Production of biocrude from organic waste: Influence of feedstock composition on hydrodenitrogenation reactivity in biocrude upgrading

Matayeva, Aisha; Fasolini, Andrea; Bianchi, Daniele; Chiaberge, Stefano; Maron, Jacopo De; Basile, Francesco

doi:10.1016/j.fuel.2022.126981

Cited by 4 publications

(1 citation statement)

References 37 publications

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“…The SS biocrude composition depends on multiple factors, including the initial composition of the SS, the HTL process conditions, and the extraction solvent used to recover the biocrude (if any). ,− For instance, Jahromi et al hydrotreated SS biocrudes produced with different HTL extraction solvents and, of the solvents tested, found dichloromethane (DCM) gave the best HTL yield but provided a biocrude that was more difficult to upgrade. Similarly, Silva Thomsen et al demonstrated that the concentration of proteins in SS is directly related to the final concentration of N in the biocrude, which, like with algal HTL biocrudes, poses a challenge during the upgrading to fuels.…”

Section: Introductionmentioning

confidence: 99%

Hydrotreatment of Sewage Sludge-Derived Hydrothermal Liquefaction Biocrude. Part I: Experimental

Browning,

Batalha,

Costa Gomes

et al. 2024

Energy Fuels

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Section: Introductionmentioning

confidence: 99%

Hydrotreatment of Sewage Sludge-Derived Hydrothermal Liquefaction Biocrude. Part I: Experimental

Browning,

Batalha,

Costa Gomes

et al. 2024

Energy Fuels

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Comprehensive review of hydrothermal liquefaction data for use in machine‐learning models

Haarlemmer,

Matricon,

Roubaud

2024

Biofuels Bioprod Bioref

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Hydrothermal liquefaction is a new, sustainable pathway to generate biogenic liquids from organic resources. The technology is compatible with a wide variety of resources such as lignocellulosic resources, organic waste, algae, and sewage sludge. The chemistry is complex and predictions of yields are notoriously difficult. Understanding and modeling of hydrothermal liquefaction is currently mostly based on a simplified biochemical analysis and product yield data. This paper presents a large dataset of 2439 experiments in batch reactors that were extracted from 171 publications in the scientific literature. The data include biochemical composition data such as fiber content and composition, proteins, lipids, carbohydrates, and ash. The experimental conditions are recorded for each experiment as well as the reported yields. The objective of this paper is to make a large database available to the scientific community. This database is analyzed with machine‐learning tools. The results show that there is no consensus on the analysis techniques, experimental procedures, and reported data. There are many inconsistencies across the literature that should be improved by the scientific community. Machine‐learning tools with a large dataset allow the generation of reliable yield production tools with a large application field. Given the accuracy of the data, the overall precision of prediction in an extrapolation to new results can be expected to be around 10%.

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Utilization of food waste for biocrude production: A review

Dhalsamant,

Tirumareddy,

Borugadda

et al. 2023

Bioresource Technology Reports

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Production of biocrude from organic waste: Influence of feedstock composition on hydrodenitrogenation reactivity in biocrude upgrading

Cited by 4 publications

References 37 publications

Hydrotreatment of Sewage Sludge-Derived Hydrothermal Liquefaction Biocrude. Part I: Experimental

Hydrotreatment of Sewage Sludge-Derived Hydrothermal Liquefaction Biocrude. Part I: Experimental

Comprehensive review of hydrothermal liquefaction data for use in machine‐learning models

Utilization of food waste for biocrude production: A review

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