Jet fuel density via GC × GC-FID
Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Vozka, Petr [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019transfer abstract |
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| Schlagwörter: |
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| Umfang: |
9 |
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| Übergeordnetes Werk: |
Enthalten in: Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias - Yang, Chaoqiang ELSEVIER, 2018, the science and technology of fuel and energy, New York, NY [u.a.] |
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| Übergeordnetes Werk: |
volume:235 ; year:2019 ; day:1 ; month:01 ; pages:1052-1060 ; extent:9 |
| Links: |
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| DOI / URN: |
10.1016/j.fuel.2018.08.110 |
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ELV044314167 |
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| 520 | |a Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. | ||
| 520 | |a Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. | ||
| 650 | 7 | |a Alternative jet fuel |2 Elsevier | |
| 650 | 7 | |a Weighted average |2 Elsevier | |
| 650 | 7 | |a PLS |2 Elsevier | |
| 650 | 7 | |a GC × GC |2 Elsevier | |
| 650 | 7 | |a SVM |2 Elsevier | |
| 650 | 7 | |a Jet fuel |2 Elsevier | |
| 650 | 7 | |a Fuel density |2 Elsevier | |
| 700 | 1 | |a Modereger, Brent A. |4 oth | |
| 700 | 1 | |a Park, Anthony C. |4 oth | |
| 700 | 1 | |a Zhang, Wan Tang Jeff |4 oth | |
| 700 | 1 | |a Trice, Rodney W. |4 oth | |
| 700 | 1 | |a Kenttämaa, Hilkka I. |4 oth | |
| 700 | 1 | |a Kilaz, Gozdem |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Yang, Chaoqiang ELSEVIER |t Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias |d 2018 |d the science and technology of fuel and energy |g New York, NY [u.a.] |w (DE-627)ELV000307122 |
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10.1016/j.fuel.2018.08.110 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001213.pica (DE-627)ELV044314167 (ELSEVIER)S0016-2361(18)31481-9 DE-627 ger DE-627 rakwb eng 530 600 670 VZ 51.00 bkl Vozka, Petr verfasserin aut Jet fuel density via GC × GC-FID 2019transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Alternative jet fuel Elsevier Weighted average Elsevier PLS Elsevier GC × GC Elsevier SVM Elsevier Jet fuel Elsevier Fuel density Elsevier Modereger, Brent A. oth Park, Anthony C. oth Zhang, Wan Tang Jeff oth Trice, Rodney W. oth Kenttämaa, Hilkka I. oth Kilaz, Gozdem oth Enthalten in Elsevier Yang, Chaoqiang ELSEVIER Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias 2018 the science and technology of fuel and energy New York, NY [u.a.] (DE-627)ELV000307122 volume:235 year:2019 day:1 month:01 pages:1052-1060 extent:9 https://doi.org/10.1016/j.fuel.2018.08.110 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 235 2019 1 0101 1052-1060 9 |
| spelling |
10.1016/j.fuel.2018.08.110 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001213.pica (DE-627)ELV044314167 (ELSEVIER)S0016-2361(18)31481-9 DE-627 ger DE-627 rakwb eng 530 600 670 VZ 51.00 bkl Vozka, Petr verfasserin aut Jet fuel density via GC × GC-FID 2019transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Alternative jet fuel Elsevier Weighted average Elsevier PLS Elsevier GC × GC Elsevier SVM Elsevier Jet fuel Elsevier Fuel density Elsevier Modereger, Brent A. oth Park, Anthony C. oth Zhang, Wan Tang Jeff oth Trice, Rodney W. oth Kenttämaa, Hilkka I. oth Kilaz, Gozdem oth Enthalten in Elsevier Yang, Chaoqiang ELSEVIER Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias 2018 the science and technology of fuel and energy New York, NY [u.a.] (DE-627)ELV000307122 volume:235 year:2019 day:1 month:01 pages:1052-1060 extent:9 https://doi.org/10.1016/j.fuel.2018.08.110 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 235 2019 1 0101 1052-1060 9 |
| allfields_unstemmed |
10.1016/j.fuel.2018.08.110 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001213.pica (DE-627)ELV044314167 (ELSEVIER)S0016-2361(18)31481-9 DE-627 ger DE-627 rakwb eng 530 600 670 VZ 51.00 bkl Vozka, Petr verfasserin aut Jet fuel density via GC × GC-FID 2019transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Alternative jet fuel Elsevier Weighted average Elsevier PLS Elsevier GC × GC Elsevier SVM Elsevier Jet fuel Elsevier Fuel density Elsevier Modereger, Brent A. oth Park, Anthony C. oth Zhang, Wan Tang Jeff oth Trice, Rodney W. oth Kenttämaa, Hilkka I. oth Kilaz, Gozdem oth Enthalten in Elsevier Yang, Chaoqiang ELSEVIER Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias 2018 the science and technology of fuel and energy New York, NY [u.a.] (DE-627)ELV000307122 volume:235 year:2019 day:1 month:01 pages:1052-1060 extent:9 https://doi.org/10.1016/j.fuel.2018.08.110 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 235 2019 1 0101 1052-1060 9 |
