Recent advances in renewable hydrogen production by thermo-catalytic conversion of biomass-derived glycerol: Overview of prospects and challenges

Ayodele, Bamidele Victor; Abdullah, Tuan Ab Rashid Bin Tuan; Alsaffar, May Ali; Mustapa, Siti Indati; Salleh, Siti Fatihah

doi:10.1016/j.ijhydene.2019.08.002

Cited by 33 publications

(13 citation statements)

References 130 publications

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“…16 Recently, there is an increasing interest in the utilization of bio-oil and glycerol for hydrogen production. [17][18][19] Bio-oil and glycerol are by-products of pyrolysis of biomass and biodiesel production and can be sustainably utilized for producing hydrogen by steam reforming technique. 20,21 One major challenge in the bio-oil and glycerol steam reforming to hydrogen is the complexity of the reaction.…”

Section: Introductionmentioning

confidence: 99%

Modeling the effect of non‐linear process parameters on the prediction of hydrogen production by steam reforming of bio‐oil and glycerol using artificial neural network

2020

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Biomass-derived substrates such as bio-oil and glycerol are gaining wide acceptability as feedstocks to produce hydrogen using a steam reforming process. The wide acceptability can be attributed to a huge amount of glycerol and bio-oil obtained as by-products of biodiesel production and pyrolysis processes. Several parameters have been reported to affect the production of hydrogen by biomass steam reforming. This study investigates the effect of non-linear process parameters on the prediction of hydrogen production by biomass (bio-oil and glycerol) steam reforming using artificial neural network (ANN) modeling technique. Twenty different multilayer ANN model architectures were tested using datasets obtained from the bio-oil and glycerol steam reforming. Two algorithms namely Levenberg-Marquardt and Bayesian regularization were employed for the training of the ANNs. An optimized network configuration consisting of 3 input layer 14 hidden neurons, 1 output layer, and 3 input layer, 5 hidden neurons, and 1 output layer were obtained for the Levenberg-Marquardt and Bayesian regularization trained network, respectively for hydrogen production by bio-oil steam reforming. While an optimized network configuration consisting of 5 input nodes, 9 hidden neurons, 1 output node, and 5 input nodes, 8 hidden neurons, and 1 output node were obtained for Levenberg-Marquardt and Bayesian regularization trained network, respectively for hydrogen production by glycerol steam reforming. Based on the optimized network, the predicted hydrogen production from the bio-oil and glycerol steam agreed with the actual values with the coefficient of determination (R 2) > 0.9. A low mean square error of 3.024 × 10 −24 and 6.22 × 10 −15 for the optimized for Levenberg-Marquardt and Bayesian regularization-trained ANN, respectively. The neural network analyses of the two processes showed that reaction temperature and glycerol-to-water molar ratio were the most relevant factors that influenced the production of hydrogen by bio-oil and glycerol steam reforming, respectively. This study has demonstrated the robustness of the ANN as a technique for investigating the effect of non-linear process parameters on hydrogen production by bio-oil and glycerol steam reforming.

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Section: Introductionmentioning

confidence: 99%

Modeling the effect of non‐linear process parameters on the prediction of hydrogen production by steam reforming of bio‐oil and glycerol using artificial neural network

2020

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“…In comparison with the biomass gasification process, biomass reforming offers the advantages of producing a purer syngas. However, technical issues such as catalyst deactivation by carbon deposition and sintering, high energy requirement, and lack of understanding of the deactivation mechanisms have been identified as major constraints of the biomass reforming process (Ayodele et al, 2019). Appropriate catalyst design, kinetics of the biomass reforming reaction and optimization of the process conditions have been proposed as means of overcoming these challenges.…”

Section: Biomass Reformingmentioning

confidence: 99%

A Mini-Review on Hydrogen-Rich Syngas Production by Thermo-Catalytic and Bioconversion of Biomass and Its Environmental Implications

et al. 2019

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The thermo-catalytic and biochemical conversion of biomass to hydrogen-rich syngas has been widely reported with less emphasis on the environmental implications of the processes. This mini-review presents an overview of different thermo-catalytic route of converting biomass to hydrogen-rich syngas as well as their environmental impact investigated using life cycle assessment methodology. The review revealed that most of the authors employed, biomass gasification, biomass pyrolysis, reforming and fermentative processes for the hydrogen-rich syngas production. Global warming potential was observed as the most significant environmental impact reported in the reviewed articles. The CO 2 equivalent emissions were found to varies with each of the processes and the type of feedstock used. Trends from literature shows that both thermo-catalytic and biochemical processes have competitive advantages and potential to compete favorable with the existing technology used for hydrogen production. Nevertheless, it cannot be ascertained that these technologies should be excluded from environmental burdens. This mini-review could be a quick guide to future research interest in environmental impact of hydrogen-rich syngas production by thermo-catalytic and biochemical conversion of biomass.

