Evidence map›Paper›PMID 41140500›Full record

ReviewRSC advances2025

Advanced technologies for plastic waste recycling: examine recent developments in plastic waste recycling technologies.

Oluwaseyi O Alabi, Timileyin O Akande, Oluwatoyin Joseph Gbadeyan, Nirmala Deenadayalu

Abstract readReview
In one paragraph

Review in RSC advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Oluwaseyi O AlabiDepartment of Mechanical Engineering, Lead City University Ibadan Nigeria.ORCID https://orcid.org/0009-0005-0027-5930
Timileyin O AkandeDepartment of Mechanical Engineering, First Technical University Ibadan 200255 Nigeria.ORCID https://orcid.org/0000-0003-4307-1880
Oluwatoyin Joseph GbadeyanDepartment of Chemistry, Durban University of Technology South Africa oluwatoying@dut.ac.za.ORCID https://orcid.org/0000-0002-7906-3965
Nirmala DeenadayaluDepartment of Chemistry, Durban University of Technology South Africa oluwatoying@dut.ac.za.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The escalating challenge of plastic waste necessitates innovative strategies that surpass conventional mechanical recycling. This review examines recent advancements in plastic waste recycling technologies, with a focus on three primary domains: chemical recycling, biological degradation, and enhanced sorting techniques. Chemical recycling employs depolymerization and pyrolysis to dismantle heterogeneous polymers into recoverable monomers, mitigating the constraints of mechanical methods on mixed waste streams. Biological approaches utilize enzymes and microbial consortia for environmentally benign degradation, with emerging engineered variants demonstrating efficacy across diverse polymer types. Furthermore, the integration of artificial intelligence (AI) in sorting systems enhances separation accuracy and throughput by up to 95%. Collectively, these developments foster a robust, sustainable recycling infrastructure aligned with circular economy principles. Nonetheless, barriers such as technological scalability, economic viability, and process optimization persist. This analysis evaluates these innovations' potential to elevate recycling rates, minimize ecological harm, and promote material circularity, while delineating principal obstacles and priority areas for future investigation to facilitate commercial deployment.

Identifiers

PMID41140500
PMCPMC12550887

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.