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Polymers
Article . 2021 . Peer-reviewed
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Polymers
Article
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PubMed Central
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Syngas Fermentation for the Production of Bio-Based Polymers: A Review

Authors: Nirpesh Dhakal; Bishnu Acharya;

Syngas Fermentation for the Production of Bio-Based Polymers: A Review

Abstract

Increasing environmental awareness among the general public and legislators has driven this modern era to seek alternatives to fossil-derived products such as fuel and plastics. Addressing environmental issues through bio-based products driven from microbial fermentation of synthetic gas (syngas) could be a future endeavor, as this could result in both fuel and plastic in the form of bioethanol and polyhydroxyalkanoates (PHA). Abundant availability in the form of cellulosic, lignocellulosic, and other organic and inorganic wastes presents syngas catalysis as an interesting topic for commercialization. Fascination with syngas fermentation is trending, as it addresses the limitations of conventional technologies like direct biochemical conversion and Fischer–Tropsch’s method for the utilization of lignocellulosic biomass. A plethora of microbial strains is available for syngas fermentation and PHA production, which could be exploited either in an axenic form or in a mixed culture. These microbes constitute diverse biochemical pathways supported by the activity of hydrogenase and carbon monoxide dehydrogenase (CODH), thus resulting in product diversity. There are always possibilities of enzymatic regulation and/or gene tailoring to enhance the process’s effectiveness. PHA productivity drags the techno-economical perspective of syngas fermentation, and this is further influenced by syngas impurities, gas–liquid mass transfer (GLMT), substrate or product inhibition, downstream processing, etc. Product variation and valorization could improve the economical perspective and positively impact commercial sustainability. Moreover, choices of single-stage or multi-stage fermentation processes upon product specification followed by microbial selection could be perceptively optimized.

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    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 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Average
Top 10%
Green
gold