| allfieldsGer |
10.1016/j.fuel.2018.08.110 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001213.pica (DE-627)ELV044314167 (ELSEVIER)S0016-2361(18)31481-9 DE-627 ger DE-627 rakwb eng 530 600 670 VZ 51.00 bkl Vozka, Petr verfasserin aut Jet fuel density via GC × GC-FID 2019transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Alternative jet fuel Elsevier Weighted average Elsevier PLS Elsevier GC × GC Elsevier SVM Elsevier Jet fuel Elsevier Fuel density Elsevier Modereger, Brent A. oth Park, Anthony C. oth Zhang, Wan Tang Jeff oth Trice, Rodney W. oth Kenttämaa, Hilkka I. oth Kilaz, Gozdem oth Enthalten in Elsevier Yang, Chaoqiang ELSEVIER Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias 2018 the science and technology of fuel and energy New York, NY [u.a.] (DE-627)ELV000307122 volume:235 year:2019 day:1 month:01 pages:1052-1060 extent:9 https://doi.org/10.1016/j.fuel.2018.08.110 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 235 2019 1 0101 1052-1060 9 |
| allfieldsSound |
10.1016/j.fuel.2018.08.110 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001213.pica (DE-627)ELV044314167 (ELSEVIER)S0016-2361(18)31481-9 DE-627 ger DE-627 rakwb eng 530 600 670 VZ 51.00 bkl Vozka, Petr verfasserin aut Jet fuel density via GC × GC-FID 2019transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. Alternative jet fuel Elsevier Weighted average Elsevier PLS Elsevier GC × GC Elsevier SVM Elsevier Jet fuel Elsevier Fuel density Elsevier Modereger, Brent A. oth Park, Anthony C. oth Zhang, Wan Tang Jeff oth Trice, Rodney W. oth Kenttämaa, Hilkka I. oth Kilaz, Gozdem oth Enthalten in Elsevier Yang, Chaoqiang ELSEVIER Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias 2018 the science and technology of fuel and energy New York, NY [u.a.] (DE-627)ELV000307122 volume:235 year:2019 day:1 month:01 pages:1052-1060 extent:9 https://doi.org/10.1016/j.fuel.2018.08.110 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 235 2019 1 0101 1052-1060 9 |
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English |
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Enthalten in Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias New York, NY [u.a.] volume:235 year:2019 day:1 month:01 pages:1052-1060 extent:9 |
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Enthalten in Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias New York, NY [u.a.] volume:235 year:2019 day:1 month:01 pages:1052-1060 extent:9 |
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Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias |
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Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. |
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Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. |
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Aviation jet fuels contain over a thousand different hydrocarbons, making the prediction of their properties from chemical composition difficult. The density of a jet fuel at 15 °C is necessary for its certification. We present here an analytical approach for the determination of the density of jet fuels based on the chemical composition of the fuel determined via comprehensive two-dimensional gas chromatography with flame ionization detector (GC × GC-FID). The analysis was carried out using two-dimensional gas chromatography with electron ionization high-resolution time-of-flight mass spectrometry detection (GC × GC-TOF/MS) and flame ionization detection (GC × GC-FID). A detailed chemical composition analysis was performed on 50 samples, including petroleum-based aviation fuels and all approved alternative aviation fuel blending components. Fuel constituents were classified into seven hydrocarbon classes (n-paraffins, isoparaffins, monocycloparaffins, di- and tricycloparaffins, alkylbenzenes, cycloaromatic compounds, and alkylnaphthalenes) with the number of carbons in the range of 7–20. Several correlation algorithms and approaches were explored, including partial least squares regression (PLS) and support vector machines method (SVM), which yielded the most accurate results with mean absolute percentage errors of 0.1740% and 0.0984%, respectively. All used methods were validated utilizing uncalibrated validation samples. |
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