Evidence map›Paper›PMID 39613753›Full record

ArticleNature communications2024

Unraveling the role of water in mechanism changes for economically viable catalytic plastic upcycling.

Taeeun Kwon, Byeongchan Ahn, Ki Hyuk Kang, Wangyun Won, Insoo Ro

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
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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

5 authors.

Taeeun Kwon *Department of Chemical and Biomolecular Engineering, Seoul National, University of Science and Technology, Seoul, Republic of Korea.ORCID http://orcid.org/0009-0007-7661-485X
Byeongchan Ahn *Department of Chemical and Biological Engineering, Korea University, Seoul, Republic of Korea.
Ki Hyuk KangChemical & Process Technology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon, Republic of Korea.
Wangyun WonDepartment of Chemical and Biological Engineering, Korea University, Seoul, Republic of Korea. wwon@korea.ac.kr.
Insoo RoDepartment of Chemical and Biomolecular Engineering, Seoul National, University of Science and Technology, Seoul, Republic of Korea. insoo@seoultech.ac.kr.ORCID http://orcid.org/0000-0002-4704-142X

Funding

MOE | Korea Environmental Industry and Technology Institute (KEITI) 2022003650002National Research Foundation of Korea (NRF) 2022R1F1A1074392
6 · The paper itself

Abstract

The surge in global plastic production, reaching 400.3 million tons in 2022, has exacerbated environmental pollution, with only 11% of plastic being recycled. Catalytic recycling, particularly through hydrogenolysis and hydrocracking, offers a promising avenue for upcycling polyolefin plastic, comprising 55% of global plastic waste. This study investigates the influence of water on polyolefin depolymerization using Ru catalysts, revealing a promotional effect only when both metal and acid sites, particularly Brønsted acid site, are present. Findings highlight the impact of Ru content, metal-acid balance, and their proximity on this interaction, as well as their role in modulating the isomerization process, affecting product selectivity. Additionally, the interaction facilitates the suppression of coke formation, ultimately enhancing catalyst stability. A comprehensive techno-economic and life cycle assessment underscores the viability and environmental benefits of the process, particularly in the presence of water. These insights advance understanding and offer strategies for optimizing polyolefin plastic recycling processes.

Identifiers

PMID39613753
PMCPMC11607347

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.