592
R. W. Kessler and W. Kessler
59. M. Rey-Bayle, R. Bendoula, N. Caillol, J.-M. Roger, Multiangle near infrared spectroscopy
associated with common components and specific weights analysis for in line monitoring. J.
Near Infrared Spectro. 27, 134–146 (2019)
60. W. Kessler, D. Oelkrug, R.W. Kessler, Using scattering and absorption spectra as MCR-hard
model constraints for diffuse reflectance measurements of tablets. Anal. Chim. Acta 642, 127–
134 (2009)
61. E. Ostertag, M. Stefanakis, K. Rebner, R.W. Kessler, Elastic and inelastic light scattering
spectroscopy and its possible use for label-free brain tumor typing. Anal. Bioanal. Chem. 409,
6613–6623 (2017)
62. H. Chung, Applications of near-infrared spectroscopy in refineries and important issues to
address. Appl. Spectrosc. Rev. 42, 251–285 (2007)
63. K. Hidajat, S.M. Chong, Quality characterization of crude oils by partial least square calibration
of NIR spectral profiles. J. Near Infrared Spectro. 8, 53–59 (2000)
64. OMV Mediendatenbank, omv-mediadatabase.com, and https://www.omv.de/services/downlo
ads/00/omv.de/1522141187364/Raffineriebroschure_DE, Accessed 31 Oct 2019
65. D. Lambert, K. Benkhelil, B. Ribero, M. Valleur, Advanced crude management by NIR
spectroscopy combined with topology modelling, in Hydrocarbon Processing, July 2019,
Special Focus: The Digital Refinery, https://www.hydrocarbonprocessing.com/magazine/
2019/july-2019/special-focus-the-digital-refinery/advanced-crude-management-by-nir-spectr
oscopy-combined-with-topology-modeling. Accessed 10 Oct 2019
66. J.C.A. Alves, C.B. Henriques, R.J. Poppi, Near infrared spectroscopy combined with support
vector machines as a process analytical chemistry tool at petroleum refineries. NIR News 23(8),
8–10 (2012)
67. J. Workman Jr., A review of process near infrared spectroscopy: 1980–1994. J. Near Infrared
Spectro. 1, 221–245 (1993)
68. Z. Yuan, W. Qin, J. Zhao, Smart manufacturing for the oil refining and petrochemical industry.
Engineering 3, 179–182 (2017)
69. G. Socrates, Infrared and Raman Characteristic Group Frequencies: Tables and Charts, 3
(Wiley, NY, 2004) 978-0-470-09307-8
70. L.G. Weyer, S.-C. Lo, Handbook of Vibrational Spectroscopy, ed. By J.M. Chalmers, P. Griffiths
(John Wiley & Sons, Chichester, 2002)
71. T.I. Dearing, J.T. Wesley, C.E. Rechsteiner Jr., B.J. Marquardt, Characterization of crude oil
products using data fusion of process Raman, infrared, and nuclear magnetic resonance (NMR)
spectra. Appl. Spectro. 65, 181–186 (2011)
72. Z. Xu, C.E. Bunker, P.B. de Harrington, Classification of jet fuel properties by near-infrared
spectroscopy using fuzzy rule-building expert systems and support vector machines. Appl.
Spectro. 11, 1251–1258 (2010)
73. J.C.L. Alves, R.J. Poppi, Diesel oil quality parameter determinations using support vector
regression and near infrared spectroscopy for hydrotreating feedstock monitoring. J. Near
Infrared Spectro. 20, 419–425 (2012)
74. M.V. Reboucas, de B.B. Netob, Near infrared spectroscopic prediction of physical properties
of aromatics-rich hydrocarbon mixtures. J. Near Infrared Spectro. 9, 263–273 (2001)
75. G. Guchardi, da P.A.C. Filho, R.J. Poppi, C. Pasquini, Determination of ethanol and methyl
tert-butyl ether (MTBE) in gasoline by NIR–AOTF-based spectroscopy and multiple linear
regression with variables selected by genetic algorithm, J. Near Infrared Spectro. 6, 333–339
(1998)
76. H. Hasheminasab, Y. Gholipour, M. Kharrazi, D. Streimikiene, Life cycle approach in sustainability assessment for petroleum refinery projects with fuzzy-AHP. Energy Environ. 29,
1208–1223 (2018)
77. H.O.M.A. Moura, A.B.F. Câmara, M.C.D. Santos, C.L.M. Morais, L.A.S. de Lima, K.M.G.
Lima, L.S. de Carvalho, Advances in chemometric control of commercial diesel adulteration
by kerosene using IR spectroscopy. Anal. Bioanal. Chem. 411, 2301–2315 (2019)
78. J.C.L. Alves, R.J. Poppi, Quantification of hydrotreated vegetable oil and biodiesel contents in
diesel fuel blends using near infrared spectroscopy. NIR News 27, 4–7 (2016)
R. W. Kessler and W. Kessler
59. M. Rey-Bayle, R. Bendoula, N. Caillol, J.-M. Roger, Multiangle near infrared spectroscopy
associated with common components and specific weights analysis for in line monitoring. J.
