Evidence map›Paper›PMID 35161565›Full record

ReviewSensors (Basel, Switzerland)2022

Surface Acoustic Wave (SAW) Sensors: Physics, Materials, and Applications.

Debdyuti Mandal, Sourav Banerjee

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing 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

86 citing papers in PubMed.

  1. Article
  2. Acoustofluidic Biosensors.Micromachines · 2026
    Review
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  20. Review

26 more citing papers are in PubMed but not listed here.

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.

Debdyuti MandalIntegrated Material Assessment and Predictive Simulation Laboratory, University of South Carolina, Columbia, SC 29208, USA.ORCID 0000-0002-9750-7814
Sourav BanerjeeIntegrated Material Assessment and Predictive Simulation Laboratory, University of South Carolina, Columbia, SC 29208, USA.ORCID 0000-0002-2636-0157

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surface acoustic waves (SAWs) are the guided waves that propagate along the top surface of a material with wave vectors orthogonal to the normal direction to the surface. Based on these waves, SAW sensors are conceptualized by employing piezoelectric crystals where the guided elastodynamic waves are generated through an electromechanical coupling. Electromechanical coupling in both active and passive modes is achieved by integrating interdigitated electrode transducers (IDT) with the piezoelectric crystals. Innovative meta-designs of the periodic IDTs define the functionality and application of SAW sensors. This review article presents the physics of guided surface acoustic waves and the piezoelectric materials used for designing SAW sensors. Then, how the piezoelectric materials and cuts could alter the functionality of the sensors is explained. The article summarizes a few key configurations of the electrodes and respective guidelines for generating different guided wave patterns such that new applications can be foreseen. Finally, the article explores the applications of SAW sensors and their progress in the fields of biomedical, microfluidics, chemical, and mechano-biological applications along with their crucial roles and potential plans for improvements in the long-term future in the field of science and technology.

Indexed as

AlNbiosensorschemical sensorscrystal cutGaAsGaNIDTinterdigitated electrodesLamb wavelithium niobatelithium tantalateLove waveMEMSpoint-of-care (POC)Rayleigh waveSAW devicesSAW waveSH-wavesurface acoustic waves (SAW)ZnO

Identifiers

PMID35161565
PMCPMC8839725

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.