Evidence map›Paper›PMID 40796778›Full record

ArticleNature communications2025

A general esterolysis strategy for upcycling waste polyesters into high-value esters.

Minghao Zhang, Yunkai Yu, Buxing Han, Qingqing Mei

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

4 authors.

Minghao ZhangState Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, China.
Yunkai YuState Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, China.
Buxing HanBeijing National Laboratory for Molecular Sciences, CAS Laboratory of Colloid and Interface and Thermodynamics, Center for Carbon Neutral Chemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0003-0440-809X
Qingqing MeiState Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, China. meiqq@zju.edu.cn.ORCID http://orcid.org/0000-0003-0210-1377

Funding

National Natural Science Foundation of China (National Science Foundation of China) 22209146National Natural Science Foundation of China (National Science Foundation of China) 22376183
6 · The paper itself

Abstract

The upcycling of waste polyesters into high-value chemicals offers a sustainable and economically viable solution to the global plastic waste crisis. Herein, we report a general esterolysis strategy for the efficient depolymerization of polyesters to produce high-value ester products, utilizing a broad range of esters, including carboxylates, carbonates, and C/Si/Ti/P-based esters. Using the 1-ethyl-3-methylimidazolium acetate as a highly effective catalyst, polyethylene terephthalate is selectively converted into dimethyl terephthalate and ethylene carbonate with remarkable yields of 99% and 90%, respectively. Mechanistic studies reveal that methanol, generated in situ via the 1-ethyl-3-methylimidazolium acetate-catalyzed hydrolysis of dimethyl carbonate, drives the cleavage of C-O ester bonds in polyethylene terephthalate. This strategy demonstrates broad applicability, achieving high conversion efficiencies across various mixed and colored commercial waste polyesters. The energy efficiency and versatility of this approach establish a transformative route to diverse high-value esters, advancing the development of circular plastic economies and sustainable chemistry.

Identifiers

PMID40796778
PMCPMC12343957

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.