scholarly journals Analytical Studies of Polychromes by Time-Integrated Laser-Induced Breakdown Spectroscopy

1999 ◽  
Vol 18 (3) ◽  
pp. 155-165 ◽  
Author(s):  
Margarita Martin ◽  
Marta Castillejo ◽  
Ricardo Torres ◽  
Diego Silva

Time integrated Laser Induced Breakdown Spectroscopy was applied to the study of real samples of polychromes. Two samples respectively from the Spanish Baroque and from the XV century were analysed. The time integrated spectra showed negligible contribution of continuum background emission. The spectra of the Baroque sample indicated the presence of vermilion; this was confirmed by Near Infrared Fourier Transform Spectroscopy. LIBS spectra of the XV century sample showed Ca, Al, Mg, Na and Pb lines and the molecular emissions CN(B-X) and C2(d-a). Relative spectral intensities were measured as a function of the number of laser pulses delivered on the same position of the sample. The LIBS analysis was compared to an exhaustive analytical study.

2007 ◽  
Vol 15 (21) ◽  
pp. 14044 ◽  
Author(s):  
Alexander W. Schill ◽  
David A. Heaps ◽  
Dimitra N. Stratis-Cullum ◽  
Bradley R. Arnold ◽  
Paul M. Pellegrino

2021 ◽  
pp. 000370282110123
Author(s):  
Hemalaxmi Rajavelu ◽  
Nilesh J Vasa ◽  
Satyanarayanan Seshadri

A benchtop Laser-Induced Breakdown Spectroscopy (LIBS) is demonstrated to determine the elemental carbon content present in raw coal used for combustion in power plants. The spectral intensities of molecular CN and C2 emission are measured together with the atomic carbon (C) and other inorganic elements (Si, Fe, Mg, Al, Ca, Na, and K) in the LIBS spectrum of coal. The emission persistence time of C2 molecule emission is measured from the coal plasma generated by a nanosecond laser ablation with a wavelength of 266 nm in the Ar atmosphere. The emission persistence time of molecular C2 emission along with the spectral intensities of major ash elements (Fe, Si, Al, and Ca) and carbon emissions (atomic C, molecular CN, and C2) shows a better relationship with the carbon wt% of different coal samples. The calibration model to measure elemental carbon (wt%) is developed by combining the spectral characteristics (Spectral intensity) and the temporal characteristics (Emission persistence time of C2 molecule emission). The temporal characteristic studies combined with the spectroscopic data in the PLSR (Partial Least Square Regression) model has resulted in an improvement in the root mean square error of validation (RMSEV), and the relative standard deviation (RSD) is reduced from 10.86% to 4.12% and from 11.32% to 6.04%, respectively.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5419 ◽  
Author(s):  
Sara Sánchez-Esteva ◽  
Maria Knadel ◽  
Sergey Kucheryavskiy ◽  
Lis W. de Jonge ◽  
Gitte H. Rubæk ◽  
...  

Conventional wet chemical methods for the determination of soil phosphorus (P) pools, relevant for environmental and agronomic purposes, are labor-intensive. Therefore, alternative techniques are needed, and a combination of the spectroscopic techniques—in this case, laser-induced breakdown spectroscopy (LIBS)—and visible near-infrared spectroscopy (vis-NIRS) could be relevant. We aimed at exploring LIBS, vis-NIRS and their combination for soil P estimation. We analyzed 147 Danish agricultural soils with LIBS and vis-NIRS. As reference measurements, we analyzed water-extractable P (Pwater), Olsen P (Polsen), oxalate-extractable P (Pox) and total P (TP) by conventional wet chemical protocols, as proxies for respectively leachable, plant-available, adsorbed inorganic P, and TP in soil. Partial least squares regression (PLSR) models combined with interval partial least squares (iPLS) and competitive adaptive reweighted sampling (CARS) variable selection methods were tested, and the relevant wavelengths for soil P determination were identified. LIBS exhibited better results compared to vis-NIRS for all P models, except for Pwater, for which results were comparable. Model performance for both the LIBS and vis-NIRS techniques as well as the combined LIBS-vis-NIR approach was significantly improved when variable selection was applied. CARS performed better than iPLS in almost all cases. Combined LIBS and vis-NIRS models with variable selection showed the best results for all four P pools, except for Pox where the results were comparable to using the LIBS model with CARS. Merging LIBS and vis-NIRS with variable selection showed potential for improving soil P determinations, but larger and independent validation datasets should be tested in future studies.


2015 ◽  
Vol 17 (2) ◽  
pp. 147-152 ◽  
Author(s):  
Jie Shen ◽  
Zhengcai Yang ◽  
Xiaoliang Liu ◽  
Yanchao Shi ◽  
Peixi Zhao ◽  
...  

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