Laser-induced breakdown spectroscopy of environmental and synthetic samples using non-intensified CCD: optimization of the excitation wavelength

Nicolodelli, Gustavo; Senesi, Giorgio S.; Romano, Renan Arnon; Cabral, Jader; Perazzoli, I. L. O.; Marangoni, Bruno; Boas, Paulino Ribeiro Villas; Milori, Débora Marcondes Bastos Pereira

doi:10.1007/s00340-017-6699-6

Cited by 11 publications

(3 citation statements)

References 32 publications

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“…Calibration based on standardised normal variate transformation gave results for a 532 nm laser better than those obtained with a 1064 nm laser. In another study they found 187 Chinese researchers investigated the effects of long pulse lengths. In one study, 500 µs pulses produced 190 a "quasi-stable" plasma in local thermal equilibrium.…”

Section: Laser Induced Breakdown Spectrometrymentioning

confidence: 99%

Atomic Spectrometry Update – a review of advances in environmental analysis

Bacon

Butler

Cairns

et al. 2019

J. Anal. At. Spectrom.

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Section: Laser Induced Breakdown Spectrometrymentioning

confidence: 99%

Atomic Spectrometry Update – a review of advances in environmental analysis

Bacon

Butler

Cairns

et al. 2019

J. Anal. At. Spectrom.

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“…Photonic techniques and machine learning algorithms have been extensively used to improve agricultural management in the past few years, mainly due to their high accuracy associated with their fast response, low analytical cost, simplified sample preparation, and environmentally clean techniques [ 7 , 8 , 9 , 10 , 11 , 12 ]. Recently, our research group demonstrated the potential application of the Fourier-transform infrared (FTIR) and Laser-induced breakdown spectroscopy (LIBS) for seed vigor classification [ 5 , 8 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Laser-Induced Breakdown Spectroscopy Associated with the Design of Experiments and Machine Learning for Discrimination of Brachiaria brizantha Seed Vigor

Cioccia

Morais

Babos

et al. 2022

Sensors

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Laser-induced breakdown spectroscopy (LIBS) associated with machine learning algorithms (ML) was used to evaluate the Brachiaria seed physiological quality by discriminating the high and low vigor seeds. A 23 factorial design was used to optimize the LIBS experimental parameters for spectral analysis. A total of 120 samples from two distinct cultivars of Brachiaria brizantha seeds exhibiting high vigor (HV) and low vigor (LV) in standard tests were studied. The raw LIBS spectra were normalized and submitted to outlier verification, previously to the reduction data dimensionality from principal component analysis. Supervised machine learning algorithm parameters were chosen by leave-one-out cross-validation in the test samples, and it was tested by external validation using a new set of data. The overall accuracy in external validation achieved 100% for HV and LV discrimination, regardless of the cultivar or the classification algorithm.

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“…The LIBS (Laser Induced Breakdown Spectroscopy) system is widely used in several research fields for atomic analysis of many materials, including alloys, soils, fertilizers, grains, architectonic objects, semiconductors and medicines, among others [1][2][3][4][5][6][7]. A short period of time have passed since the first experiments, and the technique progress is still far away from stagnate.…”

Section: -Introductionmentioning

confidence: 99%

Calculation of an Optical setup for a LIBS system

Zanetti¹,

Cabral²

2018

JETI

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In this work we will represent the calculation for an optical LIBS system, as well as the parameters for the beam characterization. On the realized simulation, the beam was treated with the wave optics theory and its propagation with the paraxial approximation. It was described as a beam of Gaussian intensity profile and its propagation was acquired through the ABCD's law. Our results have showed the appropriated lens to hold a LIBS sign for different kinds of materials, depending on their bond cleavage. Also, we have showed a table with typical values of focus lens, used in LIBS setups, and its respective irradiance.

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Laser-induced breakdown spectroscopy of environmental and synthetic samples using non-intensified CCD: optimization of the excitation wavelength

Cited by 11 publications

References 32 publications

Atomic Spectrometry Update – a review of advances in environmental analysis

Atomic Spectrometry Update – a review of advances in environmental analysis

Laser-Induced Breakdown Spectroscopy Associated with the Design of Experiments and Machine Learning for Discrimination of Brachiaria brizantha Seed Vigor

Calculation of an Optical setup for a LIBS system

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