The Classification of the Stress-Strain Curve Zones on the Basis of their Validity to Study the Shape Memory Effect (SME) Property

Article Preview

Abstract:

This study attempts to emphasize a pre-step for determining the permitted deformations (strains) extents. This is for changing the original molecular architecture shape for the materials understudy (rubber band/stearic acid (RB/based SA) and Rubber band without stearic acid (RB without SA)). It is necessary as a basic controlling step in the choosing process of the appropriate programming method to show the shape memory effect (SME) property. By this property, the polymers are either described as shape memory effect (SME) or conventional polymers. If the material was proved to have the shape memory effect (SME) property, then it will be allowed to predict many thermo-mechanical properties. So for these materials, the (stress-strain) curve zones have been classified according to the ability of the deformation history memory, which can be erased and programmed again after the immediate removement of the applied tensile force. This can be achieved by calculating the residual strain ratio. The comparative results showed that the elastic and plateau zones were classified respectively as valid for the study of the (SME) property. While for the Hardening strain and fracture zones, they were classified as bad and very bad respectively for the study of this property.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

17-30

Citation:

Online since:

June 2022

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2022 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] L'Hocine L.H" Yahia, Shape memory polymer for biomedical application,, Elsevier LTd. All rights reserved, (2015).

Google Scholar

[2] M.J. Mahmoodi, M.K. Hassanzade –Aghdam and Ansari. Effects of added SIO2 nanoparticles on the thermal expansion behavior of shape memory polymer, 30(1), (2014): 32-44.

Google Scholar

[3] Guoqiang Li, Self- Healing composites: Shape memory –Polymer – Based structures,, John wiley and sons LTd. (2015).

Google Scholar

[4] David L.Safran Ski and Jack C. Griffis Shape –memory polymer Device Design,,(2017) Elsevier Inc.

Google Scholar

[5] Guoqiang and Wei Xu, Thermo mechanical behavior of thermoset shape memory polymer programmed by cold- compression: Testing and constitutive modeling, Journal of the mechanics and physics of solid, 59, (2011): 1231-1250.

DOI: 10.1016/j.jmps.2011.03.001

Google Scholar

[6] Rola Abbas and M.Al-maamori, Design and performance Evaluation of the Shape memory characterization machine for (SMPs),, American Institute of physics (APC), to be Published.

Google Scholar

[7] Martin Bothe, Shape Memory and Actuation Behavior of Semicrystalline Polymer Networks,, thesis submit led to fulfill the requirement for the degree of Doctor of philosophy (PhD) in mechanics, University at Berlin, (2014).

Google Scholar

[8] Andreas Lendlein and S.Kelch, Shape - memory polymer,, Angew. Chem. Int. Ed., 41, (2002): 2034-2057.

DOI: 10.1002/1521-3773(20020617)41:12<2034::aid-anie2034>3.0.co;2-m

Google Scholar

[9] H. A. Khonakdar, Seyed H J, and Sorour R, Jalil M, Hossein A. Investigation and Modeling of Temperature Dependence Recovery Behavior of Shape-Memory Crosslinked Polyethylene,, Macromolecular Journal, 16, (2007): 43-52.

DOI: 10.1002/mats.200600041

Google Scholar

[10] Guoqiang Li, Anqi Wang, Cold, warm, and hot programming of shape memory polymers ,, Journal of Polymer Science Physics, 54, (2016): 1319-1339.

DOI: 10.1002/polb.24041

Google Scholar

[11] Meng. H, Li G, A Review of Stimuli-responsive Shape Memory Polymer Composites,, United Kingdom, 54, (2013): 2199-2221.

DOI: 10.1016/j.polymer.2013.02.023

Google Scholar

[12] F. Castro, K. K. Westbrook, J. Hermiller, D. U. Ahn, Y. Ding, H. J. Qi,Time Dependent Recovery of Shape Memory Polymers,, Conference Proceedings of the Society for Experimental Mechanics Series book series 15, 3, (2011): 307-312.DOI 10.1007/978-1-4419-9794-4_42.

DOI: 10.1007/978-1-4419-9794-4_42

Google Scholar

[13] Kai Yu, Qi Ge and H. Jerry Qi,Reduced time as a unified parameter determining fixity and free recovery of shape memory polymers,. Nature communications, (2014): 1-9.

