Resumé
Originalsprog | Engelsk |
---|---|
Tidsskrift | Energy & Fuels |
Vol/bind | 22 |
Udgave nummer | 6 |
ISSN | 0887-0624 |
DOI | |
Status | Udgivet - 2008 |
Citer dette
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Quantitative analysis of constituents in heavy fuel oil bytextlesssuptextgreater1textless/suptextgreaterH nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis. / Nielsen, K.E.; Dittmer, J.; Malmendal, A.; Nielsen, N.Chr.
I: Energy & Fuels, Bind 22, Nr. 6, 2008.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
TY - JOUR
T1 - Quantitative analysis of constituents in heavy fuel oil bytextlesssuptextgreater1textless/suptextgreaterH nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis
AU - Nielsen, K.E.
AU - Dittmer, J.
AU - Malmendal, A.
AU - Nielsen, N.Chr.
PY - 2008
Y1 - 2008
N2 - Characterization of heavy fuel oil (HFO) is highly important to ensure technically, economically, and environmentally proper operation of the engines and power plants that use this source of energy. This applies in particular to the shipping industry. Here, we demonstrate that the combination of standard1H nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis can be employed for quick and accurate extraction of parameters pertaining to the physical and chemical properties of complex suspensions, such as HFO. For 82 HFO samples of known origin, good prediction models were obtained for a large number of characterization parameters, including the calculated aromaticity index, the density, gross and net calorific values, and water and sulfur contents, as well as micro-carbon residue. textcopyright 2008 American Chemical Society.
AB - Characterization of heavy fuel oil (HFO) is highly important to ensure technically, economically, and environmentally proper operation of the engines and power plants that use this source of energy. This applies in particular to the shipping industry. Here, we demonstrate that the combination of standard1H nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis can be employed for quick and accurate extraction of parameters pertaining to the physical and chemical properties of complex suspensions, such as HFO. For 82 HFO samples of known origin, good prediction models were obtained for a large number of characterization parameters, including the calculated aromaticity index, the density, gross and net calorific values, and water and sulfur contents, as well as micro-carbon residue. textcopyright 2008 American Chemical Society.
U2 - 10.1021/ef800539g
DO - 10.1021/ef800539g
M3 - Journal article
VL - 22
JO - Energy & Fuels
JF - Energy & Fuels
SN - 0887-0624
IS - 6
ER -