Double-pulse neodymium YAG/Carbon dioxide laser-induced breakdown spectroscopy for excitation of bulk and trace analytes

Becker, Jason R; Skrodzki, P. J.; Diwakar, Prasoon K.; Hassanein, A.

doi:10.1080/00387010.2016.1144073

Cited by 7 publications

(2 citation statements)

References 61 publications

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“…There stark-broadening line profile of neutral Cu, Al, and Zn is shown in figure 5. Electron impact parameters for the lines can be found in [41][42][43][44]. Electron plasma number density calculated using neutral lines ranges between 3.59 × 10 15 to 3.057 × 10 16 cm −3 .…”

Section: Measurements Of Electron Number Densitymentioning

confidence: 99%

Elemental study of Devarda’s alloy using calibration free-laser induced breakdown spectroscopy (CF‒LIBS)

Iqbal¹,

Alrabdi²,

Fayyaz³

et al. 2023

Laser Phys.

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In the present study, we present the compositional analysis of a Devarda’s alloy using the calibration–free laser-induced breakdown spectroscopy (CF-LIBS) technique. A nanosecond pulsed Q-switched Nd:YAG laser was focused on the target-sample under investigation to ablate its surface and the measured emission spectrum was registered by using a spectrometer (LIBS2000+) having the optical spectral within a range from 200–720 nm. The analysis of the measured optical spectra confirms the presence of three major elements Aluminum (Al), Copper (Cu), and Zinc (Zn) in the target sample. The emission intensity line profiles of Zn, Cu, and Al were utilized to estimate the plasma-parameters consisting of excitation temperature, and the plasma number density. The plasma excitation temperature was investigated using the Boltzmann-plot technique, which yields the temperature for Cu and Zn as 8547 ± 5% K and 8100 ± 5%, respectively, while the electron plasma density was calculated from the Stark-broadening of individual neutral emission lines of Al, Cu, and Zn. For the quantitative analysis of the elements that exist in the target sample, a CF-LIBS technique was employed by assuming the condition of optically thin plasma as well as local thermodynamics equilibrium. Using the CF-LIBS technique, the relative composition in the form of weight percentage was estimated to be Zn: 57%, Al: 39%, and Cu: 4%, whereas, the certified concentration of Devarda’s alloy was 50% for Zn, 45% for Al, and 5% for Cu. These measured results reveal that the elemental concentration utilizing CF-LIBS shows a reasonable agreement with standard estimates illustrated by the manufacturer. This study further suggests that the CF-LIBS technique opens up an opportunity for engineering and industrial usage of LIBS where a quantifiable study of the substance is exceedingly advantageous.

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Section: Measurements Of Electron Number Densitymentioning

confidence: 99%

Elemental study of Devarda’s alloy using calibration free-laser induced breakdown spectroscopy (CF‒LIBS)

Iqbal¹,

Alrabdi²,

Fayyaz³

et al. 2023

Laser Phys.

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“…Therefore, to find a method that can quickly and accurately detect the magnetic properties of haematite is of great significance to the selection of the beneficiation process of haematite ore. Spectral analysis is a method of identifying substances and determining their chemical composition and relative content based on the spectrum of a substance. This method has been widely used in classification, the grade identification of rocks and minerals, food quality inspection, and many other aspects due to its advantages of a high analysis speed, simple operation, low cost, and high efficiency [3][4][5][6]. The factors influencing the magnetic property of iron ore are mainly the content of the magnetic minerals in iron ore.…”

Section: Introductionmentioning

confidence: 99%

Study of the Magnetic Properties of Haematite Based on Spectroscopy and the IPSO-ELM Neural Network

et al. 2018

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The detection of the magnetic properties of haematite plays an important role in the adjustment of the beneficiation process of haematite and the improvement of metal recovery. The existing methods for measuring the magnetic properties of iron ore either have large errors or take a long time. Therefore, it is very necessary to find a method that can quickly and accurately detect the magnetic properties of haematite. This paper presents a method to detect the magnetic properties of haematite based on the extreme learning machine based on the improved particle swarm optimization (IPSO-ELM) algorithm and spectroscopy. The improved particle swarm optimization algorithm is used to optimize the input weights, hidden layer deviations, and hidden layer nodes of the ELM network. Introducing the linear decreasing inertia weight for the particle swarm algorithm, taking into account the norm of the output weight in the particle update process and using the variation idea to change the length of the particle give the IPSO-ELM better stability and generalization ability. The experimental results show that the IPSO-ELM prediction model has a good prediction performance and has better generalization ability than that of the ELM and PSO-ELM prediction models. Compared with traditional chemical analysis methods and manual methods, this method has great advantages in terms of economy, speed, and accuracy.

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High repetition rate step acousto-optic Q-switched laser with three nanosecond equal-interval and amplitude pulses

Xie,

Liu,

et al. 2024

Optics Communications

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Double-pulse neodymium YAG/Carbon dioxide laser-induced breakdown spectroscopy for excitation of bulk and trace analytes

Cited by 7 publications

References 61 publications

Elemental study of Devarda’s alloy using calibration free-laser induced breakdown spectroscopy (CF‒LIBS)

Elemental study of Devarda’s alloy using calibration free-laser induced breakdown spectroscopy (CF‒LIBS)

Study of the Magnetic Properties of Haematite Based on Spectroscopy and the IPSO-ELM Neural Network

High repetition rate step acousto-optic Q-switched laser with three nanosecond equal-interval and amplitude pulses

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