Evidence map›Paper›PMID 42333801›Full record

ArticleAngewandte Chemie (International ed. in English)2026

Iterative Synthesis of Pyrene-Coronene Molecular Graphene Nanoribbons.

Miguel A Medel, Guanzhao Wen, Adrián Morón-Blanco, Mischa Bonn, Hai I Wang, Manuel Melle-Franco, Aurelio Mateo-Alonso

Abstract read
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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.

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0citing papers in PubMed
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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

7 authors.

Miguel A MedelPOLYMAT, Department of Applied Chemistry, University of Basque Country (EHU), Donostia-San Sebastián, Spain.
Guanzhao WenMax Planck Institute For Polymer Research, Mainz, Germany.
Adrián Morón-BlancoPOLYMAT, Department of Applied Chemistry, University of Basque Country (EHU), Donostia-San Sebastián, Spain.
Mischa BonnMax Planck Institute For Polymer Research, Mainz, Germany.
Hai I WangMax Planck Institute For Polymer Research, Mainz, Germany.
Manuel Melle-FrancoCICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, Aveiro, Portugal.
Aurelio Mateo-AlonsoPOLYMAT, Department of Applied Chemistry, University of Basque Country (EHU), Donostia-San Sebastián, Spain.ORCID https://orcid.org/0000-0002-5316-2594

Funding

CICECO Aveiro Institute of Materials LA/P/0006/2020CICECO Aveiro Institute of Materials UID/50011/2025Juan de la Cierva-Incorporación fellowship JDC2022-049936-IMaría de Maeztu Excellence Unit CEX2023-001303-M
6 · The paper itself

Abstract

The synthesis of molecular, or monodisperse, graphene nanoribbons with full atomic precision is essential for establishing fundamental structure-property relationships, validating theoretical predictions, and meeting the property requirements for the diverse potential applications of graphene nanoribbons. The synthesis of undoped molecular graphene nanoribbons remains challenging, as many edge topologies have yet to be realized and the reported structures still exhibit limited lengths. This is mostly because iterative synthetic methods for undoped molecular GNRs remain practically undeveloped, with current approaches relying predominantly on noniterative strategies. The iterative synthesis of a new family of undoped molecular GNRs, featuring both a novel edge topology and an unprecedented length, is reported. These nanoribbons are accessed through a borylation/Suzuki/cyclodehydrogenation reaction sequence, in which the Suzuki and cyclodehydrogenation are merged into one transformation, giving rise to an effective two-step iteration sequence. The resulting pyrene-coronene graphene nanoribbons exhibit strong absorption and high fluorescence efficiency, with molar absorptivity and fluorescence brightness values on the order of 10

Indexed as

graphene nanoribbonsnanographenespolycyclic aromatic hydrocarbons

Identifiers

PMID42333801
PMCPMC13502667

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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.