Evidence map›Paper›PMID 38793831›Full record

ArticleSensors (Basel, Switzerland)2024

FEM Modeling Strategies: Application to Mechanical and Dielectric Sensitivities of Love Wave Devices in Liquid Medium.

Maxence Rube, Ollivier Tamarin, Asawari Choudhari, Martine Sebeloue, Dominique Rebiere, Corinne Dejous

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Maxence RubeUMR 228 Espace-Dev, University of French Guiana, F-97300 Cayenne, France.ORCID 0000-0002-6471-0103
Ollivier TamarinUMR 228 Espace-Dev, University of French Guiana, F-97300 Cayenne, France.
Asawari ChoudhariUMR 228 Espace-Dev, University of French Guiana, F-97300 Cayenne, France.
Martine SebeloueUMR 228 Espace-Dev, University of French Guiana, F-97300 Cayenne, France.
Dominique RebiereLaboratoire de l'Intégration du Matériau au Système, University of Bordeaux, CNRS, Bordeaux INP, UMR 5218, F-33405 Talence, France.
Corinne DejousLaboratoire de l'Intégration du Matériau au Système, University of Bordeaux, CNRS, Bordeaux INP, UMR 5218, F-33405 Talence, France.ORCID 0000-0002-9004-7966

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents an extended work on the Finite Element Method (FEM) simulation of Love Wave (LW) sensors in a liquid medium. Two models are proposed to simulate the multiphysical response of the sensor. Both are extensively described in terms of principle, composition and behavior, making their applications easily reproducible by the sensor community. The first model is a Representative Volume Element (RVE) simulating the transducer and the second focuses on the sensor's longitudinal (OXZ) cut which simulates the multiphysical responses of the device. Sensitivity of the LW device to variations in the rheological and dielectric properties of liquids is estimated and then compared to a large set of measurements issued from LW sensors presenting different technological characteristics. This integral approach allows for a deeper insight into the multiphysical behavior of the LW sensor. This article also explores the advantages and drawbacks of each model. Both are in good accordance with the measurements and could be used for various applications, for which a non-exhaustive list is proposed in the conclusion.

Indexed as

COMSOLfinite element modelingLove Wavessurface acoustic wave biosensor

Identifiers

PMID38793831
PMCPMC11125070

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.