Evidence map›Paper›PMID 39414227›Full record

ReviewJournal of advanced research2025

Graphdiyne as an emerging sensor platform: Principles, synthesis and application.

Wei Zhang, Jing Xu, Tian Wang, Xi Lin, Fu Wang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of advanced research, 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

5 authors.

Wei ZhangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China; College of Life Science, Xinyang Normal University, Xinyang 464000, China.
Jing XuDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China; College of Life Science, Xinyang Normal University, Xinyang 464000, China. Electronic address: xujing@xynu.edu.cn.
Tian WangCollege of Life Science, Xinyang Normal University, Xinyang 464000, China.
Xi LinCollege of Materials and Chemical Engineering, Minjiang University, Fuzhou 350108, China. Electronic address: mjulinxi@163.com.
Fu WangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China; Institute of Medical Engineering, Department of Biophysics, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an 710061, China; Xianyang Key Laboratory of Molecular Imaging and Drug Synthesis, School of Pharmacy, Shaanxi University of International Trade & Commerce, Xianyang 712046, China. Electronic address: wangfu@xjtu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGraphdiyne (GDY) is a kind of carbon material, which has highly delocalized π-conjugated system and feasible green synthesis. Nowadays, the use of GDY substrate as a sensing platform has become a new research hotspot and is rapidly developing. However, its application as a sensor is still relatively overlook compared to other fields. AIM OF REVIEW: This study is for the purpose of making researchers have a complete comprehensive understanding of GDY and its associated sensing platforms. KEY SCIENTIFIC CONCEPTS OF REVIEW: This study introduces the structure, unique characteristics, and synthesis progress of GDY material. Moreover, the article systematically summarizes the improvement of GDY-based sensors in life, health and environmental detection. It also discusses the opportunities and challenges of designing high-performance GDY-based sensing platforms with the assistance of machine learning and theoretical calculate. It has essential scientific and practical meaning for accelerating the development of sensing platforms which base on GDY, triggering unknown phenomena and knowledge of material research, and initiating unlimited space for scientific innovation.

Indexed as

Biomedicine detectionGraphdiyneMachine learningSensor

Identifiers

PMID39414227
PMCPMC12302518

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.