Evidence map›Paper›PMID 33840899›Full record

ArticleSensors and actuators. A, Physical2021

Design and finite element simulation of metal-core piezoelectric fiber/epoxy matrix composites for virus detection.

Yinli Wang, Yu Shi, Fumio Narita

Open access · greenAbstract read
In one paragraph

Article in Sensors and actuators. A, Physical, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.5field-weighted citation impact, top 12% 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

8 citing papers in PubMed, 29 citations in OpenAlex.

  1. Review
  2. Batteryless wireless magnetostrictive FeSensors and actuators. A, Physical · 2023
    Article
  3. Article
  4. Properties of a NovelFoods (Basel, Switzerland) · 2022
    Article
  5. Review
  6. Review
  7. Article
  8. 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 at 2 institutions in 2 countries.

Yinli WangDepartment of Materials Processing, Graduate School of Engineering, Tohoku University, Aoba-yama 6-6-02, Sendai, Japan.
Yu ShiDepartment of Mechanical Engineering, University of Chester, Thornton Science Park, Pool Lane, Chester, CH2 4NU, UK.
Fumio NaritaDepartment of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Aoba-yama 6-6-02, Sendai, Japan.
Tohoku University · JPUniversity of Chester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Undoubtedly, the coronavirus disease 2019 (COVID-19) has received the greatest concern with a global impact, and this situation will continue for a long period of time. Looking back in history, airborne transimission diseases have caused huge casualties several times. COVID-19 as a typical airborne disease caught our attention and reminded us of the importance of preventing such diseases. Therefore, this study focuses on finding a new way to guard against the spread of these diseases such as COVID-19. This paper studies the dynamic electromechanical response of metal-core piezoelectric fiber/epoxy matrix composites, designed as mass load sensors for virus detection, by numerical modelling. The dynamic electromechanical response is simulated by applying an alternating current (AC) electric field to make the composite vibrate. Furthermore, both concentrated and distributed loads are considered to assess the sensitivity of the biosensor during modelling of the combination of both biomarker and viruses. The design parameters of this sensor, such as the resonant frequency, the position and size of the biomarker, will be studied and optimized as the key values to determine the sensitivity of detection. The novelty of this work is to propose functional composites that can detect the viruses from changes of the output voltage instead of the resonant frequency change using piezoelectric sensor and piezoelectric actuator. The contribution of this detection method will significantly shorten the detection time as it avoids fast Fourier transform (FFT) or discrete Fourier transform (DFT). The outcome of this research offers a reliable numerical model to optimize the design of the proposed biosensor for virus detection, which will contribute to the production of high-performance piezoelectric biosensors in the future.

Indexed as

BiosensorDynamic electromechanical responseFinite element methodPiezoelectric compositeVirus detection

Identifiers

PMID33840899
PMCPMC8025628
OpenAlexW3149287181

What OpenQuestion holds

Textmetadata
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.