Mechanical analysis of PDMS material using biaxial test

João E. Ribeiro; Hernani Lopes; Pedro Martins; Manuel Braz-César; João E. Ribeiro; Hernani Lopes; Pedro Martins; Manuel Braz-César

doi:10.3934/matersci.2019.1.97

AIMS Materials Science

2019, Volume 6, Issue 1: 97-110. doi: 10.3934/matersci.2019.1.97

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Research article Topical Sections

Mechanical analysis of PDMS material using biaxial test

1.
School of Technology and Management, Polytechnic Institute of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
2.
CIMO, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
3.
Mechanical Engineering Department, ISEP, Polytechnic Institute of Porto, Dr. António Bernardino de Almeida Street, 431, 4200-072 Porto, Portugal
4.
Mechanical Engineering Department, FEUP, Dr. Roberto Frias Street, 4200-465 Porto, Portugal
5.
CONSTRUCT-LESE, FEUP, Dr. Roberto Frias Street, 4200-465 Porto, Portugal

Received: 18 July 2018 Accepted: 29 November 2018 Published: 19 February 2019

Polydimethylsiloxane (PDMS) materials are classified as a silicone and commonly present a hyperelastic behaviour. Many researchers have studied PDMS in recent years, motivated by its applications in the biomedical field. In the present manuscript, a biaxial tensile test performed at different speeds is described. The displacement field for the different experimental test conditions is measured using the digital image correlation technique. Numerical studies were also carried out using the most popular constitutive models, namely Mooney-Rivlin, Yeoh and Ogden, for comparison with the experimental measurements. From the experimental displacement profile taken along the central section of each sample, that this tensile test presents linear behaviour; it is an independent speed test. The same conclusion can be found from the numerical results. The results of the numerical simulation show that they are strongly dependent on the constitutive model of the material. The numerical simulations with the Yeoh model presented the most accurate results for PDMS behaviour. Another important conclusion is that the digital image correlation technique is well suited for the analysis of hyperelastic materials.
- hyperelasticity,
- polydimethylsiloxane (PDMS),
- experimental tests,
- numerical simulation,
- digital image correlation
Citation: João E. Ribeiro, Hernani Lopes, Pedro Martins, Manuel Braz-César. Mechanical analysis of PDMS material using biaxial test[J]. AIMS Materials Science, 2019, 6(1): 97-110. doi: 10.3934/matersci.2019.1.97

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Abstract

Polydimethylsiloxane (PDMS) materials are classified as a silicone and commonly present a hyperelastic behaviour. Many researchers have studied PDMS in recent years, motivated by its applications in the biomedical field. In the present manuscript, a biaxial tensile test performed at different speeds is described. The displacement field for the different experimental test conditions is measured using the digital image correlation technique. Numerical studies were also carried out using the most popular constitutive models, namely Mooney-Rivlin, Yeoh and Ogden, for comparison with the experimental measurements. From the experimental displacement profile taken along the central section of each sample, that this tensile test presents linear behaviour; it is an independent speed test. The same conclusion can be found from the numerical results. The results of the numerical simulation show that they are strongly dependent on the constitutive model of the material. The numerical simulations with the Yeoh model presented the most accurate results for PDMS behaviour. Another important conclusion is that the digital image correlation technique is well suited for the analysis of hyperelastic materials.

