The Experts below are selected from a list of 156 Experts worldwide ranked by ideXlab platform
Iskender Gökalp - One of the best experts on this subject based on the ideXlab platform.
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Catalytic gasification of light and heavy gas oils in supercritical water
Journal of the Energy Institute, 2020Co-Authors: Rachita Rana, Sonil Nanda, Janusz A. Kozinski, Sivamohan Reddy, Ajay Dalai, Iskender GökalpAbstract:Canada has the third-largest oil sand reserves in the world as a result of which, it generates considerable amounts of light gas oil and heavy gas oil through Petroleum Distillation. With the escalating energy demands, it has become essential to explore alternative fuel resources from biomass and petrochemical residues. This study explores the potential of supercritical water gasification to transform light and heavy gas oils to hydrogen-rich syngas through the optimization of process conditions such as temperature (375e675 C), feed concentration (20e35 wt%) and reaction time (30e75 min). Nickel-supported functionalized carbon nanotubes (10%Ni/FCNT) were synthesized for application in catalytic supercritical water gasification. The functionalization of carbon nanotubes resulted in an increase in their surface area from 108 m2/g (in pristine CNT) to 127 m2/g (in FCNT) and 122 m2/g (in 10%Ni/FCNT). The impregnation of catalytic nickel particles onto carbon nanotubes was confirmed through X-ray diffraction (XDR) and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS). Fouriertransform infrared (FTIR) spectroscopy of both gas oils revealed the presence of aliphatics, alkyl-aryl ethers and sulfur-containing compounds among several other aromatics. Light gas oil revealed higher hydrogen yields of 3.32 mol/kg compared to that of heavy gas oil (2.79 mol/kg) at optimal process conditions, i.e. 675 C and 75 min, 20 wt% feed concentration. However, 10%Ni/FCNT enhanced hydrogen yields (4.46 mol/kg), total gas yield (9.22 mol/kg), hydrogen selectivity (94%) and lower heating value (1685 MJ/kg) of product gases obtained from light gas oil in contrast to heavy gas oil. This study indicates a tremendous potential of gas oils for hydrogen generation via hydrothermal gasification.
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Catalytic gasification of light and heavy gas oils in supercritical water
Journal of the Energy Institute, 2020Co-Authors: Rachita Rana, Ajay K. Dalai, Sonil Nanda, Sivamohan N. Reddy, Janusz A. Kozinski, Iskender GökalpAbstract:Abstract Canada has the third-largest oil sand reserves in the world as a result of which, it generates considerable amounts of light gas oil and heavy gas oil through Petroleum Distillation. With the escalating energy demands, it has become essential to explore alternative fuel resources from biomass and petrochemical residues. This study explores the potential of supercritical water gasification to transform light and heavy gas oils to hydrogen-rich syngas through the optimization of process conditions such as temperature (375–675 °C), feed concentration (20–35 wt%) and reaction time (30–75 min). Nickel-supported functionalized carbon nanotubes (10%Ni/FCNT) were synthesized for application in catalytic supercritical water gasification. The functionalization of carbon nanotubes resulted in an increase in their surface area from 108 m2/g (in pristine CNT) to 127 m2/g (in FCNT) and 122 m2/g (in 10%Ni/FCNT). The impregnation of catalytic nickel particles onto carbon nanotubes was confirmed through X-ray diffraction (XDR) and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS). Fourier-transform infrared (FTIR) spectroscopy of both gas oils revealed the presence of aliphatics, alkyl-aryl ethers and sulfur-containing compounds among several other aromatics. Light gas oil revealed higher hydrogen yields of 3.32 mol/kg compared to that of heavy gas oil (2.79 mol/kg) at optimal process conditions, i.e. 675 °C and 75 min, 20 wt% feed concentration. However, 10%Ni/FCNT enhanced hydrogen yields (4.46 mol/kg), total gas yield (9.22 mol/kg), hydrogen selectivity (94%) and lower heating value (1685 MJ/kg) of product gases obtained from light gas oil in contrast to heavy gas oil. This study indicates a tremendous potential of gas oils for hydrogen generation via hydrothermal gasification.
Erico M.m. Flores - One of the best experts on this subject based on the ideXlab platform.
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Total sulfur determination in residues of crude oil Distillation using FT-IR/ATR and variable selection methods.
Spectrochimica acta. Part A Molecular and biomolecular spectroscopy, 2011Co-Authors: Aline L. H. Muller, Marco Flôres Ferrão, Edson I. Muller, Maria De Fátima Pereira Dos Santos, Regina C. L. Guimarães, Rochele S. Picoloto, Paola A. Mello, Erico M.m. FloresAbstract:Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from Petroleum Distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm(-1)). This model produced a RMSECV of 400 mg kg(-1) S and RMSEP of 420 mg kg(-1) S, showing a correlation coefficient of 0.990.
