Characterization of petroleum-based products by infrared spectroscopy and chemometrics

Khanmohammadi, Mohammadreza; Garmarudi, Amir Bagheri; Guárdia, Miguel de la

doi:10.1016/j.trac.2011.12.006

Cited by 69 publications

(29 citation statements)

References 46 publications

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“…In the other hand, qualitative and quantitative analysis using spectroscopy in the infrared region expanded from the time when the data generated by a FT-IR spectrophotometer could only be scanned, enabling statistical methods to solve problems of chemical analysis [17–21]. In HCA the spectra data matrix is reduced to one dimension, by matching similar pairs, until all points in a single group are matched.…”

Section: Introductionmentioning

confidence: 99%

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

Mueller

Ferrão

Marder

et al. 2013

Sensors

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The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.

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Section: Introductionmentioning

confidence: 99%

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

Mueller

Ferrão

Marder

et al. 2013

Sensors

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“…28 The new matrix is added to the original matrix X, forming an extended matrix 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 and original variables, which are considered to contain nothing but noise, are eliminated. 28,35 )) ( max( * noise c abs k cutoff = (4) where k is an arbitrary value, are the values for the artificial variables, and ‫ܠ܉ܕ‬ (( ሻሻ is the maximum absolute value for the reliability criterion. A new PLS model is, therefore, built from the selected variables by UVE and its efficiency is compared to the global PLS model.…”

Section: Uve-plsmentioning

confidence: 99%

“…2,3 In this point, the chemometrics, associated with spectroscopy (near and midinfrared in particular), has shown potential as a tool for analytical chemistry by generating alternative methods for the characterization and evaluation of physical and chemical properties of petroleum and its derivatives with high precision, reliability and speed. [4][5][6][7][8][9][10] Such methods have increasingly been used in petroleum and its derivatives data, since these products are generally highly complex, and their physicochemical characterization requires considerable effort. In this context, sometimes there is urgency to obtain results of certain analysis and the decision-making is hampered by the way the analyses are made.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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Chemometric tools (PLS) with variable selection (iPLS, siPLS, UVE and GA), associated with near infrared (NIR) and mid infrared (MIR) spectroscopy, were applied for the determination of sulfur content (wt %) in petroleum derivatives. The evaluation of the models was conducted by the determination and analysis of the following requirements: coefficient of determination (R 2 ); the curve obtained by plotting the predicted versus measured values; and also the cross-validation and prediction errors.The developed models presented in this work had satisfactory results, demonstrating that both NIR and MIR techniques, combined with chemometric tools, can be used to determine the sulfur content in petroleum fractions, with LOD and LOQ from 0.0234 and 0.0781 respectively. All variable selection techniques improved the predictive ability of the mode when compared with the full-spectra model, except the UVE method that showed a better performance only when associated with MIR data.

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“…There are numerous detection methods for determining methanol content in gasoline and the commonly used is gas chromatography (GC) or gas chromatography-mass spectrometer (GC-MS) [6]. Although these detection methods have high sensitivity and accuracy, they are time-consuming and complex, require toxic and hazardous reagents, and cannot meet the needs of online monitoring.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Methanol Gasoline by ATR-FT-IR Spectroscopy

et al. 2019

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Methanol gasoline blends are a more economical, and environmentally friendly fuels than gasoline alone, and are widely used in the transportation industry. The content of methanol in methanol gasoline plays an important role in ensuring the quality of gasoline. In some solutions, due to the shortage of energy and illegal profits, the problem of gasoline adulteration and its fineness, has received more and more attention, which would seriously affect the operating condition and service life of internal combustion engines. Therefore, it is very important to identify the correct level of gasoline. However, the traditional detection method is complex and time-consuming. To this end, the feasibility of using attenuated total reflectance Fourier transform infrared (ATR-FTIR) methods coupled with chemometrics methods were investigated to quantitatively and qualitatively analyze methanol gasoline. The qualitative analysis result of partial least squares discriminant analysis (PLS-DA) obtained 100% and 98.66% accuracy in the calibration set and the prediction set, respectively. As for quantitative analysis; two regression algorithms of partial least squares regression (PLSR) and the least square support vector machine (LS-SVM), as well as two variables selection methods of the successive projections algorithm (UVE) competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE) were combined to establish the quantitative model. By comparing the performance of the optimal models; the UVE-PLSR model performed best with a residual predictive deviation (RPD) value of 6.420. The qualitative and quantitative analysis results demonstrate the feasibility of using ATR-FTIR spectra to detect the methanol in methanol gasoline. It is believed that the promising IR spectra will be widely used in gasoline energy quality control in the further.

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Characterization of petroleum-based products by infrared spectroscopy and chemometrics

Cited by 69 publications

References 46 publications

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

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

Analysis of Methanol Gasoline by ATR-FT-IR Spectroscopy

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