Evidence map›Paper›PMID 32320328›Full record

ArticleSoft robotics2021

A Soft Material Flow Sensor for Micro Air Vehicles.

Johan Sundin, Katherine Kokmanian, Matthew K Fu, Shervin Bagheri, Marcus Hultmark

Abstract read
In one paragraph

Article in Soft robotics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Johan SundinDepartment of Engineering Mechanics, Linné FLOW Centre, Royal Institute of Technology, Stockholm, Sweden.
Katherine KokmanianMechanical and Aerospace Engineering Department, Princeton University, Princeton, New Jersey, USA.
Matthew K FuDepartment of Civil and Environmental Engineering, Stanford University, Stanford, California, USA.
Shervin BagheriDepartment of Engineering Mechanics, Linné FLOW Centre, Royal Institute of Technology, Stockholm, Sweden.
Marcus HultmarkMechanical and Aerospace Engineering Department, Princeton University, Princeton, New Jersey, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To control and navigate micro air vehicles (MAVs) efficiently, there is a need for small, lightweight, durable, sensitive, fast, and low-power airspeed sensors. When designing sensors to meet these requirements, soft materials are promising alternatives to more traditional materials due to the large deformations they can withstand. In this article, a new concept of a soft material flow sensor is presented based on elastic filament velocimetry, which fulfills all necessary criteria. This technique measures flow velocity by relating it to the strain of a soft ribbon suspended between two static supports and subjected to a flow of interest. The ribbon is manufactured from polydimethylsiloxane and can be made piezoresistive by the addition of silver nanowires. With the described manufacturing method, the sensor can be made using common laboratory tools, outside of a clean room, significantly reducing its complexity. Furthermore, it can be operated using a simple and lightweight circuit, making it a convenient alternative for MAVs. Using a piezoresistive material allows for the flow velocity to be calibrated to the resistance change of the strained ribbon. Although certain challenges remain unsolved, such as polymer creep, the sensor has demonstrated its ability to measure flow velocities down to 4 m/s in air through experiments. A time-dependent analytical model is also provided. The model shows that the current sensor has a bandwidth of 480 Hz. Most importantly, the sensitivity and the bandwidth of the sensor can be varied strictly by modifying the geometry and the material properties of the ribbon.

Indexed as

NanowiresWearable Electronic DevicesPolymersSilverPolymersSilverflow measurementsmicro air vehiclesPDMSsoft sensorstretchable electronics

Identifiers

PMID32320328
PMCPMC8082728

What OpenQuestion holds

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LicenceCC BY
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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.