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Deep Eutectic Solvents for Pretreatment, Extraction, and Catalysis of Biomass and Food Waste

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type , Journal 06 Nov 2019Publisher:MDPI AGJournal:Molecules, volume 24, page 4,012 (eissn: 1420-3049,

Authors: Payam Kalhor; Khashayar Ghandi;

doi: 10.3390/molecules24224012

pmid: 31698717

pmc: PMC6891572

Deep Eutectic Solvents for Pretreatment, Extraction, and Catalysis of Biomass and Food Waste

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Abstract

Valorization of lignocellulosic biomass and food residues to obtain valuable chemicals is essential to the establishment of a sustainable and biobased economy in the modern world. The latest and greenest generation of ionic liquids (ILs) are deep eutectic solvents (DESs) and natural deep eutectic solvents (NADESs); these have shown great promise for various applications and have attracted considerable attention from researchers who seek versatile solvents with pretreatment, extraction, and catalysis capabilities in biomass- and biowaste-to-bioenergy conversion processes. The present work aimed to review the use of DESs and NADESs in the valorization of biomass and biowaste as pretreatment or extraction solvents or catalysis agents.

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Keywords

Models, Molecular, biomass, Chemical Phenomena, Molecular Structure, deep eutectic solvent, natural deep eutectic solvent, Organic chemistry, Review, pretreatment, Lignin, Catalysis, Refuse Disposal, food residue, QD241-441, Food, extraction, Solvents, Biomass

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	217
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 0.1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 0.1%