Evidence map›Paper›PMID 36273018›Full record

ArticleScientific reports2022

A multifunctional ultra-thin acoustic membrane with self-healing properties for adaptive low-frequency noise control.

Marco Boccaccio, Konstantinos Myronidis, Michael Thielke, Michele Meo, Fulvio Pinto

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. 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
0.6field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. AI-Based Metamaterial Design.ACS applied materials & interfaces · 2024
    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

5 authors at 1 institution in 1 country.

Marco BoccaccioDepartment of Mechanical Engineering, University of Bath, Bath, BA27AY, UK.
Konstantinos MyronidisDepartment of Mechanical Engineering, University of Bath, Bath, BA27AY, UK.
Michael ThielkeDepartment of Mechanical Engineering, University of Bath, Bath, BA27AY, UK.
Michele MeoDepartment of Mechanical Engineering, University of Bath, Bath, BA27AY, UK. m.meo@bath.ac.uk.
Fulvio PintoDepartment of Mechanical Engineering, University of Bath, Bath, BA27AY, UK.
University of Bath · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes a novel multifunctional ultra-thin membrane based on a Polyborosiloxane-based gel with stimuli-responsive sound absorption and sound transmission loss (STL) and characterised by excellent self-healing properties. This adaptive behaviour is the result of a dynamically activated phase transition in the membrane's polymeric network which is given by the interaction with the travelling sound pressure wave. The presence and the extent of such phase transition in the material was investigated via oscillatory rheological measurements showing the possibility to control the dynamic response by modifying the Boron content within the polymer. Acoustic analyses conducted at different stimuli responses showed high and dynamic absorption (95%) at the absorption coefficient peaks and an adaptive shift to lower frequencies while sound amplitudes were increased. An average STL up to 27 dB in the frequency range between 500 to 1000 Hz was observed and an increased STL above 2 dB was measured as the excitation amplitude was increased. Results demonstrated that the new membrane can be used to develop deep subwavelength absorbers with unique properties (1/54 wavelength in absorption and 1/618 in STL) able to tune their performance in response to an external stimulus while autonomously regaining their properties in case of damage thanks to their self-healing ability.

Identifiers

PMID36273018
PMCPMC9588055
OpenAlexW4307130866

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.