Near Infrared Spectro. 27, 134–146 (2019)
60. W. Kessler, D. Oelkrug, R.W. Kessler, Using scattering and absorption spectra as MCR-hard
model constraints for diffuse reflectance measurements of tablets. Anal. Chim. Acta 642, 127–
134 (2009)
61. E. Ostertag, M. Stefanakis, K. Rebner, R.W. Kessler, Elastic and inelastic light scattering
spectroscopy and its possible use for label-free brain tumor typing. Anal. Bioanal. Chem. 409,
6613–6623 (2017)
62. H. Chung, Applications of near-infrared spectroscopy in refineries and important issues to
address. Appl. Spectrosc. Rev. 42, 251–285 (2007)
63. K. Hidajat, S.M. Chong, Quality characterization of crude oils by partial least square calibration
of NIR spectral profiles. J. Near Infrared Spectro. 8, 53–59 (2000)
64. OMV Mediendatenbank, omv-mediadatabase.com, and https://www.omv.de/services/downlo
ads/00/omv.de/1522141187364/Raffineriebroschure_DE, Accessed 31 Oct 2019
65. D. Lambert, K. Benkhelil, B. Ribero, M. Valleur, Advanced crude management by NIR
spectroscopy combined with topology modelling, in Hydrocarbon Processing, July 2019,
Special Focus: The Digital Refinery, https://www.hydrocarbonprocessing.com/magazine/
2019/july-2019/special-focus-the-digital-refinery/advanced-crude-management-by-nir-spectr
oscopy-combined-with-topology-modeling. Accessed 10 Oct 2019
66. J.C.A. Alves, C.B. Henriques, R.J. Poppi, Near infrared spectroscopy combined with support
vector machines as a process analytical chemistry tool at petroleum refineries. NIR News 23(8),
8–10 (2012)
67. J. Workman Jr., A review of process near infrared spectroscopy: 1980–1994. J. Near Infrared
Spectro. 1, 221–245 (1993)
68. Z. Yuan, W. Qin, J. Zhao, Smart manufacturing for the oil refining and petrochemical industry.
Engineering 3, 179–182 (2017)
69. G. Socrates, Infrared and Raman Characteristic Group Frequencies: Tables and Charts, 3
(Wiley, NY, 2004) 978-0-470-09307-8
70. L.G. Weyer, S.-C. Lo, Handbook of Vibrational Spectroscopy, ed. By J.M. Chalmers, P. Griffiths
(John Wiley & Sons, Chichester, 2002)
71. T.I. Dearing, J.T. Wesley, C.E. Rechsteiner Jr., B.J. Marquardt, Characterization of crude oil
products using data fusion of process Raman, infrared, and nuclear magnetic resonance (NMR)
spectra. Appl. Spectro. 65, 181–186 (2011)
72. Z. Xu, C.E. Bunker, P.B. de Harrington, Classification of jet fuel properties by near-infrared
spectroscopy using fuzzy rule-building expert systems and support vector machines. Appl.
Spectro. 11, 1251–1258 (2010)
73. J.C.L. Alves, R.J. Poppi, Diesel oil quality parameter determinations using support vector
regression and near infrared spectroscopy for hydrotreating feedstock monitoring. J. Near
Infrared Spectro. 20, 419–425 (2012)
74. M.V. Reboucas, de B.B. Netob, Near infrared spectroscopic prediction of physical properties
of aromatics-rich hydrocarbon mixtures. J. Near Infrared Spectro. 9, 263–273 (2001)
75. G. Guchardi, da P.A.C. Filho, R.J. Poppi, C. Pasquini, Determination of ethanol and methyl
tert-butyl ether (MTBE) in gasoline by NIR–AOTF-based spectroscopy and multiple linear
regression with variables selected by genetic algorithm, J. Near Infrared Spectro. 6, 333–339
(1998)
76. H. Hasheminasab, Y. Gholipour, M. Kharrazi, D. Streimikiene, Life cycle approach in sustainability assessment for petroleum refinery projects with fuzzy-AHP. Energy Environ. 29,
1208–1223 (2018)
77. H.O.M.A. Moura, A.B.F. Câmara, M.C.D. Santos, C.L.M. Morais, L.A.S. de Lima, K.M.G.
Lima, L.S. de Carvalho, Advances in chemometric control of commercial diesel adulteration
by kerosene using IR spectroscopy. Anal. Bioanal. Chem. 411, 2301–2315 (2019)
78. J.C.L. Alves, R.J. Poppi, Quantification of hydrotreated vegetable oil and biodiesel contents in
diesel fuel blends using near infrared spectroscopy. NIR News 27, 4–7 (2016)