Quantitative analysis of constituents in heavy fuel oil bytextlesssuptextgreater1textless/suptextgreaterH nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis

K.E. Nielsen, J. Dittmer, A. Malmendal, N.Chr. Nielsen

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

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.
OriginalsprogEngelsk
TidsskriftEnergy & Fuels
Vol/bind22
Udgave nummer6
ISSN0887-0624
DOI
StatusUdgivet - 2008

Citer dette

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title = "Quantitative analysis of constituents in heavy fuel oil bytextlesssuptextgreater1textless/suptextgreaterH nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis",
abstract = "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.",
author = "K.E. Nielsen and J. Dittmer and A. Malmendal and N.Chr. Nielsen",
year = "2008",
doi = "10.1021/ef800539g",
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volume = "22",
journal = "Energy & Fuels",
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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 tidsskriftTidsskriftartikelForskningpeer 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 -