Evidence map›Paper›PMID 32720441›Full record

ReviewAngewandte Chemie (International ed. in English)2020

Synthetic Tailoring of Graphene Nanostructures with Zigzag-Edged Topologies: Progress and Perspectives.

Junzhi Liu, Xinliang Feng

Abstract readReview
In one paragraph

Review in Angewandte Chemie (International ed. in English), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Molecular Graphene Nanoribbon Junctions.Journal of the American Chemical Society · 2024
    Article
  11. Article
  12. Article
  13. Review
  14. Butterfly-Shaped Dibenz[Organic letters · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Azaarenes: 13 Rings in a Row by Cyclopentannulation.Angewandte Chemie (International ed. in English) · 2023
    Article
  19. Journal of the American Chemical Society · 2022
    Article
  20. Article
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

2 authors.

Junzhi LiuDepartment of Chemistry and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong, Pokfulam Road, Hong Kong, China.ORCID http://orcid.org/0000-0001-7146-0942
Xinliang FengCenter for Advancing Electronics Dresden (cfaed) & Faculty of Chemistry and Food Chemistry, Technische Universität Dresden, 01062, Dresden, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Experimental and theoretical investigations have revealed that the chemical and physical properties of graphene are crucially determined by their topological structures. Therefore, the atomically precise synthesis of graphene nanostructures is essential. A particular example is graphene nanostructures with zigzag-edged structures, which exhibit unique (opto)electronic and magnetic properties owing to their spin-polarized edge state. Recent progress in the development of synthetic methods and strategies as well as characterization methods has given access to this class of unprecedented graphene nanostructures, which used to be purely molecular objectives in theoretical chemistry. Thus, clear insight into the structure-property relationships has become possible as well as new applications in organic carbon-based electronic and spintronic devices. In this Minireview, we discuss the recent progress in the controlled synthesis of zigzag-edged graphene nanostructures with different topologies through a bottom-up synthetic strategy.

Indexed as

bottom-up synthesisdopinggraphene nanoribbonsmagnetismnanographenes

Identifiers

PMID32720441
PMCPMC7756885

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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.