Isotopic Analysis of Lithium Hydroxide Monohydrate Using Laser-Induced Breakdown Self-Reversal Isotopic Spectrometry (LIBRIS) and Machine Learning

Author

• Madison R. Moran, Air Force Institute of Technology

Date of Award

3-2025

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Engineering Physics

First Advisor

Anik K. Patnaik, PhD

Abstract

High-resolution Laser-Induced Breakdown Self-Reversal Isotopic Spectrometry (LIBRIS) is implemented to record the 15.8 pm Li I 670.8 nm isotopic shift in LiOH · H₂O samples of varying 6, 7Li abundance. A simple univariate linear regression demonstrates an acquired isotopic shift of 13.813 ± 1.21 pm in samples varying from 3 to 95 ⁶Li at%. Supervised machine learning regressions are trained on self-reversal wavelength locations in order to quantify ⁶Li abundance. A stacked ensemble using two base learners yields the superlative characterization of 6Li abundance with RMSE of 5.66 at% and detection limit of 18.8 at%. Using LIBRIS under ambient pressure simplifies the experimental parameters to mimic the conditions of in-situ Li analysis. Combining LIBRIS with advanced machine learning models yields better accuracy and sensitivity than traditional chemometric analysis.

AFIT Designator

AFIT-ENP-MS-25-M-221

DTIC Accession Number

AD1356662

Comments

An embargo was observed for posting this graduate work on AFIT Scholar.  Approved for public release, distribution unlimited. PA case number 88ABW-2025-0302.

Recommended Citation

Moran, Madison R., "Isotopic Analysis of Lithium Hydroxide Monohydrate Using Laser-Induced Breakdown Self-Reversal Isotopic Spectrometry (LIBRIS) and Machine Learning" (2025). Theses and Dissertations. 8299.
https://scholar.afit.edu/etd/8299