Matches in SemOpenAlex for { <https://semopenalex.org/work/W3048987442> ?p ?o ?g. }
- W3048987442 endingPage "118854" @default.
- W3048987442 startingPage "118854" @default.
- W3048987442 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 R2p = 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." @default.
- W3048987442 created "2020-08-21" @default.
- W3048987442 creator A5001898876 @default.
- W3048987442 creator A5004437012 @default.
- W3048987442 creator A5011754630 @default.
- W3048987442 creator A5021380786 @default.
- W3048987442 creator A5042393314 @default.
- W3048987442 creator A5073530151 @default.
- W3048987442 creator A5074382420 @default.
- W3048987442 creator A5081501216 @default.
- W3048987442 date "2021-01-01" @default.
- W3048987442 modified "2023-10-17" @default.
- W3048987442 title "Discrimination of oils and fuels using a portable NIR spectrometer" @default.
- W3048987442 cites W1620101335 @default.
- W3048987442 cites W1967594998 @default.
- W3048987442 cites W1974766427 @default.
- W3048987442 cites W1988975411 @default.
- W3048987442 cites W1994852670 @default.
- W3048987442 cites W1997976704 @default.
- W3048987442 cites W2009957961 @default.
- W3048987442 cites W2016365402 @default.
- W3048987442 cites W2029372760 @default.
- W3048987442 cites W2031624236 @default.
- W3048987442 cites W2032822866 @default.
- W3048987442 cites W2035995049 @default.
- W3048987442 cites W2054335324 @default.
- W3048987442 cites W2054884292 @default.
- W3048987442 cites W2063646344 @default.
- W3048987442 cites W2066544032 @default.
- W3048987442 cites W2069907454 @default.
- W3048987442 cites W2077726450 @default.
- W3048987442 cites W2080373529 @default.
- W3048987442 cites W2085157107 @default.
- W3048987442 cites W2095274773 @default.
- W3048987442 cites W2097598900 @default.
- W3048987442 cites W2109606373 @default.
- W3048987442 cites W2114604090 @default.
- W3048987442 cites W2134827119 @default.
- W3048987442 cites W2140196823 @default.
- W3048987442 cites W2142749297 @default.
- W3048987442 cites W2264208959 @default.
- W3048987442 cites W2306844991 @default.
- W3048987442 cites W2326676660 @default.
- W3048987442 cites W2341468012 @default.
- W3048987442 cites W2462646109 @default.
- W3048987442 cites W2501236914 @default.
- W3048987442 cites W2511572704 @default.
- W3048987442 cites W2561045012 @default.
- W3048987442 cites W2563359405 @default.
- W3048987442 cites W2565996824 @default.
- W3048987442 cites W2566340699 @default.
- W3048987442 cites W2596231840 @default.
- W3048987442 cites W2745127447 @default.
- W3048987442 cites W2763200587 @default.
- W3048987442 cites W2766187403 @default.
- W3048987442 cites W2767663224 @default.
- W3048987442 cites W2774462379 @default.
- W3048987442 cites W2780876659 @default.
- W3048987442 cites W2789825181 @default.
- W3048987442 cites W2799365888 @default.
- W3048987442 cites W2808419452 @default.
- W3048987442 cites W2894339648 @default.
- W3048987442 cites W2896872337 @default.
- W3048987442 cites W2897233156 @default.
- W3048987442 cites W2897761855 @default.
- W3048987442 cites W2913929641 @default.
- W3048987442 cites W2915535103 @default.
- W3048987442 cites W2921229908 @default.
- W3048987442 cites W4239796383 @default.
- W3048987442 cites W608013677 @default.
- W3048987442 cites W91032783 @default.
- W3048987442 cites W999430408 @default.
- W3048987442 doi "https://doi.org/10.1016/j.fuel.2020.118854" @default.
- W3048987442 hasPublicationYear "2021" @default.
- W3048987442 type Work @default.
- W3048987442 sameAs 3048987442 @default.
- W3048987442 citedByCount "19" @default.
- W3048987442 countsByYear W30489874422022 @default.
- W3048987442 countsByYear W30489874422023 @default.
- W3048987442 crossrefType "journal-article" @default.
- W3048987442 hasAuthorship W3048987442A5001898876 @default.
- W3048987442 hasAuthorship W3048987442A5004437012 @default.
- W3048987442 hasAuthorship W3048987442A5011754630 @default.
- W3048987442 hasAuthorship W3048987442A5021380786 @default.
- W3048987442 hasAuthorship W3048987442A5042393314 @default.
- W3048987442 hasAuthorship W3048987442A5073530151 @default.
- W3048987442 hasAuthorship W3048987442A5074382420 @default.
- W3048987442 hasAuthorship W3048987442A5081501216 @default.
- W3048987442 hasBestOaLocation W30489874421 @default.
- W3048987442 hasConcept C103697071 @default.
- W3048987442 hasConcept C105795698 @default.
- W3048987442 hasConcept C113196181 @default.
- W3048987442 hasConcept C119128265 @default.
- W3048987442 hasConcept C121332964 @default.
- W3048987442 hasConcept C134484671 @default.
- W3048987442 hasConcept C138171918 @default.
- W3048987442 hasConcept C161790260 @default.
- W3048987442 hasConcept C178790620 @default.