Evidence map›Paper›PMID 36582477›Full record

ArticleHardwareX2023

A low-cost and open-source measurement system to determine the Young's and shear moduli and Poisson's ratio of soft materials using a Raspberry Pi camera module and 3D printed parts.

Matthew Sands, Jinki Kim

Abstract read
In one paragraph

Article in HardwareX, 2023. 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

2 authors.

Matthew SandsDepartment of Mechanical Engineering, Georgia Southern University, P.O. Box 8046, Statesboro, GA 30460, USA.
Jinki KimDepartment of Mechanical Engineering, Georgia Southern University, P.O. Box 8046, Statesboro, GA 30460, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in biomedical and engineering fields have greatly increased the need for understanding of soft structures. Soft materials such as gelatin and gelatin-based hydrogels have grown in popularity for use in a wide variety of applications including tissue engineering, biofabrication, and organ transplantation. With hydrogel structures being used in such demanding applications, it is crucial to properly characterize the dynamic behavior of these soft structures. Although there have been major improvements in measurement technology for determining the mechanical properties of soft, translucent materials, it remains quite challenging to reliably measure the Young's and shear moduli of these materials in a way that remains straightforward, low-cost, and non-contact. This research aims to address the weaknesses in modern measurement methods and develop a system suitable for characterizing the elastic moduli of soft materials that requires only four, inexpensive, off-the-shelf components. Utilizing a Raspberry Pi, stepping motor, and an inexpensive camera, the Young's and shear moduli of a gelatin column is measured five times. The standard deviation between measurement was observed to be less than 0.15% with high accuracy having an error of less than 4.6% when compared to relatively expensive, conventional measurement techniques.

Indexed as

HydrogelPhase-based motion estimationPoisson’s ratioShear modulusSoft materialYoung’s modulus

Identifiers

PMID36582477
PMCPMC9793308

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.