Bio-Based Covalent Adaptable Oligorotaxane Networks.

Wenbin Wang, Ruixue Bai, Wenzhe Gao, Wei Yu, Zhaoming Zhang, Xuzhou Yan

Abstract read

In one paragraph

Article in Angewandte Chemie (International ed. in English), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Wenbin WangRenji Branch of National Center For Translational Medicine, Shanghai Key Laboratory For Nucleic Acid Chemistry and Nanomedicine, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China.

Ruixue BaiState Key Laboratory of Synergistic Chem-Bio Synthesis, Frontiers Science Center For Transformative Molecules, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Wenzhe GaoState Key Laboratory of Synergistic Chem-Bio Synthesis, Frontiers Science Center For Transformative Molecules, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Wei YuState Key Laboratory of Synergistic Chem-Bio Synthesis, Frontiers Science Center For Transformative Molecules, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Zhaoming ZhangState Key Laboratory of Synergistic Chem-Bio Synthesis, Frontiers Science Center For Transformative Molecules, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Xuzhou YanRenji Branch of National Center For Translational Medicine, Shanghai Key Laboratory For Nucleic Acid Chemistry and Nanomedicine, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0000-0002-6114-5743

Funding

NSFC/China 22401185NSFC/China 22471164NSFC/China 22475128NSFC/China 22525106NSFC/China 225B2114NSFC/China 52333001NSFC/China 52421006Shanghai Municipal Science and Technology Major Project, and Open Project of State Key Laboratory of Supramolecular Structure and Materials sklssm202518

6 · The paper itself

Abstract

The construction of high-performance polymers from sustainable resources represents a forefront direction in materials science. Dynamic covalent chemistry can introduce recyclability into bio-based cross-linked polymers, yet a trade-off between their mechanical robustness and reprocessability often persists. Herein, we report a synergistic integration of biomass feedstocks, dynamic covalent bonds, and mechanically interlocked architectures to create bio-based covalent adaptable oligorotaxane networks (

Indexed as

bio‐based polymerscovalent adaptable networksintramolecular motionoligorotaxanesreprocessability

Identifiers

PMID42165534

DOI10.1002/anie.6436445

PMCPMC13360318

What OpenQuestion holds

Textmetadata

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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.