Machine learning-assisted laser-induced breakdown spectroscopy for estimating substrate surface temperatures
Laser-induced breakdown spectroscopy has been used for detecting substrate surface temperatures with the assistance of machine learning.
Authors
- Haoyu Dong (ORCID: https://orcid.org/0009-0007-2645-9572)
- Bai Cui (ORCID: https://orcid.org/0000-0002-0585-6698)
- Xi Huang (ORCID: https://orcid.org/0000-0002-4477-3748)
- Jean‐François Silvain (ORCID: https://orcid.org/0000-0002-5881-6833)
- Peizi Li
- Yongfeng Lu (ORCID: https://orcid.org/0000-0002-5942-1999)
- Luke Wadle
Institutions
- University of Nebraska–Lincoln (US)
- Centre National de la Recherche Scientifique (FR)
- Université de Bordeaux (FR)
- Institut de Chimie de la Matière Condensée de Bordeaux (FR)
- Institut Polytechnique de Bordeaux (FR)
Publication Details
- Journal
- Journal of Analytical Atomic Spectrometry
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d4ja00437j
- Citations
- 1
- Primary Topic
- Laser-induced spectroscopy and plasma
- Type
- article
- Field-Weighted Citation Impact
- 0.86
Funders
- National Science Foundation
- U.S. Department of Energy
- Office of Nuclear Energy
- Office of the Under Secretary of Defense
- Idaho Operations Office, U.S. Department of Energy
- Division of Electrical, Communications and Cyber Systems
- Laboratory Directed Research and Development