Evidence map›Paper›PMID 32099010›Full record

ArticleScientific reports2020

Simulation of an electrically actuated cantilever as a novel biosensor.

Masoud SoltanRezaee, Mahdi Bodaghi

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. 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

2 authors.

Masoud SoltanRezaeeDepartment of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran. m.soltan@modares.ac.ir.
Mahdi BodaghiDepartment of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, NG11 8NS, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, detecting biological particles by analyzing their mechanical properties has attracted increasing attention. To detect and identify different bioparticles and estimate their dimensions, a mechanical nanosensor is introduced in this paper. To attract particles, numerous parts of the substrate are coated with different chemicals as probe detectors or receptors. The principal of cell recognition in this sensor is based on applying an electrical excitation and measuring the maximum deflection of the actuated cantilever electrode. Investigating the critical voltage that causes pull-in instability is also important in such highly-sensitive detectors. The governing equation of motion is derived from Hamilton's principle. A Galerkin approximation is applied to discretize the nonlinear equation, which is solved numerically. Accuracy of the proposed model is validated by comparison studies with available experimental and theoretical data. The coupled effects of geometrical and mechanical properties are included in this model and studied in detail. Moreover, system identification is carried out to distinguish bioparticles by a stability analysis. Due to the absence of a similar concept and device, this research is expected to advance the state-of-the-art biosystems in identifying particles.

Identifiers

PMID32099010
PMCPMC7042266

What OpenQuestion holds

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Registered trials

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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.