Simulating the Feasibility of Using Liquid Micro-Jets for Determining Electron–Liquid Scattering Cross-Sections

Dale L. Muccignat, Peter W. Stokes, Daniel G. Cocks, Jason R. Gascooke, Darryl B. Jones, Michael J. Brunger, Ronald D. White

Research output: Contribution to journalArticlepeer-review

Abstract

The extraction of electron–liquid phase cross-sections (surface and bulk) is proposed through the measurement of (differential) energy loss spectra for electrons scattered from a liquid micro-jet. The signature physical elements of the scattering processes on the energy loss spectra are highlighted using a Monte Carlo simulation technique, originally developed for simulating electron transport in liquids. Machine learning techniques are applied to the simulated electron energy loss spectra, to invert the data and extract the cross-sections. The extraction of the elastic cross-section for neon was determined within 9% accuracy over the energy range 1–100 eV. The extension toward the simultaneous determination of elastic and ionisation cross-sections resulted in a decrease in accuracy, now to within 18% accuracy for elastic scattering and 1% for ionisation. Additional methods are explored to enhance the accuracy of the simultaneous extraction of liquid phase cross-sections.

Original languageEnglish
Article number3354
Number of pages25
JournalInternational Journal of Molecular Sciences
Volume23
Issue number6
DOIs
Publication statusPublished - 2 Mar 2022

Keywords

  • Cross-section
  • Electron
  • Liquid microjet
  • Machine learning
  • Monte Carlo

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