Sulfur Determination in Brazilian Petroleum Fractions by Mid-infrared and Near-infrared Spectroscopy and Partial Least Squares Associated with Variable Selection Methods

Rocha, Julia T.C.; Oliveira, Lize M. S. L.; Dias, Júlio Cesar; Pinto, Ulysses B.; Marques, Maria de Lourdes S. P.; Oliveira, Betina P.; Filgueiras, Paulo R.; Castro, Eustáquio Vinícius Ribeiro de; Oliveira, Marcone Augusto Leal de

doi:10.1021/acs.energyfuels.5b02463

Cited by 37 publications

(15 citation statements)

References 47 publications

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“…PLS linear regression is an mathematical method that externally correlates an instrumental data set (X matrix) and an interest property set (Y matrix) by linear equations [13,14] :…”

Section: Mathematical and Computational Fundamentalsmentioning

confidence: 99%

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Silva

Wiebeck

2019

Polímeros

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Industries and the scientific community currently focus on creating new ways to recycle and to reuse polymer waste that leads to serious socio-environmental risks. However, the quality of recycled polyethylenes depends strongly on their purity degree, but the distinction between Low Density Polyethylene (LDPE) and High Density Polyethylene (HDPE) by a fast and consistently good methodology is still an unsolved issue for the current recycling processes. In this study, confocal Raman spectroscopy and Competitive Adaptive Reweighted Sampling-Partial Least Squares (CARS-PLS) linear regression have been successfully applied to quantify the concentration of LDPE/HDPE blends. The effects of several regression parameters (pretreatment method, Monte Carlo sampling runs, k-fold and maximal number of latent variables for cross-validation) on the CARS-PLS model training and prediction performance were analyzed. The CARS-PLS-based models show root-mean-squared prediction error of 4.06-8.87 wt% of LDPE for the whole composition range of HDPE/LDPE blend.

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“…PLS linear regression is an mathematical method that externally correlates an instrumental data set (X matrix) and an interest property set (Y matrix) by linear equations [13,14] :…”

Section: Mathematical and Computational Fundamentalsmentioning

confidence: 99%

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Silva

Wiebeck

2019

Polímeros

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“…The use of small amounts of samples was highlighted by the authors 39 . Sulfur content in petroleum derivatives was determined using MIR spectroscopy and PLS in association with variable selection methods, among them iPLS, siPLS, uninformative variable elimination (UVE), and GA 40 . The UV spectroscopy integrated different chemometric strategies for quantifying the hydrocarbon contents in fuel oil samples 41 .…”

Section: Fuelmentioning

confidence: 99%

Chemometrics in analytical chemistry – an overview of applications from 2014 to 2018

et al. 2019

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A compilation of papers published between 2014 and 2018 was evaluated. Many papers related to multivariate calibration and classification have been reported, as well as, design of experiments applications and artificial intelligence methods. Some applications were highlighted, as medical and pharmaceutical, food analysis, fuels, biological and forensic for the chemometric techniques on this review. Most studies are related to developing methods for practical solutions in industry or routine analysis. A promising scenario is shown considering the number of published papers: a total of 832 for this period using the keywords, multivariate classification, multivariate calibration, analysis, chemometrics, prediction, analytical chemistry, artificial neural networks (ANN), design of experiments (DoE) and factorial design. An useful overview for Analytical Chemistry researchers´ combined with Chemometrics is presented in this review.

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“…The quantitative analysis model can be established via the pretreated spectral data. Partial least squares (PLS) is a chemometrics method which can establish quantitative analysis model in the full spectrum range [20][21][22][23]. Interval partial least squares (iPLS) is a new chemometric method developed on the basis of PLS [24,25], dividing the full spectrum range into several intervals with equal width.…”

Section: Introductionmentioning

confidence: 99%

Rapid Determination of the Total Phosphorus and the Nitrate Nitrogen in Denitrifying Phosphorus Removal with iPLS and Near Infrared Spectroscopy

Jian¹,

Xuan²,

Zhang³

et al. 2021

Pol. J. Environ. Stud.

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Denitrifying phosphorus removal was realized in sequencing batch reactor with alternate anaerobicanoxic procedures. Quantitative analysis models of the total phosphorus and nitrate nitrogen were established with near infrared spectroscopy combined with interval partial least-squares (iPLS). Second derivative, multiple scatter correction and wavelet denoising were respectively used to pretreat the raw near infrared spectral data. The results show that the iPLS model established by wavelet denoising method was the optimal one. As to the interval partial least-squares calibration models (iPLS models) of the total phosphorus and nitrate nitrogen, the results showed that the coefficients (r c ) of the correlation between the actual values and corrected values were respectively 0.9449 and 0.8681, with the root mean square errors of cross validation (RMSECV) being 0.0254 and 0.0315. In addition, the testing results of the interval partial least-squares calibration models of the total phosphorus and nitrate nitrogen indicated that the coefficients (r p ) of correlation between the actual values and predicted values were 0.9294 and 0.9014, with the root mean square errors of prediction (RMSEP) being 0.0235 and 0.0298. This study suggested that the iPLS models of the total phosphorus and nitrate nitrogen may provide a method for synchronous detection of the total phosphorus and nitrate nitrogen during denitrifying phosphorus removal.

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Sulfur Determination in Brazilian Petroleum Fractions by Mid-infrared and Near-infrared Spectroscopy and Partial Least Squares Associated with Variable Selection Methods

Cited by 37 publications

References 47 publications

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Chemometrics in analytical chemistry – an overview of applications from 2014 to 2018

Rapid Determination of the Total Phosphorus and the Nitrate Nitrogen in Denitrifying Phosphorus Removal with iPLS and Near Infrared Spectroscopy

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