Background <p>Mechanical testing of soft materials requires specialized equipment. Unfortunately, commercial devices are expensive and, thus, prohibitive for many laboratories. Additionally, non-uniformity in device use across laboratories contributes to the reproducibility crisis in experimental mechanics. Finally, even expensive commercial devices are usually not adaptable and do not allow for customization, for example, to integrate <i>in-situ</i> imaging modalities into the test protocols.</p> Objective <p>Therefore, our objective was to develop a device that is accessible, customizable, and compatible with various imaging modalities.</p> Methods <p>We set out to develop a device capable of operating in biaxial, off-biaxial, and uniaxial modes under monotonic loading, cyclic testing, and stress relaxation. To this end, we combined a 3D printed device platform with off-the-shelf motors, load cells, and LabVIEW control.</p> Results <p>Our device is easy to use, relatively inexpensive (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\approx \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≈</mo> </math></EquationSource> </InlineEquation> $15,000), and fully customizable. To showcase the device, we first obtained equibiaxial stress-strain curves of rubber samples under large deformation. Additionally, we tracked in-plane strains via digital image correlation and through-thickness deformations via optical coherence tomography. In our second and third examples, we produced strip biaxial and biaxial stress-strain curves under repeated step and stress relaxation loading of PCL meshes and a tricuspid valve leaflet, respectively. Simultaneously, we imaged the microstructure of the materials via confocal and multiphoton microscopy.</p> Conclusion <p>In conclusion, we have designed a device that is accessible, customizable, and compatible with various imaging modalities. We hope that our technology enables other labs to conduct soft material tests and that it improves the reproducibility of soft material mechanical data.</p>

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An Affordable, Openly-Shared Planar Biaxial Device to Study the Multiscale Mechanics of Soft Materials

  • A. Madariaga,
  • M. J. Lohr,
  • C.-Y. Lin,
  • J. Fuhg,
  • A. Buganza Tepole,
  • M.K. Rausch

摘要

Background

Mechanical testing of soft materials requires specialized equipment. Unfortunately, commercial devices are expensive and, thus, prohibitive for many laboratories. Additionally, non-uniformity in device use across laboratories contributes to the reproducibility crisis in experimental mechanics. Finally, even expensive commercial devices are usually not adaptable and do not allow for customization, for example, to integrate in-situ imaging modalities into the test protocols.

Objective

Therefore, our objective was to develop a device that is accessible, customizable, and compatible with various imaging modalities.

Methods

We set out to develop a device capable of operating in biaxial, off-biaxial, and uniaxial modes under monotonic loading, cyclic testing, and stress relaxation. To this end, we combined a 3D printed device platform with off-the-shelf motors, load cells, and LabVIEW control.

Results

Our device is easy to use, relatively inexpensive ( \(\approx \) $15,000), and fully customizable. To showcase the device, we first obtained equibiaxial stress-strain curves of rubber samples under large deformation. Additionally, we tracked in-plane strains via digital image correlation and through-thickness deformations via optical coherence tomography. In our second and third examples, we produced strip biaxial and biaxial stress-strain curves under repeated step and stress relaxation loading of PCL meshes and a tricuspid valve leaflet, respectively. Simultaneously, we imaged the microstructure of the materials via confocal and multiphoton microscopy.

Conclusion

In conclusion, we have designed a device that is accessible, customizable, and compatible with various imaging modalities. We hope that our technology enables other labs to conduct soft material tests and that it improves the reproducibility of soft material mechanical data.