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Total Acid Number Determination in Residues of Crude Oil Distillation Using ATR-FTIR and Variable Selection by Chemometric Methods
Energy & Fuels, 2010Co-Authors: Graciele Parisotto, Marco Flôres Ferrão, Aline L. H. Muller, Edson I. Muller, Maria De Fátima Pereira Dos Santos, Regina C. L. Guimarães, Julio C. M. Dias, Erico M.m. FloresAbstract:The total acid number (TAN) was determined in the atmospheric residue (AR) and vacuum residue (VR) of the Petroleum Distillation process using mid-infrared spectroscopy with attenuated total reflection in association with chemometric methods. Calibration and prediction sets consisted of 44 and 13 samples, respectively (16 AR samples and 41 VR samples). Calibration models were developed using three variable-selection models: interval partial least squares (iPLS), synergy interval partial least squares (siPLS), and backward interval partial least squares (biPLS). Different treatments and preprocessing steps were also evaluated for development of the models. The treatment based on the first derivative with a Savitzky−Golay filter and the mean centered was selected for model construction. A root-mean-square error of prediction of 0.164 mg g−1 of KOH was achieved using the biPLS algorithm with spectra divided into 20 intervals and combinations of 5 intervals (2992−2826, 1823−1657, 1656−1490, 1489−1323, and 821...
Rachita Rana - One of the best experts on this subject based on the ideXlab platform.
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Catalytic gasification of light and heavy gas oils in supercritical water
Journal of the Energy Institute, 2020Co-Authors: Rachita Rana, Sonil Nanda, Janusz A. Kozinski, Sivamohan Reddy, Ajay Dalai, Iskender GökalpAbstract:Canada has the third-largest oil sand reserves in the world as a result of which, it generates considerable amounts of light gas oil and heavy gas oil through Petroleum Distillation. With the escalating energy demands, it has become essential to explore alternative fuel resources from biomass and petrochemical residues. This study explores the potential of supercritical water gasification to transform light and heavy gas oils to hydrogen-rich syngas through the optimization of process conditions such as temperature (375e675 C), feed concentration (20e35 wt%) and reaction time (30e75 min). Nickel-supported functionalized carbon nanotubes (10%Ni/FCNT) were synthesized for application in catalytic supercritical water gasification. The functionalization of carbon nanotubes resulted in an increase in their surface area from 108 m2/g (in pristine CNT) to 127 m2/g (in FCNT) and 122 m2/g (in 10%Ni/FCNT). The impregnation of catalytic nickel particles onto carbon nanotubes was confirmed through X-ray diffraction (XDR) and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS). Fouriertransform infrared (FTIR) spectroscopy of both gas oils revealed the presence of aliphatics, alkyl-aryl ethers and sulfur-containing compounds among several other aromatics. Light gas oil revealed higher hydrogen yields of 3.32 mol/kg compared to that of heavy gas oil (2.79 mol/kg) at optimal process conditions, i.e. 675 C and 75 min, 20 wt% feed concentration. However, 10%Ni/FCNT enhanced hydrogen yields (4.46 mol/kg), total gas yield (9.22 mol/kg), hydrogen selectivity (94%) and lower heating value (1685 MJ/kg) of product gases obtained from light gas oil in contrast to heavy gas oil. This study indicates a tremendous potential of gas oils for hydrogen generation via hydrothermal gasification.
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Catalytic gasification of light and heavy gas oils in supercritical water
Journal of the Energy Institute, 2020Co-Authors: Rachita Rana, Ajay K. Dalai, Sonil Nanda, Sivamohan N. Reddy, Janusz A. Kozinski, Iskender GökalpAbstract:Abstract Canada has the third-largest oil sand reserves in the world as a result of which, it generates considerable amounts of light gas oil and heavy gas oil through Petroleum Distillation. With the escalating energy demands, it has become essential to explore alternative fuel resources from biomass and petrochemical residues. This study explores the potential of supercritical water gasification to transform light and heavy gas oils to hydrogen-rich syngas through the optimization of process conditions such as temperature (375–675 °C), feed concentration (20–35 wt%) and reaction time (30–75 min). Nickel-supported functionalized carbon nanotubes (10%Ni/FCNT) were synthesized for application in catalytic supercritical water gasification. The functionalization of carbon nanotubes resulted in an increase in their surface area from 108 m2/g (in pristine CNT) to 127 m2/g (in FCNT) and 122 m2/g (in 10%Ni/FCNT). The impregnation of catalytic nickel particles onto carbon nanotubes was confirmed through X-ray diffraction (XDR) and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS). Fourier-transform infrared (FTIR) spectroscopy of both gas oils revealed the presence of aliphatics, alkyl-aryl ethers and sulfur-containing compounds among several other aromatics. Light gas oil revealed higher hydrogen yields of 3.32 mol/kg compared to that of heavy gas oil (2.79 mol/kg) at optimal process conditions, i.e. 675 °C and 75 min, 20 wt% feed concentration. However, 10%Ni/FCNT enhanced hydrogen yields (4.46 mol/kg), total gas yield (9.22 mol/kg), hydrogen selectivity (94%) and lower heating value (1685 MJ/kg) of product gases obtained from light gas oil in contrast to heavy gas oil. This study indicates a tremendous potential of gas oils for hydrogen generation via hydrothermal gasification.
