Quantitative methods for compensation of matrix effects and self-absorption in Laser Induced Breakdown Spectroscopy signals of solids

Takahashi, Tomoko; Thornton, Blair

doi:10.1016/j.sab.2017.09.010

Cited by 133 publications

(59 citation statements)

References 131 publications

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“…Differences in spectral resolution, for example, often result in difficulties due to varying line widths and minor calibration errors. This, combined with chemical matrix effects and multicollinearities from analyses of geologic materials (with multiple elements), may significantly affect standard statistical techniques in their ability to accurately predict the elemental composition of the ablated sample . Minimizing the prediction error in chemometric analyses of LIBS data is of great importance given its widespread applications, and as such, these difficulties must be addressed.…”

Section: Introductionmentioning

confidence: 99%

On the application of a novel linear mixture model on laser‐induced breakdown spectroscopy: Implications for Mars

Konstantinidis

Cote

Lalla

et al. 2019

Journal of Chemometrics

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As the exploration of Mars and other solar system bodies becomes more prevalent, the importance of accurate methods in chemical analyses has increased. The use of laser‐induced breakdown spectroscopy (LIBS) in such analyses requires that well understood and accurate statistical methods exist for appropriate interpretation of resulting spectra. Many multivariate techniques have been developed for the elemental quantification of LIBS; however, each still has its limitations. In an endeavor to improve upon existing methodologies, a new algorithm is proposed using the ChemCam preflight calibration dataset and a dataset from the characterization of a LIBS/Raman sensor prototype developed at York University. The algorithm which was developed in this work is a linear mixture model within a submodel clustering framework. The cross validation and test results of the model on both datasets were reported using various metrics for each element under consideration (root mean square error, relative standard deviation, and R2 value). The algorithm was subsequently compared with other well established chemometric models on both datasets, such as principal component regression, partial least square regression, and ordinary least squares regression. Further validation of the algorithm was achieved by comparing the results presented herein to previously published results on the ChemCam data. The samples in each dataset are highly representative of Martian geology, which, given the overwhelming success of the algorithm on both datasets, suggests that subsequent implementation of the proposed algorithm on larger databases may have significant implications for Martian geochemical analyses and for planetary exploration as a whole.

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Section: Introductionmentioning

confidence: 99%

On the application of a novel linear mixture model on laser‐induced breakdown spectroscopy: Implications for Mars

Konstantinidis

Cote

Lalla

et al. 2019

Journal of Chemometrics

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“…The "matrix effects" are caused by changes in the emission line intensities of some elements in samples when the physical properties and the chemical composition of the matrix vary [46]. Previous studies have indicated that chemometrics and multivariate methods involving spectral preprocessing and calibration are efficient at reducing the "matrix effects" when applying LIBS to the determination of elements [47,48]. However, there are only a few studies combining chemometrics and LIBS for the measurements of soil properties, especially for soil nutrients.…”

Section: Introductionmentioning

confidence: 99%

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

et al. 2019

Soil Systems

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Accurate management of soil nutrients and fast and simultaneous acquisition of soil properties are crucial in the development of sustainable agriculture. However, the conventional methods of soil analysis are generally labor-intensive, environmentally unfriendly, as well as time- and cost-consuming. Laser-induced breakdown spectroscopy (LIBS) is a “superstar” technique that has yielded outstanding results in the elemental analysis of a wide range of materials. However, its application for analysis of farmland soil faces the challenges of matrix effects, lack of large-scale soil samples with distinct origin and nature, and problems with simultaneous determination of multiple soil properties. Therefore, LIBS technique, in combination with partial least squares regression (PLSR), was applied to simultaneously determinate soil pH, cation exchange capacity (CEC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) in 200 soils from different farmlands in China. The prediction performances of full spectra and characteristic lines were evaluated and compared. Based on full spectra, the estimates of pH, CEC, SOM, TN, and TK achieved excellent prediction abilities with the residual prediction deviation (RPDV) values > 2.0 and the estimate of TP featured good performance with RPDV value of 1.993. However, using characteristic lines only improved the predicted accuracy of SOM, but reduced the prediction accuracies of TN, TP, and TK. In addition, soil AP and AK were predicted poorly with RPDV values of < 1.4 based on both full spectra and characteristic lines. The weak correlations between conventionally analyzed soil AP and AK and soil LIBS spectra are responsible for the poor prediction abilities of AP and AK contents. Findings from this study demonstrated that the LIBS technique combined with multivariate methods is a promising alternative for fast and simultaneous detection of some properties (i.e., pH and CEC) and nutrient contents (i.e., SOM, TN, TP, and TK) in farmland soils because of the extraordinary prediction performances achieved for these attributes.

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“…To demonstrate the truth of concentration determination, facile calibration curves were determined for the known lead contents of the investigated glass samples. Though more sophisticated methods exist for determination of concentration, for example, calibration‐free LIBS or multivariate analysis, these techniques often require high experimental and numerical efforts . However, this is contrary to the objective of this work to show the feasibility of CO 2 ‐LIBS as a simple, fast, and economic detection technique for lead in glass cullet.…”

Section: Resultsmentioning

confidence: 83%

The feasibility of CO₂‐laser‐induced breakdown spectroscopy for fast lead determination in glass cullet

Lehmann

Fischer

Rosin

et al. 2019

Int J of Appl Glass Sci

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With an overall collection and recycling rate of 74%, the material cycle for glass packaging is well established in the European Union. However, knowledge of the composition of the recycled glass cullet is necessary to avoid creeping accumulation of undesirable contaminants into the material cycle. Due to their toxic properties, this applies in particular for heavy metals, for example, lead. The state‐of‐the‐art technology for detection of lead in recycling glass sorting is X‐ray fluorescence (XRF). Due to lower regulatory demands, as well as increasingly economical hardware, laser‐based detection techniques, like Laser‐Induced Breakdown Spectroscopy (LIBS) may provide an alternate approach in industrial glass sorting to reach comparable detection limits and rates. In our work, CO2‐LIBS was investigated as an alternative tool for the determination of lead in glass cullet. Instead of usually utilized spectrometers, a combination of spectral filters and photodiode was employed to facilitate a fast detection rate. Glass samples with different lead content were investigated in two spectral ranges with respect to detection limits, detection speed, and accuracy. The results are compared to a commercial XRF‐sorting machine for glass cullet. It was found that comparable speeds and accuracies for lead detection in glasses can be reached.

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Quantitative methods for compensation of matrix effects and self-absorption in Laser Induced Breakdown Spectroscopy signals of solids

Cited by 133 publications

References 131 publications

On the application of a novel linear mixture model on laser‐induced breakdown spectroscopy: Implications for Mars

On the application of a novel linear mixture model on laser‐induced breakdown spectroscopy: Implications for Mars

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

The feasibility of CO₂‐laser‐induced breakdown spectroscopy for fast lead determination in glass cullet

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