Evidence map›Paper›PMID 40360485›Full record

ReviewMicrosystems & nanoengineering2025

Bio-inspired artificial hair flow sensors: a comprehensive review of design, fabrication, enhancements, and applications.

Lansheng Zhang, Zheyi Hang, Huan Hu

Abstract readReview
In one paragraph

Review in Microsystems & nanoengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Lansheng ZhangNanomanufacturing & Biomimetics Lab, ZJUI Institute, International Campus, Zhejiang University, 311400, Haining, China.
Zheyi HangNanomanufacturing & Biomimetics Lab, ZJUI Institute, International Campus, Zhejiang University, 311400, Haining, China.
Huan HuNanomanufacturing & Biomimetics Lab, ZJUI Institute, International Campus, Zhejiang University, 311400, Haining, China. huanhu@intl.zju.edu.cn.ORCID http://orcid.org/0000-0002-1317-5470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flow measurement is critical in various sectors, including industry, agriculture, medicine, and environmental monitoring. There is a growing need for compact, sensitive, scalable, and energy-efficient flow sensors, particularly for applications in unmanned aerial vehicles, unmanned underwater vehicles, biomedicine, and bionic robotics. Inspired by biological mechanosensory structures, artificial hair and hair cell flow sensors have emerged as promising solutions. This study offers a comprehensive review of the progress, underlying principles, performance optimization techniques, and applications of hair flow sensors. We provide an overview of the biological mechanisms of hair as mechanical receptors. Subsequently, we explain the design and fabrication techniques of artificial hair flow sensors, highlighting the challenges associated with replicating and integrating hair structures. The study further explores strategies for sensor enhancement and their diverse applications. Finally, we conclude by outlining the challenges and prospects of hair sensor technology, along with its potential to address specific flow-sensing requirements. While most applications of artificial hair cell flow sensors are still in the research stage, they offer substantial potential for flow measurement. Future progress in materials science, structural design, and sensing mechanisms is anticipated to drive the development of these sensors, opening up new avenues for scientific research and commercial applications.

Identifiers

PMID40360485
PMCPMC12075567

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.