Optical and thermal characterization of pure CuO and Zn/CuO using laser-induced breakdown spectroscopy (LIBS), x-ray fluorescence (XRF), and ultraviolet–visible (UV–Vis) spectroscopy techniques

Khan, Muhammad Ilyas; Fayyaz, Amir; Mushtaq, Saadia; Asghar, Haroon; Alrebdi, Tahani A.; Cabrera, Humberto; Ali, Raheel; Akbar, Jehan

doi:10.1088/1612-202x/ace0b0

Cited by 3 publications

(2 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The UV-visible region refers to the absorption of electromagnetic radiation in the wavelength range of 200~800 nm, with the wavelength in the 200~380 nm range of electromagnetic radiation called ultraviolet, and the wavelength in the range of 400~750 nm called visible light [212]. The UV-visible absorption spectrum is due to molecular absorption of ultraviolet or visible light after the valence electrons undergo a leap, produced by the molecular absorption spectrum, usually only 2~3 absorption peaks and mainly used to detect the unsaturation of molecules to determine the conjugate system [213,214]. UV spectroscopy can be used for qualitative analysis in the structural identification of compounds, which requires a comprehensive consideration of the number, position, intensity, and shape of absorption bands.…”

Section: Ultraviolet-visible (Uv-vis) Spectroscopymentioning

confidence: 99%

Extraction and Analysis of Chemical Compositions of Natural Products and Plants

Zhang,

Zhao,

Dai

et al. 2023

Separations

View full text Add to dashboard Cite

There are many types of natural plants in nature that contain a variety of effective and complex chemical components. These constituents can be categorized as organic acids, volatile oils, coumarins, steroids, glycosides, alkaloids, carbohydrates, phytochromes, etc., all of which play important roles in the fields of pharmaceuticals, food, nutraceuticals, and cosmetics. The study of extraction and chemical composition analysis of natural products is important for the discovery of these active ingredients and their precursors. Therefore, the aim of this article is to review the status of research on the extraction, separation and purification, and structural identification of natural products, to provide a reference for the study of natural products.

show abstract

Section: Ultraviolet-visible (Uv-vis) Spectroscopymentioning

confidence: 99%

Extraction and Analysis of Chemical Compositions of Natural Products and Plants

Zhang,

Zhao,

Dai

et al. 2023

Separations

View full text Add to dashboard Cite

show abstract

“…Because of its unique features like in-situ realtime measurements, stand-off property, the lack of sample preparation, and applicability to any sample regardless of physical state, the LIBS has been recognized as a versatile technique among other physical methods for elemental analysis [1][2][3]. Besides the analytical applications, LIBS is considered the most effective method to characterize laserproduced plasmas (LPP) parameters, including plasma temperature, electron number density, and atomic species number densities [4,5]. Evaluation of plasma parameters, particularly plasma temperature, is necessary to analyse the complex laser ablation process, including dissociations, atomization, ionization, and excitation [6].…”

Section: Introductionmentioning

confidence: 99%

Impact of intensity error on temperature estimation in laser-induced breakdown spectroscopy: a numerical study

John,

Anoop

2023

Laser Phys.

View full text Add to dashboard Cite

Laser-induced breakdown spectroscopy (LIBS) is a cutting-edge technique for the compositional analysis of multi-element materials. Under standard circumstances for laser-induced plasma (T e = 1 eV and N e = 1016 cm−3), we simulated the emission spectrum of a binary alloy (with 70 wt.% Cu–30 wt.% Al). We used the Saha ionization equilibrium formulas to calculate the population of neutral and ionized species of each constituent element, and the Boltzmann distribution to estimate the intensities of emission lines with radiative transition probabilities. The Stark broadening equation is then used to determine the line broadening, yielding a Lorentzian profile for each line. The sum of line emissions of all constituent species will approximate the alloy’s LIBS spectra in an assumption of ideal analytical plasma. Then, we generated random errors in the intensities of spectral lines ranging from 5% to 35%. To investigate temperature estimation accuracy, we utilized three well-established approaches: the Boltzmann plot (BP) method, the Saha–Boltzmann plot (SBP) method, and the Multi-elemental SBP (MESBP) method. As intensity error increases from 5% to 35%, the estimated temperature in the BP method deviates from 0.25% to 18.3%. Whereas the intensity error is almost unaffected using the SBP method and the MESBP method. The temperature deviation is less than 2% in both situations. This study is relevant to calibration-free LIBS, in which the exact temperature determination is crucial for the abundance estimation of trace, major, and minor elements.

show abstract

Strategy for reducing the effect of surface fluctuation in the classification of aluminum alloy via data transfer and laser-induced breakdown spectroscopy

Chen,

Ding,

et al. 2023

Opt. Express

View full text Add to dashboard Cite

Laser-induced breakdown spectroscopy (LIBS) plays an increasingly important role in the classification and recycling of aluminum alloys owing to its outstanding elemental analysis performance. For LIBS measurements with sample surface fluctuations, consistently and exactly maintaining the laser and fiber focus points on the sample surface is difficult, and fluctuations in the focus severely affect the stability of the spectrum. In this study, a data transfer method is introduced to reduce the effect of spectral fluctuations on the model performance. During the experiment, a focal point is placed on the sample surface. Then, keeping experimental conditions unchanged, the three-dimensional platform is only moved up and down along the z-axis by 0.5 mm, 1 mm, 1.5 mm, 2 mm and 2.5 mm, respectively. Eleven spectral datasets at different heights are collected for analysis. The KNN model is used as the base classifier, and the accuracies of the 11 datasets, from the lowest to the highest, are 11.48%, 19.71%, 30.57%, 45.71%, 53.57%, 88.28%, 52.57%, 21.42%, 14.42%, 14.42%, and 14.42%. To improve predictive performance, the difference in data distribution between the spectra collected at the sample surface and those collected at other heights is reduced by data transfer. Feature selection is introduced and combined with data transfer, and the final accuracies are 78.14%, 82.28%, 80.14%, 89.71%, 91.85%, 98.42%, 94.28%, 92.42%, 82.14%, 78.57%, and 73.71%. It can be seen that the proposed method provides a new feasible and effective way for the classification of aluminum alloys in a real detection environment.

show abstract

Optical and thermal characterization of pure CuO and Zn/CuO using laser-induced breakdown spectroscopy (LIBS), x-ray fluorescence (XRF), and ultraviolet–visible (UV–Vis) spectroscopy techniques

Cited by 3 publications

References 40 publications

Extraction and Analysis of Chemical Compositions of Natural Products and Plants

Extraction and Analysis of Chemical Compositions of Natural Products and Plants

Impact of intensity error on temperature estimation in laser-induced breakdown spectroscopy: a numerical study

Strategy for reducing the effect of surface fluctuation in the classification of aluminum alloy via data transfer and laser-induced breakdown spectroscopy

Contact Info

Product

Resources

About