Evidence map›Paper›PMID 35035391›Full record

ReviewScience China. Chemistry2022

Two-dimensional material-based virus detection.

Wenbin Wang, Wei Zhai, Ye Chen, Qiyuan He, Hua Zhang

Abstract readReview
In one paragraph

Review in Science China. Chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Two-Dimensional (2D) materials in the detection of SARS-CoV-2.Microchemical journal : devoted to the application of microtechniques in all branches of science · 2023
    Article
  5. 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.

Wenbin WangDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong, China.
Wei ZhaiDepartment of Chemistry, City University of Hong Kong, Hong Kong, China.
Ye ChenDepartment of Chemistry, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
Qiyuan HeDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong, China.
Hua ZhangDepartment of Chemistry, City University of Hong Kong, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cost-effective, rapid, and accurate virus detection technologies play key roles in reducing viral transmission. Prompt and accurate virus detection enables timely treatment and effective quarantine of virus carrier, and therefore effectively reduces the possibility of large-scale spread. However, conventional virus detection techniques often suffer from slow response, high cost or sophisticated procedures. Recently, two-dimensional (2D) materials have been used as promising sensing platforms for the high-performance detection of a variety of chemical and biological substances. The unique properties of 2D materials, such as large specific area, active surface interaction with biomolecules and facile surface functionalization, provide advantages in developing novel virus detection technologies with fast response and high sensitivity. Furthermore, 2D materials possess versatile and tunable electronic, electrochemical and optical properties, making them ideal platforms to demonstrate conceptual sensing techniques and explore complex sensing mechanisms in next-generation biosensors. In this review, we first briefly summarize the virus detection techniques with an emphasis on the current efforts in fighting again COVID-19. Then, we introduce the preparation methods and properties of 2D materials utilized in biosensors, including graphene, transition metal dichalcogenides (TMDs) and other 2D materials. Furthermore, we discuss the working principles of various virus detection technologies based on emerging 2D materials, such as field-effect transistor-based virus detection, electrochemical virus detection, optical virus detection and other virus detection techniques. Then, we elaborate on the essential works in 2D material-based high-performance virus detection. Finally, our perspective on the challenges and future research direction in this field is discussed.

Indexed as

biosensorCOVID-19field-effect transistortwo-dimensional materialsvirus detection

Identifiers

PMID35035391
PMCPMC8742882

What OpenQuestion holds

Textmetadata
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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.