A1 Journal article (refereed)
Optimization of spodumene identification by statistical approach for laser-induced breakdown spectroscopy data of lithium pegmatite ores (2023)

Romppanen, S., Pölönen, I., Häkkänen, H., & Kaski, S. (2023). Optimization of spodumene identification by statistical approach for laser-induced breakdown spectroscopy data of lithium pegmatite ores. Applied Spectroscopy Reviews, 58(5), 297-317. https://doi.org/10.1080/05704928.2021.1963977

JYU authors or editors

Publication details

All authors or editors: Romppanen, Sari; Pölönen, Ilkka; Häkkänen, Heikki; Kaski, Saara

Journal or series: Applied Spectroscopy Reviews

ISSN: 0570-4928

eISSN: 1520-569X

Publication year: 2023

Publication date: 17/08/2021

Volume: 58

Issue number: 5

Pages range: 297-317

Publisher: Taylor & Francis

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1080/05704928.2021.1963977

Publication open access: Not open

Publication channel open access: Channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/78680

Abstract

Mapping with laser-induced breakdown spectroscopy (LIBS) can offer more than just the spatial distribution of elements: the rich spectral information also enables mineral recognition. In the present study, statistical approaches were used for the recognition of the spodumene from lithium pegmatite ores. A broad spectral range (280–820 nm) with multiple lines was first used to establish the methods based on vertex component analysis (VCA) and K-means and DBSCAN clusterings. However, with a view to potential on-site applications, the dimensions of the datasets must be reduced in order to accomplish fast analysis. Therefore, the capability of the methods in mineral identification was tested with a limited spectral range (560–815 nm) using Li-pegmatites with various mineralogical characters.

Keywords: minerals; ore minerals; pegmatites; lithium; elementary analysis; spectroscopy; optimisation; statistical methods

Free keywords: lithium pegmatite ore; LIBS; VCA; K-means; DBSCAN

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2022

JUFO rating: 1