Discrimination of oils and fuels using a portable NIR spectrometer. (1st January 2021)
- Record Type:
- Journal Article
- Title:
- Discrimination of oils and fuels using a portable NIR spectrometer. (1st January 2021)
- Main Title:
- Discrimination of oils and fuels using a portable NIR spectrometer
- Authors:
- Santos, Francine D.
Santos, Layla P.
Cunha, Pedro H.P.
Borghi, Flávia T.
Romão, Wanderson
de Castro, Eustáquio V.R.
de Oliveira, Elcio C.
Filgueiras, Paulo R. - Abstract:
- Graphical abstract: Highlights: Portable NIR spectrometer was used to discriminate crude oils from used motor oils. PLS-DA model discriminated crude oils with precision over 94%. Naphtha was quantified in gasoline with LOD of 4.4 wt%. Diesel was quantified in kerosene with LOD of 9.3 wt%. Abstract: Improper mixtures of: motor oil with crude oil; and derivatives mixed with other derivatives of lesser commercial value were identified in Brazil by companies in the energy sector. This study shows the great response that a portable NIR spectrometer had to discriminate crude oils and derivatives and to quantify them in blends (crude oils with used motor oil; and naphtha, gasoline, diesel, and kerosene). NIR spectra set were acquired in triplicate using a microNIR™ portable spectrometer, where it was possible to discriminate crude oil from used motor oil with 100% sensitivity, specificity, and precision. Regression models can quantify the oil content of a ternary mixture containing two crude oils (light and heavy oil) and a used motor oil with root mean square error of prediction (RMSEP) of 6.2 and 4.8 wt%, and R 2 p = 0.9871 and 0.9870 for support vector regression (SVR) and partial least squares (PLS), respectively. About the NIR spectra of naphtha, gasoline, diesel, and kerosene, partial least squares discriminant analysis (PLS-DA) allows the identification of any of these products with sensitivity, specificity, and precision of 100%. For the blends of gasoline and naphtha, theGraphical abstract: Highlights: Portable NIR spectrometer was used to discriminate crude oils from used motor oils. PLS-DA model discriminated crude oils with precision over 94%. Naphtha was quantified in gasoline with LOD of 4.4 wt%. Diesel was quantified in kerosene with LOD of 9.3 wt%. Abstract: Improper mixtures of: motor oil with crude oil; and derivatives mixed with other derivatives of lesser commercial value were identified in Brazil by companies in the energy sector. This study shows the great response that a portable NIR spectrometer had to discriminate crude oils and derivatives and to quantify them in blends (crude oils with used motor oil; and naphtha, gasoline, diesel, and kerosene). NIR spectra set were acquired in triplicate using a microNIR™ portable spectrometer, where it was possible to discriminate crude oil from used motor oil with 100% sensitivity, specificity, and precision. Regression models can quantify the oil content of a ternary mixture containing two crude oils (light and heavy oil) and a used motor oil with root mean square error of prediction (RMSEP) of 6.2 and 4.8 wt%, and R 2 p = 0.9871 and 0.9870 for support vector regression (SVR) and partial least squares (PLS), respectively. About the NIR spectra of naphtha, gasoline, diesel, and kerosene, partial least squares discriminant analysis (PLS-DA) allows the identification of any of these products with sensitivity, specificity, and precision of 100%. For the blends of gasoline and naphtha, the limit of detection (LOD), limit of quantification (LOQ), and RMSEP were 1.3, 4.4, and 1.4 wt%, respectively. Likewise, for diesel and kerosene blends, the PLS model allows the identification of the diesel with LOD, LOQ, and RMSEP of 2.8 wt%, 9.3 wt%, and 11.4 wt%, respectively. … (more)
- Is Part Of:
- Fuel. Volume 283(2021)
- Journal:
- Fuel
- Issue:
- Volume 283(2021)
- Issue Display:
- Volume 283, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 283
- Issue:
- 2021
- Issue Sort Value:
- 2021-0283-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-01-01
- Subjects:
- Crude oil -- Fuels -- Chemometrics -- NIR portable
Fuel -- Periodicals
Coal -- Periodicals
Coal
Fuel
Periodicals
662.6 - Journal URLs:
- http://www.sciencedirect.com/science/journal/latest/00162361 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.fuel.2020.118854 ↗
- Languages:
- English
- ISSNs:
- 0016-2361
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4048.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14737.xml