Time Domain-NMR Combined with Chemometrics Analysis: An Alternative Tool for Monitoring Diesel Fuel Quality
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-separa...
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Published in: | Energy & fuels Vol. 29; no. 4; pp. 2299 - 2303 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
American Chemical Society
16-04-2015
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Subjects: | |
Online Access: | Get full text |
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Summary: | 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 °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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0887-0624 1520-5029 |
DOI: | 10.1021/acs.energyfuels.5b00017 |