Laser ablation (LA); Laser induced fluorescence (LIF); Laser-induced breakdown spectroscopy (UBS); Plasma chemistry; Combustion;INDUCED BREAKDOWN SPECTROSCOPY; EXCITED ATOMIC FLUORESCENCE; INDUCED ALUMINUM PLASMA; SELECTIVE EXCITATION; URANIUM; ALO; SOLIDS; SPECTROMETRY; EVOLUTION; DYNAMICS

Oxygen present in the ambient gas medium may affect both laser-induced breakdown spectroscopy (LIBS) and laser-induced fluorescence (LIF) emission through a reduction of emission intensity and persistence. In this study, an evaluation is made on the role of oxygen in the ambient environment under atmospheric pressure conditions in LIBS and laser ablation (LA)-LIF emission. To generate plasmas, 1064 nm, 10 ns pulses were focused on an aluminum alloy sample. LIF was performed by frequency scanning a CW laser over the 396.15 nm (3s(2)4s S-2(1/2) -> 3s(2)3p P-2 degrees(3/2)) Al I transition. Time-resolved emission and fluorescence signals were recorded to evaluate the variation in emission intensity caused by the presence of oxygen. The oxygen partial pressure (p(o)) in the atmospheric pressure environment using N-2 as the makeup gas was varied from 0 to 400 Torr O-2. 2D-fluorescence spectroscopy images were obtained for various oxygen concentrations for simultaneous evaluation of the emission and excitation spectral features. Results showed that the presence of oxygen in the ambient environment reduces the persistence of the LIBS and LIF emission through an oxidation process that depletes the density of atomic species within the resulting laser-produced plasma (LPP) plume. (C) 2017 Elsevier B.V. All rights reserved.

LA-LIES; Dual-pulse; Elemental analysis; Low sample destruction;INDUCED BREAKDOWN SPECTROSCOPY; SIGNAL ENHANCEMENT; LASER-ABLATION; NANOSECOND; PLASMA

A study on elemental analysis of alloy samples under low sample destruction with dual-pulse laser-ablation laser induced breakdown spectroscopy (LA-LIES) based on one picosecond Nd : YAG laser is presented. In LA-LIBS, low pulse energy 532 nm laser was used for sample ablation and high pulse energy, time - delayed 1 064 nm laser was used for re-excitation of the ablated samples to enhance atomic emissions of the laser-induced plasma and signal detection sensitivity. The influence of pulse energies of the ablation laser and excitation laser to the signal intensities was studied experimentally. I was observed that Cu 324. 75 nm line intensity in LA-LIBS was enhanced 86 times in comparison with that obtained in SP-LIES under 10 mu J pulse energy of the ablation laser and 2. 5 mJ pulse energy of the excitation laser. The diameter of the crater generated in LA-LIES was less than 10 pin. It is demonstrated the possibility of using dual-pulse LA-LIBS to realize elemental analysis of solid sample under low sample destruction. This technique is valuable for elemental analysis of precious samples and 2D elements mapping under high spatial resolution.

Additive manufacturing; composition monitoring; optical emission spectroscopy (OES); support vector regression (SVR);INDUCED BREAKDOWN SPECTROSCOPY; METAL-DEPOSITION; MAGNESIUM ALLOY; ARC PLASMA; ELEMENTS; DEFECTS; NETWORK; SAMPLES; SYSTEM; LIBS

Laser additive manufacturing has gained widespread adoption in recent years. However, process diagnosis and process control lag behind the progresses of other key technologies, which make the product quality control a challenging problem. This work proposes an operating parameter conditioned support vector regression (SVR) method that uses processing parameter conditioned kernel function to achieve a processing parameter independent in-situ composition prediction. Two different features of laser-induced plasma, spectral line-intensity-ratio, and both spectral line-intensity-ratio and spectral integrated intensity were used to train the SVR. Composition measurements using a calibration curve method, partial least square regression, and artificial neural networks are also performed for comparison. The results show that the SVR with both spectral line-intensity-ratio and spectral integrated intensity as inputs has the best performance due to linearly separable point clusters in the high-dimensional space. Laser power independent composition prediction is achieved and real-time composition predictions are validated. It is proved that the operating parameter conditioned SVR provides a more accurate, a more universal, and an operating parameter independent prediction. Moreover, operating parameter conditioned SVR provides a potential data-driven-based approach for real-time composition monitoring of the laser additive manufacturing process.