DOI: 10.1038/ncomms4066

Google Scholar

[14] Vanessa A. Fernandes, Davide S.A.De Focatiis, The role of deformation history on stress relaxation and stress memory of filled rubber,, Polymer Testing 40, (2014): 124-132.

DOI: 10.1016/j.polymertesting.2014.08.018

Google Scholar

[15] Frank K, Joerg C. Tiller,Shape memory natural rubber,, Journal of Polymer Science Part B: Polymer Physics, 54(14), (2016): 1381-1388.

DOI: 10.1002/polb.24040

Google Scholar

[16] R. Abishera, R. Velmurugan, K. V. Nagendra Gopal, Shape memory behavior of cold-programmed carbon fiber reinforced CNT/epoxy composites,. Materials Research Express, 5(8), (2018): 1-19.

DOI: 10.1088/2053-1591/aaa60c

Google Scholar

[17] Ming Lei, Zhen Chen, Haibao Lu and Kai Yu, Recent progress in shape memory polymer composites: methods, properties, applications and prospects,, Journal Nanotechnology Reviews; 8(1), (2019): 327–351.

DOI: 10.1515/ntrev-2019-0031

Google Scholar

[18] Avraham .I. B, Irina. G, Asaf. B, Noam E, and Ronen V, The Effect of POSS Type on the Shape Memory Properties of Epoxy-Based Nanocomposites,. Journal Molecules, 25(18), (2020): 1-19.

Google Scholar

[19] Ingrid A. Rousseau, and Tao Xie, Shape memory epoxy: Composition, structure, properties and shape memory performances,, J. Mater. Chem, 20(17), (2010): 3431–3441.

DOI: 10.1039/b923394f

Google Scholar

[20] Jiquan Li , Yadong Jia, Taidong Li, Zhou Zhu, Hangchao Zhou, Xiang Peng, and Shaofei Jiang, Tensile Behavior of Acrylonitrile Butadiene Styrene at Different Temperatures,, Hindawi: Advances in Polymer Technology, 2020,(2020):Article ID 8946591, 10 pages.

DOI: 10.1155/2020/8946591

Google Scholar

[21] B. Heuwers, A. Beckel, A. Krieger, F. Katzenberg, J. C. Tiller, Shape-Memory Natural Rubber: An Exceptional Material for Strain and Energy Storage, Macromolecular Chemistry and Physics, 214, (2013): 912−923.

DOI: 10.1002/macp.201200649

Google Scholar

[22] Bever, de, J. J. M. Dynamic behaviour of rubber and rubber like materials, Technische Universiteit Eindhoven, literature survey. (DCT rapporten; 6,(1992): 1-71.

Google Scholar

[23] N M Setyadewi, N. Indrajati and N. Darmawan, Mechanical properties and curing characteristics of shape memory natural rubber,, IOP Conference Series: Materials Science and Engineering, 541 (2019): 012012(1-6).

DOI: 10.1088/1757-899x/541/1/012012

Google Scholar

[24] J. Ciambella, A. Paolone and S. Vidoli, Memory decay rates of viscoelastic solids: not too slow, but not too fast either,. J.Rheologica Acta, 50, (2011): 661–674.

DOI: 10.1007/s00397-011-0549-y

Google Scholar

[25] A.Favata, P. Podio-Guidugli and G. Tomassetti, Energy Splitting Theorems for Materials with Memory,, Journal of Elasticity, 101,(2010): 59–67.

DOI: 10.1007/s10659-010-9244-y

Google Scholar

[26] D. Drozdov1 and N. Dusunceli. Mullins-type phenomena in polypropylene,, Int. J. of Appl. Math. and Mech,8(11)(2012): 82-98.

Google Scholar

[27] par Xavier Morelle, Mechanical characterization and physics based modeling of highly-crosslinked epoxy resin, thesis for the degree of doctor philosophy (PhD) in mechanics , Universite catholique de Louvain (UCL), Institute of Mechanics, (2015).

Google Scholar

[28] V. Izraylit, M. Heuche, O. E.C. Gould, K. Kratz, A. Lendlein, Strain recovery and stress relaxation behaviour of multiblock copolymer blends physically cross-linked with PLA stereocomplexation,, J. Polymer, 209, (2020): 122984.

DOI: 10.1016/j.polymer.2020.122984

Google Scholar