Evidence map›Paper›PMID 34138091›Full record

ArticleNano-micro letters2020

Development of an Ultra-Sensitive and Flexible Piezoresistive Flow Sensor Using Vertical Graphene Nanosheets.

Sajad Abolpour Moshizi, Shohreh Azadi, Andrew Belford, Amir Razmjou, Shuying Wu, Zhao Jun Han, Mohsen Asadnia

Open access · diamondAbstract read
In one paragraph

Article in Nano-micro letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
6.4field-weighted citation impact, top 2% of its field
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

24 citing papers in PubMed, 116 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Bioinspired flow-sensing capacitive microphone.The Journal of the Acoustical Society of America · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. 3D-Printed Artificial Cilia Arrays: A Versatile Tool for Customizable Mechanosensing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review
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

7 authors at 3 institutions in 1 country.

Sajad Abolpour MoshiziSchool of Engineering, Macquarie University, Sydney, NSW, 2109, Australia.
Shohreh AzadiSchool of Engineering, Macquarie University, Sydney, NSW, 2109, Australia.
Andrew BelfordSchool of Engineering, Macquarie University, Sydney, NSW, 2109, Australia.
Amir RazmjouUNESCO Centre for Membrane Science and Technology, School of Chemical Science and Engineering, University of New South Wales, Sydney, NSW, 2052, Australia.
Shuying WuSchool of Engineering, Macquarie University, Sydney, NSW, 2109, Australia.
Zhao Jun HanCSIRO Manufacturing, PO Box 218, 36 Bradfield Road, Lindfield, NSW, 2070, Australia.
Mohsen AsadniaSchool of Engineering, Macquarie University, Sydney, NSW, 2109, Australia. mohsen.asadnia@mq.edu.au.
Macquarie University · AUCSIRO Manufacturing · AUUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper suggests development of a flexible, lightweight, and ultra-sensitive piezoresistive flow sensor based on vertical graphene nanosheets (VGNs) with a mazelike structure. The sensor was thoroughly characterized for steady-state and oscillatory water flow monitoring applications. The results demonstrated a high sensitivity (103.91 mV (mm/s)

Indexed as

Artificial vestibular systemBioinspired sensorsPiezoresistive sensorsVertical graphene nanosheets

Identifiers

PMID34138091
PMCPMC7770822
OpenAlexW3025776985

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.