A review of artificial neural network based chemometrics applied in laser-induced breakdown spectroscopy analysis

LN Li, XF Liu, F Yang, WM Xu, JY Wang… - Spectrochimica Acta Part B …, 2021 - Elsevier
In the past decades various categories of chemometrics for laser-induced breakdown
spectroscopy (LIBS) analysis have been developed, among which an important category is …

Catching up on calibration-free LIBS

F Poggialini, B Campanella, B Cocciaro… - Journal of Analytical …, 2023 - pubs.rsc.org
This review paper will present and critically discuss the evolution of the calibration-free LIBS
(CF-LIBS) method and some of its new applications that appeared since the last extensive …

A hybrid calibration-free/artificial neural networks approach to the quantitative analysis of LIBS spectra

E D'Andrea, S Pagnotta, E Grifoni, S Legnaioli… - Applied Physics B, 2015 - Springer
A 'hybrid'method is proposed for the quantitative analysis of materials by LIBS, combining
the precision of the calibration-free LIBS (CF-LIBS) algorithm with the quickness of artificial …

Classification of wrought aluminum alloys by Artificial Neural Networks evaluation of Laser Induced Breakdown Spectroscopy spectra from aluminum scrap samples

B Campanella, E Grifoni, S Legnaioli… - … Acta Part B: Atomic …, 2017 - Elsevier
Every year throughout the world> 50 million vehicles reach the end of their life, producing
millions of tons of automotive waste. The current strategies for the separation of the non …

CF-LIBS analysis of frozen aqueous solution samples by using a standard internal reference and correcting the self-absorption effect

F de Oliveira Borges, JU Ospina… - Journal of Analytical …, 2018 - pubs.rsc.org
The aim of this paper is to present an innovative procedure to determine the composition of
a liquid sample using Laser Induced Breakdown Spectroscopy without calibration curves, or …

ANN-LIBS analysis of mixture plasmas: detection of xenon

H Saeidfirozeh, AK Myakalwar, P Kubelík… - Journal of Analytical …, 2022 - pubs.rsc.org
We developed an artificial neural network method for characterising crucial physical plasma
parameters (ie, temperature, electron density, and abundance ratios of ionisation states) in a …

Modeling temporal and spatial evolutions of laser-induced plasma characteristics by using machine learning algorithms

AN Bakhtiyari, Y Wu, D Qi, H Zheng - Optik, 2023 - Elsevier
It is well-demonstrated that laser-induced plasma (LIP) is a transient phenomenon in which
plasma characteristics vary with space and time. The study of the spatial and temporal …

Quantitative analysis of carbon with laser-induced breakdown spectroscopy (LIBS) using genetic algorithm and back propagation neural network models

J He, C Pan, Y Liu, X Du - Applied Spectroscopy, 2019 - journals.sagepub.com
Carbon content detection is an essential component of the metal-smelting and classification
processes. An obstacle in carbon content detection by laser-induced breakdown …

Towards real-time calibration-free LIBS supported by machine learning

A Favre, A Abad, A Poux, L Gosse, A Berjaoui… - … Acta Part B: Atomic …, 2025 - Elsevier
Abstract Calibration-Free Laser-Induced Breakdown Spectroscopy (CF-LIBS) enables multi-
elemental quantification without needing standards. This type of approach can be used to …

Quantitative analysis of steel samples using laser-induced breakdown spectroscopy with an artificial neural network incorporating a genetic algorithm

K Li, L Guo, J Li, X Yang, R Yi, X Li, Y Lu, X Zeng - Applied optics, 2017 - opg.optica.org
In this work, a genetic algorithm (GA) was employed to select the intensity ratios of the
spectral lines belonging to the target and domain matrix elements, then these selected line …