The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Enzymes’ Power for Plastics Degradation
Open accessAbstract
Plastics are everywhere in our modern way of living, and their production keeps increasing every year, causing major environmental concerns. Nowadays, the end-of-life management involves accumulation in landfills, incineration, and recycling to a lower extent. This ecological threat to the environment is inspiring alternative bio-based solutions for plastic waste treatment and recycling toward a circular economy. Over the past decade, considerable efforts have been made to degrade commodity plastics using biocatalytic approaches. Here, we provide a comprehensive review on the recent advances in enzyme-based biocatalysis and in the design of related biocatalytic processes to recycle or upcycle commodity plastics, including polyesters, polyamides, polyurethanes, and polyolefins. We also discuss scope and limitations, challenges, and opportunities of this field of research. An important message from this review is that polymer-assimilating enzymes are very likely part of the solution to reaching a circular plastic economy.
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Citations
Cites
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Self-citationBeyond Mechanical Recycling: Giving New Life to Plastic Waste
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Cited by
Sustainable Solutions Through Innovative Plastic Waste Recycling Technologies
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Identification and characterization of substrate- and product-selective nylon hydrolases
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Metadata
- Authors
- Tournier, V., Duquesne, S., Guillamot, F., Cramail, H., Taton, D., Marty, A., & André, I.
- Venue
- Chemical Reviews
- Publisher
- American Chemical Society (ACS)
- Published
- 2023-03-14
- Volume
- 123
- Issue
- 9
- Pages
- 5612-5701
- ISSN
- 0009-2665 (ISSN-L)
- 1520-6890
- OpenAlex
- W4324130041
- Cited by
- 590
- References
- 27
- FWCI
- 8.34
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
