Comparison of machine learning techniques to optimize the analysis of plutonium surrogate material via a portable LIBS device

Abstract

Enhancing the analytical capabilities of a hand-held LIBS device for chemical composition analysis of a plutonium surrogate using different machine learning paradigms.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2021
Source ID
10.1039/d0ja00435a

Entities

People

  • Ashwin P. Rao
  • J D Auxier
  • Michael B Shattan
  • Phillip R. Jenkins

Organizations

  • Air Force Institute of Technology
  • Air Force Office of Scientific Research
  • Defense Threat Reduction Agency
  • Los Alamos National Laboratory
  • United States Army

Tags

Fields of Study

  • Physics

Readers

  • Distributed Systems and Data Platform Development
  • Environmental Engineering.
  • Instructional Design and Training Evaluation.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks