Evidence map›Paper›PMID 40082613›Full record

ArticleNature chemistry2025

Vinyl polymers with fully degradable carbon backbones enabled by aromatization-driven C-C bond cleavage.

Zhen-Hua Zhang, Yangyang Sun, Thayalan Rajeshkumar, Yuesheng Li, Laurent Maron, Miao Hong

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Article in Nature chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Zhen-Hua Zhang *State Key Laboratory of Organometallic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China.
Yangyang Sun *State Key Laboratory of Organometallic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China.ORCID http://orcid.org/0000-0001-5148-0954
Thayalan RajeshkumarLPCNO, Département de Génie Physique, INSA, Université Paul Sabatier-Toulouse III, Toulouse, France.ORCID http://orcid.org/0000-0001-5109-8093
Yuesheng LiTianjin Key Lab of Composite and Functional Materials, School of Materials Science and Engineering, Tianjin University, Tianjin, China.
Laurent MaronLPCNO, Département de Génie Physique, INSA, Université Paul Sabatier-Toulouse III, Toulouse, France. laurent.maron@irsamc.ups-tlse.fr.ORCID http://orcid.org/0000-0003-2653-8557
Miao HongState Key Laboratory of Organometallic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China. miaohong@sioc.ac.cn.ORCID http://orcid.org/0000-0003-1016-882X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Degradation of carbon-backbone polymers, which make up most plastics, remains a formidable challenge owing to strong and inert main-chain C-C bonds. While incorporation of comonomers that generate backbone radicals under certain conditions can induce degradation of the polymer chain, such strategies yield complex oligomer mixtures. Here we report aromatization-driven C-C bond cleavage as a viable and powerful strategy to endow the degradability into carbon backbones using acrylic polymers as a model example. The key to this new strategy is the efficient, living, alternating addition copolymerization of acrylates with simple, commercially available and biorenewable coumarin using a frustrated Lewis pair cooperative catalyst. The resulting acrylic copolymers are strong, transparent thermoplastics with key thermal, optical, mechanical properties comparable or superior to poly(methyl methacrylate). Under strong base, alternating copolymers can completely degrade at room temperature through efficient cleavage of main-chain C-C bonds utilizing aromatization as a thermodynamic driving force, to generate pure, pharmaceutically valuable molecules, thus affording durable, robust yet fully degradable carbon-backbone acrylic polymers.

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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.