References

[1]	Ophir J, Céspedes I, Ponnekanti H, et al. (1991) Elastography: A quantitative method for imaging the elasticity of biological tissues. Ultrasonic Imaging 13: 111–134. doi: 10.1177/016173469101300201
[2]	Greenleaf J, Fatemi M, Insana M (2003) Selected methods for imaging elastic properties of biological tissues. Annu Rev Biomed Eng 5: 57–78. doi: 10.1146/annurev.bioeng.5.040202.121623
[3]	Choi D (2016) Mechanical characterization of biological tissues: Experimental methods based on mathematical modeling. Biomed Eng Lett 6: 181–195. doi: 10.1007/s13534-016-0222-6
[4]	Bronzino JD (2000) Biomedical Engineering Handbook, 2 Eds., Florida: CRC Press LLC.
[5]	Enderle JD, Blanchard SM, Bronzino JD (2005) Introduction to biomedical engineering, 2 Eds., Oxford: Elsevier Academic Press.
[6]	Holzapfel GA (2000) Nonlinear Solid Mechanics: A Continuum Approach for Engineering, West Sussex: John Wiley & Sons Ltd.
[7]	Besson J, Cailletaud G, Chaboche J, et al. (2010) Non-Linear Mechanics of Materials, London: Springer Science & Business Media.
[8]	Yannas I, Burke J (1980) Design of an artificial skin. I. Basic design principles. J Biomed Mater Res 14: 65–81.
[9]	Tompkins R, Burke J (1990) Progress in burn treatment and the use of artificial skin. World J Surg 14: 819–824. doi: 10.1007/BF01670529
[10]	Sopyan I, Mel M, Ramesh S, et al. (2007) Porous hydroxyapatite for artificial bone applications. Sci Technol Adv Mat 8: 116–123. doi: 10.1016/j.stam.2006.11.017
[11]	Afonso J, Martins P, Girão M, et al. (2008) Mechanical properties of polypropylene mesh used in pelvic floor repair. Int Urogynecol J 19: 375–380. doi: 10.1007/s00192-007-0446-1
[12]	Pinho D, Bento D, Ribeiro J, et al. (2015) An In Vitro Experimental Evaluation of the Displacement Field in an Intracranial Aneurysm Model, In: Flores P, Viadero F, New Trends in Mechanism and Machine Science: From Fundamentals to Industrial Applications, Springer, 261–268.
[13]	Bernardi L, Hopf R, Ferrari A, et al. (2017) On the large strain deformation behavior of silicone-based elastomers for biomedical applications. Polym Test 58: 189–198. doi: 10.1016/j.polymertesting.2016.12.029
[14]	Aziz T, Waters M, Jagger R (2003) Analysis of the properties of silicone rubber maxillofacial prosthetic materials. J Dent 31: 67–74. doi: 10.1016/S0300-5712(02)00084-2
[15]	Gerratt A, Michaud H, Lacour S (2015) Elastomeric electronic skin for prosthetic tactile sensation. Adv Funct Mater 25: 2287–2295. doi: 10.1002/adfm.201404365
[16]	Yu YS, Zhao YP (2009) Deformation of PDMS membrane and microcantilever by a water droplet: Comparison between Mooney–Rivlin and linear elastic constitutive models. J Colloid Interf Sci 332: 467–476. doi: 10.1016/j.jcis.2008.12.054
[17]	Yu YS, Yang Z, Zhao YP (2008) Role of vertical component of surface tension of the droplet on the elastic deformation of PDMS membrane. J Adhes Sci Technol 22: 687–698.
[18]	Martins P, Peña E, Calvo B, et al. (2010) Prediction of nonlinear elastic behaviour of vaginal tissue: experimental results and model formulation. Comput Method Biomec 13: 327–337. doi: 10.1080/10255840903208197
[19]	Bakar MSA, Cheng MHW, Tang SM, et al. (2003) Tensile properties, tension-tension fatigue and biological response of polyetheretherketone-hydroxyapatite composites for load-bearing orthopedic implants. Biomaterials 24: 2245–2250. doi: 10.1016/S0142-9612(03)00028-0
[20]	Wang RZ, Weiner S (1997) Strain–structure relations in human teeth using Moiré fringes. J Biomech 31: 135–141.
[21]	Zaslansky P, Shahar R, Friesem AA, et al. (2006) Relations between shape, materials properties, and function in biological materials using laser speckle interferometry: in situ tooth deformation. Adv Funct Mater 16: 1925–1936. doi: 10.1002/adfm.200600120
[22]	Sujatha NU, Murukeshan VM (2004) Nondestructive inspection of tissue/tissue like phantom curved surfaces using digital speckle shearography. Opt Eng 43: 3055–3060. doi: 10.1117/1.1810531
[23]	Zhang DS, Arola DD (2004) Applications of digital image correlation to biological tissues. J Biomed Opt 9: 691–699. doi: 10.1117/1.1753270
[24]	Rodrigues R, Pinho D, Bento D, et al. (2016) Wall Expansion assessment of an intracranial aneurysm model by a 3D Digital Image Correlation system. Measurement 88: 262–270. doi: 10.1016/j.measurement.2016.03.045
[25]	Ribeiro J, Fernandes CS, Lima R (2017) Numerical Simulation of Hyperelastic Behaviour in Aneurysm Models, In: Tavares J, Natal Jorge R, Lecture Notes in Computational Vision and Biomechanics, Springer, 937–944.
[26]	Bischoff JE, Arruda EM, Grosh K (2000) Finite element modeling of human skin using an isotropic, nonlinear elastic constitutive model. J Biomech 33: 645–652. doi: 10.1016/S0021-9290(00)00018-X
[27]	Ribeiro J, Lopes H, Martins P (2017) A hybrid method to characterize the mechanical behaviour of biological hyperelastic tissues. Comput Method Biomech Biomed Eng Imag Visual 5: 157–164.
[28]	Sutton MA, Orteu JJ, Scheier HW (2009) Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts, Theory and Applications, Springer Science & Business Media.
[29]	Nunes LCS (2011) Mechanical characterization of hyperelastic polydimethylsiloxane by simple shear test. Mat Sci Eng A-Struct 528: 1799–1804. doi: 10.1016/j.msea.2010.11.025
[30]	Cardoso C, Fernandes C, Lima R, et al. (2018) Biomechanical analysis of PDMS channels using different hyperelastic numerical constitutive models. Mech Res Commun 90: 26–33. doi: 10.1016/j.mechrescom.2018.04.007
[31]	Madenci E, Guven I (2015) The Finite Element Method and Applications in Engineering Using ANSYS^®, New York: Springer.

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