target continuum states as part of energy deposition simulations. The simulation was benchmarked in an ab-initio calculation of the mean energy per ion pair, yielding excellent agreement with experiment and previous theoretical work. Finally, the simulation was used to examine molecular dissociation effects in the energy deposition process, with the new method being used to produce a model fully resolved in both the bound and dissociative vibrational states of the hydrogen molecule. |
Friday, October 7, 2022 9:00AM - 9:15AM |
GF1.00004: A General Analytic Electron-Impact Ionization Electron Energy Sharing Model for Monte Carlo Plasma and Swarm Applications Mark C Zammit, Ryan Park, Brett S Scheiner, James Colgan, Christopher J Fontes, Eddy M Timmermans, Xianzhu Tang, Nathan Garland Modeling non-equilibrium plasmas or swarm experiments with Monte Carlo collision codes or Boltzmann equation solver codes requires input of comprehensive sets of collision cross sections and or scattering models. Of particular interest are the scattering models utilized for the ionization process, where detailed angle and energy resolved cross sections are generally not available in the literature.
Recently we have developed a general analytic model for calculating the electron-impact ionization electron energy sharing distribution function, which can be readily implemented in Monte Carlo simulation codes. Here we present our approach and show the utility of the model for a range of impact energies, species, ions, and excited states, by comparing the analytic model to accurate close-coupling and distorted-wave scattering calculations. We compare this approach to scattering models generally utilized by Boltzmann equation solver and collisional Monte Carlo codes, e.g. the commonly used model of C. B. Opal et al. J. Chem. Phys. 55, 4100 (1971), the equal-energy sharing approximation, and approximating the primary electron to take all of the excess energy. We note that unlike the commonly used approach of Opal, the present analytic model is applicable to all species, requires minimal input data from the user, and does not rely on experimentally determined parameters. |
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