Machine learning in laser-induced breakdown spectroscopy as a novel approach towards experimental parameter optimization
David Procházka, Pavel Pořízka, Jakub Hruška, Karel Novotný, Aleš Hrdlička, Jozef Kaiser
Abstract
Samples with different mechanical and physical properties were measured by LIBS under diverse experimental conditions. The results were used to train a neural network. By means of the neural network, the optimisation process was significantly reduced.
Topics & Concepts
Laser-induced breakdown spectroscopyArtificial neural networkProcess (computing)SpectroscopyLaserBiological systemMaterials scienceComputer scienceMachine learningArtificial intelligenceAnalytical Chemistry (journal)ChemistryPhysicsOpticsChromatographyQuantum mechanicsBiologyOperating systemLaser-induced spectroscopy and plasmaAnalytical chemistry methods developmentIon-surface interactions and analysis