Optimization of partial-least-square regression for determination of manganese in low-alloy steel by single-shot laser-induced breakdown spectroscopy

Shunsuke Kashiwakura, Kazuaki Wagatsuma

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Laser-induced breakdown spectroscopy (LIBS) is employed for ultra-high-speed determination of the manganese content in various steel specimens. LIBS is widely known as a method for elemental analysis with a rapid response. It has several advantages such that it can work under ambient pressure, and that specimens can be tested without any pre-treatment such as acid digestion, cleaning, or polishing of surface of the specimens. We applied a laboratory-build LIBS system for the determination of Mn in a series of low-alloy steel certified reference materials by a multivariate analysis using partial-least-square regression. Considering enough intensities of Mn emission lines and spectral interferences from emission lines of the iron matrix in these alloys, two wavelength ranges for the spectrograph could be employed. By minimizing the predicted residual sum of squares and the root mean square error of prediction, the analytical result of the Mn concentrations could be obtained with reasonable accuracy and precision.

Original languageEnglish
Pages (from-to)1705-1710
Number of pages6
JournalIsij International
Volume58
Issue number9
DOIs
Publication statusPublished - 2018 Sep 15

Keywords

  • LIBS
  • Low alloy steel
  • Mn
  • PLS regression

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering
  • Metals and Alloys
  • Materials Chemistry

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