| Full text | |
| Author(s): |
Santos, Poliana M.
[1]
;
Amais, Renata S.
[2]
;
Colnago, Luiz A.
[3]
;
Rinnan, Asmund
[4]
;
Monteiro, Marcos R.
[5]
Total Authors: 5
|
| Affiliation: | [1] Fed Technol Univ Parana, Dept Biol & Chem, BR-80230901 Curitiba, Parana - Brazil
[2] Univ Sao Carlos, Dept Chem, BR-13565905 Sao Paulo - Brazil
[3] EMBRAPA Instrumentacao, BR-13560970 Sao Paulo - Brazil
[4] Univ Copenhagen, Fac Life Sci, Dept Food Sci, Qual & Technol, DK-1165 Copenhagen - Denmark
[5] Univ Fed Sao Carlos, Dept Mat Engn, BR-13565905 Sao Paulo - Brazil
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | ENERGY & FUELS; v. 29, n. 4, p. 2299-2303, APR 2015. |
| Web of Science Citations: | 8 |
| Abstract | |
Time-domain nuclear magnetic resonance (TD-NMR) was explored as a rapid method for simultaneous assessment of the quality parameters in commercial diesel samples (B5 diesel-biodiesel blend). A principal component analysis (PCA) obtained with the relaxation decay curves revealed tight and well-separated clusters, allowing discrimination of the diesel samples according to the sulfur content: 10 (S10), 500 (S500), and 1800 (S1800) mg kg(-1). Classification models based on the soft independent modeling of class analogy (SIMCA) showed a good discrimination power with a percentage of correct classification ranging from 90% (for S500 diesel samples) to 100% (for S10 and S1800 diesel samples). Partial least-squares regression (PLSR) was used to estimate the cetane index, density, flash point, and temperature achieved during distillation to obtain 50% of the distilled (T50) physicochemical parameters in the commercial diesel samples. The best PLSR models were obtained with two latent variables, providing a standard error of prediction (RMSEP) of 0.60, 2.37 kg m(-3), 3.24, and 2.20 degrees C for the cetane index, density, flash point, and T50, respectively, which represents the accuracy of the models. The results support the application of TD-NMR to evaluate the quality of B5 diesel, providing a simple, rapid, and nondestructive method for the petrofuel industry. (AU) | |
| FAPESP's process: | 10/17387-7 - Assessment of spectroanalytical techniques and sample preparation procedures for the determination of sulfur in biodiesel and diesel blends |
| Grantee: | Renata Stábile Amais |
| Support Opportunities: | Scholarships in Brazil - Doctorate |