A fast method for the calculation of electron number density and temperature in laser-induced breakdown spectroscopy plasmas using artificial neural networks |
| |
Authors: | Fábio O. Borges Gildo H. Cavalcanti Gabriela C. Gomes Vincenzo Palleschi Alexandre Mello |
| |
Affiliation: | 1. Instituto de Física, Universidade Federal Fluminense, Av. Gal. Milton Tavares de Souza, s/no, Campus da Praia Vermelha, Niterói, Rio de Janeiro, CEP 24210-346, Brazil 2. Centro Brasileiro de Pesquisas Físicas, Rua Dr. Xavier Sigaud, 150, Urca, Rio de Janeiro, RJ, CEP: 22290-180, Brazil 3. Institute of Chemistry of Organometallic Compounds, Research Area of National Research Council, Via G. Moruzzi, 1, Pisa, 56124, Italy
|
| |
Abstract: | A fast and precise method for the determination of electron temperature and electron number density in laser-induced plasmas is presented. The method is based on the use of a simple artificial neural network (ANN), trained on a suitable set of laser-induced breakdown spectroscopy spectra. The training procedure is quite fast; once the ANN is set, the determination of plasma temperature and electron number density is almost instantaneous, allowing the possibility of measuring these parameters, with good precision, in real time. A direct application of this new method could be the characterization of plasmas generated during pulsed laser deposition process of thin films and nanoparticles generation. The plasma electronic parameters will help to tune the energies involved in the stoichiometry and crystallization control of those nanostructured materials. As an example, the characteristics of the plasma induced by a Nd:YAG laser on a pure titanium target are determined, at different laser fluences. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|