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“…As glycerol (C 3 H 8 O 3 ) is a polyol with three hydroxyl groups, it may be possible to utilize it in a plethora of industrial platforms (Bagheri et al [9] has provided an excellent review on the different technological pathways that are currently being developed) however, the pressing need for further 'greening' of the energy sector, means that its conversion to hydrogen via thermochemical processes (i.e., via pyrolysis or different reforming reactions) is perhaps the most attractive option [10][11][12][13]. As is widely accepted, hydrogen is an efficient energy carrier that can provide clean power in stationary, portable and transport applications [14,15].…”

Section: Introductionmentioning

confidence: 99%

“…C 3 H 8 O 3 decomposition occurs at temperatures exceeding 300 • C and can involve different parallel and/or consecutive steps, which not only include the cleavage of the C-C and C-O bonds, but also dehydration, dehydrogenation, hydrogenation, isomerisation and polymerisation reactions [16,17]. Additionally, depending on the operating conditions and/or the catalytic system under consideration, a number of other reactions may also parallelly occur, such as, CO methanation (Equation (4)), CO disproportionation (Equation (5)), methane reforming (Equations (6) and (7)) carbon formation (Equations (8)-(10)), methanation of glycerol (Equation (11)) and direct glycerol decomposition (Equation (12)) [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Noble Metal (M: Ir, Pt, Pd) on M/Ce2O3-γ-Al2O3 Catalysts for Hydrogen Production via the Steam Reforming of Glycerol

et al. 2020

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A promising route for the energetic valorisation of the main by-product of the biodiesel industry is the steam reforming of glycerol, as it can theoretically produce seven moles of H2 for every mole of C3H8O3. In the work presented herein, CeO2–Al2O3 was used as supporting material for Ir, Pd and Pt catalysts, which were prepared using the incipient wetness impregnation technique and characterized by employing N2 adsorption–desorption, X-Ray Diffraction (XRD), Temperature Programmed Reduction (TPR), Temperature Programmed Desorption (TPD), X-ray Photoelectron Spectroscopy (XPS) and Transmission Electron Microscopy (TEM). The catalytic experiments aimed at identifying the effect of temperature on the total conversion of glycerol, on the conversion of glycerol to gaseous products, the selectivity towards the gaseous products (H2, CO2, CO, CH4) and the determination of the H2/CO and CO/CO2 molar ratios. The main liquid effluents produced during the reaction were quantified. The results revealed that the Pt/CeAl catalyst was more selective towards H2, which can be related to its increased number of Brønsted acid sites, which improved the hydrogenolysis and dehydrogenation–dehydration of condensable intermediates. The time-on-stream experiments, undertaken at low Water Glycerol Feed Ratios (WGFR), showed gradual deactivation for all catalysts. This is likely due to the dehydration reaction, which leads to the formation of unsaturated hydrocarbon species and eventually to carbon deposition. The weak metal–support interaction shown for the Ir/CeAl catalyst also led to pronounced sintering of the metallic particles.

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Recent advances in renewable hydrogen production by thermo-catalytic conversion of biomass-derived glycerol: Overview of prospects and challenges

Cited by 33 publications

References 130 publications

Modeling the effect of non‐linear process parameters on the prediction of hydrogen production by steam reforming of bio‐oil and glycerol using artificial neural network

Modeling the effect of non‐linear process parameters on the prediction of hydrogen production by steam reforming of bio‐oil and glycerol using artificial neural network

A Mini-Review on Hydrogen-Rich Syngas Production by Thermo-Catalytic and Bioconversion of Biomass and Its Environmental Implications

The Effect of Noble Metal (M: Ir, Pt, Pd) on M/Ce2O3-γ-Al2O3 Catalysts for Hydrogen Production via the Steam Reforming of Glycerol

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