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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Data fusion of middle-resolution NMR spectroscopy and low-field relaxometry using the Common Dimensions Analysis (ComDim) to monitor diesel fuel adulteration

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Author(s):
de Aguiar, Leticia Magalhaes [1] ; Galvan, Diego [1] ; Bona, Evandro [2] ; Colnago, Luiz Alberto [3] ; Killner, Mario Henrique M. [1]
Total Authors: 5
Affiliation:
[1] Univ Estadual Londrina, Dept Quim, POB 10-011, BR-86057970 Londrina, Parana - Brazil
[2] Univ Tecnol Fed Parana, Programa Posgrad Tecnol Alimentos, Campus Campo Mourao, BR-87301899 Campo Mourao - Brazil
[3] Embrapa Instrumentacao, Rua 15 Novembro 1452, BR-13560970 Sao Carlos, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: Talanta; v. 236, JAN 1 2022.
Web of Science Citations: 0
Abstract

Medium-resolution (MR-NMR) and time-domain NMR relaxometry (TD-NMR) using benchtop and low-field NMR instruments are powerful tools to tackle fuel adulteration issues. In this work, for the first time, we investigate the possibility of enhancing the low-field NMR capability on fuel analysis using data fusion of MR and TD-NMR. We used the ComDim (Common Dimensions Analysis) multi-block analysis to join the data, which allowed exploration, classification, and quantification of common adulterations of diesel fuel by vegetable oils, biodiesel, and diesel of different sources as well as the sulfur content. After data exploration using ComDim, classification (applying linear discriminant analysis, LDA), and regression (applying multiple linear regression, MLR), models were built using ComDim scores as input variables on the LDA and MLR analyses. This approach enabled 100% of accuracy in classifying diesel fuel source (refinery), sulfur content (S10 or S500), vegetable oil, and biodiesel source. Moreover, in the quantification step, all MLR models showed a root mean square error of prediction (RMSEP) and the residual prediction deviation (RPD) values comparable to the literature for determining diesel, vegetable oil, and biodiesel contents. (AU)

FAPESP's process: 13/25802-2 - Development and validation of simple, fast and nondestructive medium and low-resolution NMR methods for the characterization and quality control of fossil fuels and biofuels.
Grantee:Mario Henrique Montazzolli Killner
Support Opportunities: Scholarships in Brazil - Post-Doctoral