Alkaline hydrogen peroxide pretreatment of lignocellulosic biomass: status and perspectives
Lignocellulosic biomass is a renewable and abundant resource that is suitable for the production of bio-based materials such as biofuels and chemical products. However, owing to its complex chemical composition, it requires a process that enhances the release of sugars. Pretreatment is an essential...
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Published in | Biomass conversion and biorefinery Vol. 8; no. 1; pp. 225 - 234 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.03.2018
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | Lignocellulosic biomass is a renewable and abundant resource that is suitable for the production of bio-based materials such as biofuels and chemical products. However, owing to its complex chemical composition, it requires a process that enhances the release of sugars. Pretreatment is an essential stage in increasing the efficiency of enzymatic hydrolysis of lignocellulosic biomass. The most widely used pretreatment methods operate at high temperatures (160–290 °C) and pressures (0.69 to 4.9 MPa) and generate biological growth inhibitors such as furfural and hydroxymethylfurfural (HMF). Thus, there has been a growing need to adopt new approaches for an effective pretreatment that operates at ambient temperature and pressure and reduces the generation of inhibitors. Among these methods, alkaline hydrogen peroxide (AHP) is notable because it is effective for a wide range of lignocellulosic biomass concentrations, and can provide a high degree of enzymatic hydrolysis efficiency. However, few results have been discussed in the literature. Given this, the aim of this study was to investigate the use of alkaline hydrogen peroxide (AHP) as an oxidative pretreatment agent to improve the efficiency of enzymatic hydrolysis for different types of biomass and examine the key areas of the pretreatment. Finally, there is a discussion of the challenges facing a large-scale application of this method. |
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ISSN: | 2190-6815 2190-6823 |
DOI: | 10.1007/s13399-017-0277-3 |