Evidence map›Paper›PMID 39886374›Full record

ReviewPrecision chemistry2025

Constructing Two-Dimensional, Ordered Networks of Carbon-Carbon Bonds with Precision.

Jui-Han Fu, De-Chian Chen, Yen-Ju Wu, Vincent Tung

Abstract readReview
In one paragraph

Review in Precision chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Jui-Han FuDepartment of Chemical System Engineering, School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan.
De-Chian ChenDepartment of Chemical System Engineering, School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan.
Yen-Ju WuCenter for Basic Research on Materials, National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan.ORCID https://orcid.org/0000-0003-2647-3407
Vincent TungDepartment of Chemical System Engineering, School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan.ORCID https://orcid.org/0000-0003-3230-0932

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organic semiconducting nanomembranes (OSNMs), particularly carbon-based ones, are at the forefront of next-generation two-dimensional (2D) semiconductor research. These materials offer remarkable promise due to their diverse chemical properties and unique functionalities, paving the way for innovative applications across advanced semiconductor material sectors. Graphene stands out for its extraordinary mechanical strength, thermal conductivity, and superior charge transport capabilities, inspiring extensive research into other 2D carbon allotropes like graphyne and graphdiyne. With its high electron mobility and tunable bandgap, graphdiyne is particularly attractive for power-efficient electronic devices. However, synthesizing graphdiyne presents significant challenges, primarily due to the difficulty in achieving precise and deterministic control over the coupling of its monomers. This precision is crucial for determining the material's porosity, periodicity, and overall functionality. Innovative approaches have been developed to address these challenges, such as the strategic assembly of molecular building blocks at heterogeneous interfaces. Furthermore, data-driven techniques, such as machine learning and artificial intelligence (AI), are proving invaluable in this field, assisting in screening precursors, optimizing structural configurations, and predicting novel properties of these materials. These advancements are essential for producing durable monolayer sheets that can be integrated into existing electronic components. Despite these advancements, the integration of graphdiyne into semiconductor technology remains complex. Achieving long-range coherence in bonding configurations and enhancing charge transport characteristics are significant hurdles. Continued research into robust and controllable synthesis techniques is essential for unlocking the full potential of graphdiyne and other 2D materials, leading to more efficient, faster, and mechanically robust electronics.

Identifiers

PMID39886374
PMCPMC11775848

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.