Recent development of biomass gasification for H2 rich gas production

Song, Hao; Yang, Guangchao; Xue, Peixuan; Li, Yuchen; Zou, Jun; Wang, Shurong; Yang, Haiping; Chen, Hanping

doi:10.1016/j.jaecs.2022.100059

Cited by 59 publications

(27 citation statements)

References 163 publications

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“…Experimentally, it is wellknown that gasification temperature (T ) is one of the most relevant variables for the gasification process outcomes. 33,34 It is encouraging that our model correctly indeed identifies T as one of the most important features. The SHAP plot for the H 2 concentration (Fig.…”

Section: Feature Importance Analysissupporting

confidence: 55%

Biomass to energy: A machine learning model for optimum gasification pathways

Gil

Jablonka

García³

et al. 2023

Preprint

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Biomass is a highly versatile renewable resource for decarbonizing energy systems. Gasification is a promising conversion technology that can transform biomass into multiple energy carriers to produce heat, electricity, biofuels, or chemicals. At present, identifying the best gasification route for a given biomass relies on trial and error, time-consuming experimentation that, given the wide range of biomass feedstocks available, slows down the deployment of the technology. Here we develop a supervised machine-learning model to find the optimal application of a particular biomass in gasification processes. Our model can select the suitable gasification pathway from the characteristics of the biomass, and also identify the optimal operating conditions for a selected application of the produced gas. In addition, with this model, we can obtain insights into the relationships between biomass properties and gasification results, leading to a better understanding of the process. A relevant aspect of this work is that these results rely on a relatively small dataset, representative of those typically collected by research groups using different types of gasifiers worldwide. This study opens the path for future integration of such data, which would allow addressing the complexity of biomass and conversion process simultaneously. With this work, we aim to increase the flexibility of biomass gasification processes and promote the development of bioenergy technologies, considered crucial in the energy transition context.

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Section: Feature Importance Analysissupporting

confidence: 55%

Biomass to energy: A machine learning model for optimum gasification pathways

Gil

Jablonka

García³

et al. 2023

Preprint

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show abstract

“…On the other hand, H 2 O and CO 2 are also employed as gasifying agents leading to higher H 2 and CO concentrations in the gasification products. 3 , 5 − 8 To sum up, according to the literature, the approximate composition of a producer gas obtained with different gasifying agents is depicted in Table 1 .…”

Section: Introductionmentioning

confidence: 99%

“…In this sense, running the gasifier with pure O 2 solves this issue, although it also increases remarkably the operating costs due to pure O 2 production typically achieved through energy-intensive cryogenic distillation. On the other hand, H 2 O and CO 2 are also employed as gasifying agents leading to higher H 2 and CO concentrations in the gasification products. ,− To sum up, according to the literature, the approximate composition of a producer gas obtained with different gasifying agents is depicted in Table .…”

Section: Introductionmentioning

confidence: 99%

Catalytic Upgrading of Biomass-Gasification Mixtures Using Ni-Fe/MgAl₂O₄ as a Bifunctional Catalyst

et al. 2022

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Biomass gasification streams typically contain a mixture of CO, H 2 , CH 4 , and CO 2 as the majority components and frequently require conditioning for downstream processes. Herein, we investigate the catalytic upgrading of surrogate biomass gasifiers through the generation of syngas. Seeking a bifunctional system capable of converting CO 2 and CH 4 to CO, a reverse water gas shift (RWGS) catalyst based on Fe/MgAl 2 O 4 was decorated with an increasing content of Ni metal and evaluated for producing syngas using different feedstock compositions. This approach proved efficient for gas upgrading, and the incorporation of adequate Ni content increased the CO content by promoting the RWGS and dry reforming of methane (DRM) reactions. The larger CO productivity attained at high temperatures was intimately associated with the generation of FeNi 3 alloys. Among the catalysts’ series, Ni-rich catalysts favored the CO productivity in the presence of CH 4 , but important carbon deposition processes were noticed. On the contrary, 2Ni-Fe/MgAl 2 O 4 resulted in a competitive and cost-effective system delivering large amounts of CO with almost no coke deposits. Overall, the incorporation of a suitable realistic application for valorization of variable composition of biomass-gasification derived mixtures obtaining a syngas-rich stream thus opens new routes for biosyngas production and upgrading.

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“…AAEMs as catalysts also regulated the biomass pyrolysis process to increase the hydrogen yield [ 12 ]. Hao Song et al [ 13 ] further summarized the key factors affecting hydrogen production from biomass pyrolysis. It indicated that calcium-based catalysts had a significant impact on increasing the hydrogen yield and inhibiting the formation of CO 2 .…”

Section: Introductionmentioning

confidence: 99%

Catalytic Pyrolysis of Sawdust with Desulfurized Fly Ash for Pyrolysis Gas Upgrading

Song

Tang

et al. 2022

IJERPH

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In this study, the catalytic effects of desulfurized fly ash (DFA) on the gaseous products of sawdust (SD) pyrolysis were investigated in a tubular furnace. The results indicated that DFA catalyzed the process of SD decomposition to improve the hydrogen content and the calorific value of pyrolysis gas. As to its effect on pyrolysis products, DFA increased the non-oxide content of CH4, C3H4, and H2 in pyrolysis gas by 1.4-, 1.8-, and 2.3-fold, respectively. Meanwhile, the catalytic effect of DFA reduced the CO and CO2 yields during DFA/SD pyrolysis. Based on the model compound method, CaSO3 and Ca(OH)2 in DFA was proved to have quite different catalytic effects on pyrolysis gas components. Ca(OH)2 accelerated the formation of CH4 and H2 through the cracking of methoxyl during lignin and cellulose degradation, while CaSO3 favored the generation of CO and CO2 due to the carbonyl and carboxyl of lignin in SD. CaSO3 also catalyzed SD pyrolysis to promote the C3H4 yield in pyrolysis gas. Overall, the catalytic pyrolysis of SD with DFA yielded negative-carbon emission, which upgraded the quality of the pyrolysis gas.

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Recent development of biomass gasification for H2 rich gas production

Cited by 59 publications

References 163 publications

Biomass to energy: A machine learning model for optimum gasification pathways

Biomass to energy: A machine learning model for optimum gasification pathways

Catalytic Upgrading of Biomass-Gasification Mixtures Using Ni-Fe/MgAl₂O₄ as a Bifunctional Catalyst

Catalytic Pyrolysis of Sawdust with Desulfurized Fly Ash for Pyrolysis Gas Upgrading

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Recent development of biomass gasification for H2 rich gas production

Cited by 59 publications

References 163 publications

Biomass to energy: A machine learning model for optimum gasification pathways

Biomass to energy: A machine learning model for optimum gasification pathways

Catalytic Upgrading of Biomass-Gasification Mixtures Using Ni-Fe/MgAl2O4 as a Bifunctional Catalyst

Catalytic Pyrolysis of Sawdust with Desulfurized Fly Ash for Pyrolysis Gas Upgrading

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Catalytic Upgrading of Biomass-Gasification Mixtures Using Ni-Fe/MgAl₂O₄ as a Bifunctional Catalyst