Direct Determination of Ca, K, and Mg in Cocoa Beans by Laser-Induced Breakdown Spectroscopy (LIBS): Evaluation of Three Univariate Calibration Strategies for Matrix Matching

Gamela, Raimundo R.; Costa, Vinícius Câmara; Babos, Diego Victor; Araújo, Alisson Silva; Pereira-Filho, Edenir Rodrigues

doi:10.1007/s12161-020-01722-6

Cited by 19 publications

(7 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As the LIBS handheld tool provides fast identification of trace elements, i.e., Li (Figure 1); here we aimed to establish the calibration curve of Li content in different matrices. These univariate calibrations can be used in LIBS applications [42,[47][48][49][50][51][52].…”

Section: Discussionmentioning

confidence: 99%

Analyses of Li-Rich Minerals Using Handheld LIBS Tool

Fabre

Ourti

Cardoso-Fernandes

et al. 2021

Data

View full text Add to dashboard Cite

Lithium (Li) is one of the latest metals to be added to the list of critical materials in Europe and, thus, lithium exploration in Europe has become a necessity to guarantee its mid- to long-term stable supply. Laser-induced breakdown spectroscopy (LIBS) is a powerful analysis technique that allows for simultaneous multi-elemental analysis with an excellent coverage of light elements (Z < 13). This data paper provides more than 4000 LIBS spectra obtained using a handheld LIBS tool on approximately 140 Li-content materials (minerals, powder pellets, and rocks) and their Li concentrations. The high resolution of the spectrometers combined with the low detection limits for light elements make the LIBS technique a powerful option to detect Li and trace elements of first interest, such as Be, Cs, F, and Rb. The LIBS spectra dataset combined with the Li content dataset can be used to obtain quantitative estimation of Li in Li-rich matrices. This paper can be utilized as technical and spectroscopic support for Li detection in the field using a portable LIBS instrument.

show abstract

Section: Discussionmentioning

confidence: 99%

Analyses of Li-Rich Minerals Using Handheld LIBS Tool

Fabre

Ourti

Cardoso-Fernandes

et al. 2021

Data

View full text Add to dashboard Cite

show abstract

“…F1-score is the reconciled average of precision and recall, which is commonly used to evaluate the performance of machine learning models on unbalanced datasets. 34 Its formula is shown in eqn (2-4).…”

Section: Data Analysis Methodologymentioning

confidence: 99%

Rapid classification of heavy metal soils from different mining areas by using a GSCV quadratic merit seeking network combined with MF-LIBS

Jin,

Hao,

2023

J. Anal. At. Spectrom.

View full text Add to dashboard Cite

show abstract

“…The standard addition method (SAM) is not practical for solid sample analysis because of the difficulties in adding proper analyte amounts to the sample and errors may be caused by the heterogeneous distribution of the spiked analytes. Even with these hindrances, the approach was successfully exploited in the analysis of foods, [20][21][22] soil, 23 and cosmetics 24 by LIBS. Because of the previously mentioned difficulties, novel calibration approaches based on a single standard have been developed.…”

Section: Introductionmentioning

confidence: 99%