Principal component-generalized spectrum-machine learning approach for quantifying gallium in a surrogate plutonium matrix using LIBS
Year: 2025
Type: article
Source: Applied Optics
DOI: 10.1364/ao.554537
Authors: Ashwin P. Rao, Anil K. Patnaik
Institution: U.S. Air Force Institute of Technology
Language: English
Subfield: Mechanics of Materials
Field: Engineering
Domain: Physical Sciences
Open Access status: closed
Funder: Defense Threat Reduction Agency
OpenAlex ID: W4408453509