An artificial neural network approach to laser-induced breakdown spectroscopy quantitative analysis

Abstract

The usual approach to laser-induced breakdown spectroscopy (LIBS) quantitative analysis is based on the use of calibration curves, suitably built using appropriate reference standards. More recently, statistical methods relying on the principles of artificial neural networks (ANN) are increasingly used. However, ANN analysis is often used as a 'black box' system and the peculiarities of the LIBS spectra are not exploited fully. An a priori exploration of the raw data contained in the LIBS spectra, carried out by a neural network to learn what are the significant areas of the spectrum to be used for a subsequent neural network delegated to the calibration, is able to throw light upon important information initially unknown, although already contained within the spectrum. This communication will demonstrate that an approach based on neural networks specially taylored for dealing with LIBS spectra would provide a viable, fast and robust method for LIBS quantitative analysis. This would allow the use of a relatively limited number of reference samples for the training of the network, with respect to the current approaches, and provide a fully automatizable approach for the analysis of a large number of samples

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a ‘black box’ approach and how to avoid them

“…It is thus clear that using the Matlab® defaults for the number of neurons in the hidden layer would only increase the risk of overfitting. In fact, the proper optimization of the network would imply a series of tests varying of the number of hidden neurons [25]. This procedure is time-consuming, and totally empirical.…”

Atomic spectrometry update: review of advances in atomic spectrometry and related techniques

“…Furthermore, D'Andrea et al 111 developed an approach based on ANN for LIBS quantitative analysis. Nevertheless, strong matrix effects can degrade the precision and accuracy.…”

Hackem-LIBS: An Heterogeneous Stacking Ensemble Model for Laser-Induced Breakdown Spectroscopy Elemental Quantitative Analysis

“…Once the calibration curve is obtained, we can easily determine the concentration of target element given the spectral intensity of its emission peak. Due to its simplicity, the Calibration Curve Model gains increasing popularity in LIBS analysis, however, the plasma fluctuation and the problem of self-absorption and matrix effects usually lead to unsatisfactory determination results [3][4][5][6][7][8][9].…”