Highly active and magnetically recoverable heterogeneous catalyst for hydrothermal liquefaction of biomass into high quality bio-oil

Mukundan, Swathi; Xuan, Jin; Dann, Sandra E.; Wagner, Jonathan L.

doi:10.1016/j.biortech.2022.128479

Cited by 22 publications

(5 citation statements)

References 46 publications

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“…different yields of bio-oil can be obtained from the liquefaction of biomass. [303][304][305] The gas phase with a yield of 5-10 wt%, which includes CO 2 as the main component, CO, CH 4 , etc. is obtained from the HTL of biomass.…”

Section: Hydrothermal Liquefactionmentioning

confidence: 99%

“…[300][301][302] Bio-oil from the hydrothermal liquefaction has 70-95% of the energy content of biomass. [302][303][304][305] It is full of heavy compounds containing oxygen, which require upgrading. 303 Hydrodeoxygenation is used as the main upgrading method to improve the quality of the bio-oil from the liquefaction of biomass.…”

Section: Hydrothermal Liquefactionmentioning

confidence: 99%

See 1 more Smart Citation

A review on thermochemical based biorefinery catalyst development progress

Gholizadeh,

Castro,

Fabrega

et al. 2023

Sustainable Energy Fuels

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Section: Hydrothermal Liquefactionmentioning

confidence: 99%

Section: Hydrothermal Liquefactionmentioning

confidence: 99%

A review on thermochemical based biorefinery catalyst development progress

Gholizadeh,

Castro,

Fabrega

et al. 2023

Sustainable Energy Fuels

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show abstract

“…Designing such circular pathways requires key information such as catalyst, product, reactant, methods, etc., for plastic waste recycling, which is scattered in journals, books, and web sites. To name a few, some of the key techniques related to plastic waste recycling are discussed in refs − . Due to the plethora of scientific literature available, it is exceedingly difficult to distill the required information from these resources.…”

Section: Introductionmentioning

confidence: 99%

Recycle-BERT: Extracting Knowledge about Plastic Waste Recycling by Natural Language Processing

Kumar,

Bakshi,

Ramteke

et al. 2023

ACS Sustainable Chem. Eng.

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Managing waste plastic is a serious global challenge since most of this waste is either landfilled, incinerated, burned in the open, or littered. Each of these approaches has a large environmental impact. Establishing a circular economy of plastics requires its recovery and recycling, and much effort is now focused in this direction. The body of literature on approaches for managing the end of life of plastics is growing exponentially, making it increasingly difficult to segregate the most relevant information across multiple articles. Such work is extremely timeand effort-consuming, particularly when performed manually. To address this issue, in this study, we propose a methodology based on natural language processing (NLP) for automatically extracting and compiling information that is most relevant to a selected category of plastics. In the developed methodology, the research articles are first extracted with the help of a science-direct Elsevier Application Programming Interface key by utilizing a set of keywords such as "polyethylene recycle methods", "polyethylene terephthalate recycle methods", "polypropylene recycle methods", and "polystyrene recycle methods" for relevant articles. Extracted articles are processed to address two fundamental problems; (i) classification and (ii) question and answer (Q&A) related to literature pertaining to plastic waste recycling. To this extent, we developed a bundle of NLP tools called Recycle-Bidirectional Encoder Representations from Transformers (BERT). Under the hood, Recycle-BERT comprised five language models, (1) Class-BERT, for classifying the literature as relevant or nonrelevant; (2) Catalyst-BERT, for extracting catalyst details for recycling; (3) Method-BERT, for finding the methods enlisted in the literature for recycling; (4) Reactant-BERT to identify the reactants used for waste recycling; and (5) Product-BERT to pinpoint products obtained from recycling. We have evaluated the performance of the developed models based on the metrics such as accuracy and F1-score. For the classification task, an accuracy metric value of 0.974 is obtained for the test data set. Similarly, the metric F1-score values for the Q&A task are 0.7646, 0.8014, 0.8221, and 0.8512 for the test data set for Catalyst-BERT, Method-BERT, Reactant-BERT, and Product-BERT, respectively. The results indicate the proposed NLP-based model's ability to extract essential information from the literature related to plastic waste processing, aiding suitable recommendations to assist transformation to a sustainable circular economy.

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“…Among them, hydrothermal liquefaction (HTL) is one of the most effective technologies, able to efficiently convert several biomass types, such as rice straw [2], peanut shell [3], oak wood [4] sugar beet pulp [5] and microalga [6,7], into more valuable liquid bio-crude. Furthermore, the process is carried out at a medium temperature (250-400 • C) and under high pressure (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), using water as a solvent [8]. The influence of several process variables, such as temperature [9], residence time [10], catalyst activity [11] and water-biomass ratio [12], on the product yields has been widely investigated in literature in order to find the optimal conditions.…”

Section: Introductionmentioning

confidence: 99%

“…The use of heterogeneous catalysts solves this issue; they can be easily recovered and recycled at the end of the reaction. Furthermore, several studies have highlighted their ability to enhance both bio-crude yields and quality [17,18]. In particular, nickel metal (Ni) is a well-known hydrogenation catalyst, and in the authors' previous work, the use of supported Ni coupled with Fe as the hydrogen producer enhanced the biomass conversion into high-quality bio-crude [19].…”

Section: Introductionmentioning

confidence: 99%

Catalytic Hydrothermal Liquefaction of Brachychiton populneus Biomass for the Production of High-Value Bio-Crude

et al. 2023

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The current study focused on the heterogenous catalytic hydrothermal liquefaction (HTL) of Brachychiton populneus biomass seed, using Ni as hydrogenation catalyst and Fe as active hydrogen producer. The activity of Ni metal and of Ni/Al2O3 in the HTL of seed (BS) and of a mixture of seed and shell (BM) was studied. To establish the best operating process conditions, the influence of variation of temperature and reaction time on the product yields was also examined. The highest bio-crude yields of 57.18% and 48.23% for BS and BM, respectively, were obtained at 330 °C and 10 min of reaction time, in the presence of Ni/Al2O3 as catalyst and Fe as hydrogen donor. Elemental analysis results showed that at these operative conditions, an increase of the higher heating value (HHV) from 25.14 MJ/kg to 38.04 MJ/kg and from 17.71 MJ/kg to 31.72 MJ/kg was obtained for BS and BM biomass, respectively, when the combination of Fe and Ni/Al2O3 was used. Gas chromatography–mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FT-IR), used to determine the oils’ chemical compositions, showed that the combined presence of Fe and Ni/Al2O3 favored the hydrodeoxygenation of the fatty acids into hydrocarbons, indeed their amount increased to ≈20% for both biomasses used. These results demonstrate that the obtained bio-crude has the capacity to be a source of synthetic fuels and chemical feedstock.

show abstract

Highly active and magnetically recoverable heterogeneous catalyst for hydrothermal liquefaction of biomass into high quality bio-oil

Cited by 22 publications

References 46 publications

A review on thermochemical based biorefinery catalyst development progress

A review on thermochemical based biorefinery catalyst development progress

Recycle-BERT: Extracting Knowledge about Plastic Waste Recycling by Natural Language Processing

Catalytic Hydrothermal Liquefaction of Brachychiton populneus Biomass for the Production of High-Value Bio-Crude

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