Evidence map›Paper›PMID 36798507›Full record

ReviewNanoscale advances2023

Recent trends in carbon nanotube (CNT)-based biosensors for the fast and sensitive detection of human viruses: a critical review.

Hicham Meskher, Hussain Chaudhery Mustansar, Amrit Kumar Thakur, Ravishankar Sathyamurthy, Iseult Lynch, Punit Singh, Tan Kim Han, Rahman Saidur

Erratum issuedAbstract readReview
In one paragraph

Review in Nanoscale advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Review
  2. Review
  3. (Cu-S)Mikrochimica acta · 2026
    Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. Review
  18. Article
  19. Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Hicham MeskherDepartment of Process Engineering, Kasdi-Merbah University Ouargla 30000 Algeria hicham.meskher@g.enp.edu.dz.ORCID https://orcid.org/0000-0002-6097-9439
Hussain Chaudhery MustansarDepartment of Chemistry and Environmental Science, New Jersey Institute of Technology Newark 07102 NJ USA.ORCID https://orcid.org/0000-0002-1964-4338
Amrit Kumar ThakurDepartment of Mechanical Engineering, KPR Institute of Engineering and Technology Arasur Coimbatore 641407 Tamil Nadu India amritt1@gmail.com.ORCID https://orcid.org/0000-0002-0644-2323
Ravishankar SathyamurthyMechanical Engineering Department, King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia.
Iseult LynchSchool of Geography, Earth and Environmental Sciences, University of Birmingham Edgbaston Birmingham B15 2TT UK I.Lynch@bham.ac.uk.ORCID https://orcid.org/0000-0003-4250-4584
Punit SinghInstitute of Engineering and Technology, Department of Mechanical Engineering, GLA University Mathura Uttar Pradesh 281406 India.
Tan Kim HanResearch Centre for Nano-Materials and Energy Technology (RCNMET), School of Engineering and Technology, Sunway University No. 5, Jalan Universiti, Bandar Sunway Petaling Jaya 47500 Malaysia saidur@sunway.edu.my.ORCID https://orcid.org/0000-0002-6634-1006
Rahman SaidurResearch Centre for Nano-Materials and Energy Technology (RCNMET), School of Engineering and Technology, Sunway University No. 5, Jalan Universiti, Bandar Sunway Petaling Jaya 47500 Malaysia saidur@sunway.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current COVID-19 pandemic, with its numerous variants including Omicron which is 50-70% more transmissible than the previously dominant Delta variant, demands a fast, robust, cheap, and easily deployed identification strategy to reduce the chain of transmission, for which biosensors have been shown as a feasible solution at the laboratory scale. The use of nanomaterials has significantly enhanced the performance of biosensors, and the addition of CNTs has increased detection capabilities to an unrivaled level. Among the various CNT-based detection systems, CNT-based field-effect transistors possess ultra-sensitivity and low-noise detection capacity, allowing for immediate analyte determination even in the presence of limited analyte concentrations, which would be typical of early infection stages. Recently, CNT field-effect transistor-type biosensors have been successfully used in the fast diagnosis of COVID-19, which has increased research and commercial interest in exploiting current developments of CNT field-effect transistors. Recent progress in the design and deployment of CNT-based biosensors for viral monitoring are covered in this paper, as are the remaining obstacles and prospects. This work also highlights the enormous potential for synergistic effects of CNTs used in combination with other nanomaterials for viral detection.

Identifiers

PMID36798507
PMCPMC9926911

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.