P. Dauge - One of the best experts on this subject based on the ideXlab platform.
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High-pressure dynamic viscosity and density of two synthetic hydrocarbon mixtures representative of some heavy Petroleum Distillation cuts
Fluid Phase Equilibria, 2003Co-Authors: Christian Boned, C. K. Zéberg-mikkelsen, Antoine Baylaucq, P. DaugeAbstract:Abstract The dynamic viscosity and density of two hydrocarbon mixtures representative of some heavy Petroleum Distillation cuts at 515 K have been studied in the temperature range 293.15–353.15 K and up to 100 MPa. The pure hydrocarbons used are n-tridecane, 2,2,4,4,6,8,8-heptamethylnonane, heptylcyclohexane, heptylbenzene, and 1-methylnaphthalene. The normal boiling point of these five compounds are 508.0, 513.1, 518.1, 519.1 and 515.0 K, respectively. The studied mixtures contain respectively three hydrocarbons (n-tridecane, heptylcyclohexane, heptylbenzene) and five hydrocarbons. The viscosity was measured with a falling-body viscometer, except at atmospheric pressure, where a classical capillary viscometer was used. The experimental uncertainty for the dynamic viscosity is 2%, except at atmospheric pressure, where the uncertainty is 1%. For the density, the uncertainty is less than 1 kg m−3. The viscosity data obtained for the two mixtures (84 experimental points) have been used to evaluate the performance of seven different representative models, applicable to hydrocarbon fluids, incorporating the effects of temperature, pressure and composition. The evaluated models are based on the classical mixing laws, the self-referencing model, the hard-sphere scheme, the free-volume viscosity model, the friction theory, and the Lohrenz–Bray–Clark (LBC) correlation. It follows from the discussion that some of the schemes are able to predict the viscosity of these two mixtures being simple representations of some Petroleum Distillation cuts at 515 K. This work shows the potential extension of these viscosity approaches to real Petroleum fluids. In addition, using the experimental densities, the variation of the internal pressure versus temperature and pressure for the two synthetic hydrocarbon mixtures has been evaluated.
Aline L. H. Muller - One of the best experts on this subject based on the ideXlab platform.
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Total sulfur determination in residues of crude oil Distillation using FT-IR/ATR and variable selection methods.
Spectrochimica acta. Part A Molecular and biomolecular spectroscopy, 2011Co-Authors: Aline L. H. Muller, Marco Flôres Ferrão, Edson I. Muller, Maria De Fátima Pereira Dos Santos, Regina C. L. Guimarães, Rochele S. Picoloto, Paola A. Mello, Erico M.m. FloresAbstract:Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from Petroleum Distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm(-1)). This model produced a RMSECV of 400 mg kg(-1) S and RMSEP of 420 mg kg(-1) S, showing a correlation coefficient of 0.990.
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Total Acid Number Determination in Residues of Crude Oil Distillation Using ATR-FTIR and Variable Selection by Chemometric Methods
Energy & Fuels, 2010Co-Authors: Graciele Parisotto, Marco Flôres Ferrão, Aline L. H. Muller, Edson I. Muller, Maria De Fátima Pereira Dos Santos, Regina C. L. Guimarães, Julio C. M. Dias, Erico M.m. FloresAbstract:The total acid number (TAN) was determined in the atmospheric residue (AR) and vacuum residue (VR) of the Petroleum Distillation process using mid-infrared spectroscopy with attenuated total reflection in association with chemometric methods. Calibration and prediction sets consisted of 44 and 13 samples, respectively (16 AR samples and 41 VR samples). Calibration models were developed using three variable-selection models: interval partial least squares (iPLS), synergy interval partial least squares (siPLS), and backward interval partial least squares (biPLS). Different treatments and preprocessing steps were also evaluated for development of the models. The treatment based on the first derivative with a Savitzky−Golay filter and the mean centered was selected for model construction. A root-mean-square error of prediction of 0.164 mg g−1 of KOH was achieved using the biPLS algorithm with spectra divided into 20 intervals and combinations of 5 intervals (2992−2826, 1823−1657, 1656−1490, 1489−1323, and 821...