Micromechanics evaluation of equivalent temperature-dependent stiffness of graphene-reinforced shape memory polymer nanocomposites

被引:2
|
作者
Umer, Usama [1 ]
Abidi, Mustufa Haider [1 ]
Almutairi, Zeyad [2 ]
El-Meligy, Mohammed A. [1 ]
机构
[1] King Saud Univ, Adv Mfg Inst, POB 800, Riyadh 11421, Saudi Arabia
[2] King Saud Univ, Coll Engn, Dept Mech Engn, POB 800, Riyadh 11421, Saudi Arabia
关键词
Shape memory polymer; Graphene; Stiffness; Non-flatness; Aggregation; MECHANICAL-PROPERTIES; NANOPLATELETS; INTERPHASE; MODEL;
D O I
10.1016/j.rineng.2024.102978
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Effective stiffness of shape memory polymer (SMP) nanocomposites filled with graphene nanoplatelets (GNPs) is analyzed at various temperatures using an efficient micromechanical scheme. Three microstructural features, including aggregation and non-flatness shape of graphene, and GNP/SMP interphase are incorporated. It is found that addition of GNPs can enhance the temperature-dependent stiffness of SMP nanocomposites. The nanocomposite stiffness is more improved by (I) increasing the volume fraction, (II) increasing the length (or width) and (III) decreasing the thickness of uniformly dispersed GNPs. Also, an effective way to remarkably augment the nanocomposite stiffness is suggested to be alignment of the GNPs into the SMP matrix. However, the aggregated state and non-flatness configuration of GNPs act as two lowering factors of SMP nanocomposite stiffness. From mechanical viewpoint on designing a SMP nanocomposite, the interfacial zone should be as stiff and thick as possible. It is observed at very low volume fraction that the non-flatness structure and interfacial zone should be included in the modeling to give better predictions as compared with experiments. At high volume fraction, the GNP aggregation in addition to those two factors should be reflected in the analysis to encompass a more realistic micromechanical scheme.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Prediction of temperature-dependent free recovery behaviors of amorphous shape memory polymers
    Ge, Qi
    Yu, Kai
    Ding, Yifu
    Qi, H. Jerry
    SOFT MATTER, 2012, 8 (43) : 11098 - 11105
  • [42] Temperature-dependent compatibilizing effect of graphene oxide as a compatibilizer for immiscible polymer blends
    Ye, Shibing
    Cao, Yewen
    Feng, Jiachun
    Wu, Peiyi
    RSC ADVANCES, 2013, 3 (21) : 7987 - 7995
  • [43] Water-induced shape memory effect of graphene oxide reinforced polyvinyl alcohol nanocomposites
    Qi, Xiaodong
    Yao, Xuelin
    Deng, Sha
    Zhou, Tiannan
    Fu, Qiang
    JOURNAL OF MATERIALS CHEMISTRY A, 2014, 2 (07) : 2240 - 2249
  • [44] Solution-processed white graphene-reinforced ferroelectric polymer nanocomposites with improved thermal conductivity and dielectric properties for electronic encapsulation
    Deshmukh, Kalim
    Ahamed, M. Basheer
    Sadasivuni, Kishor Kumar
    Ponnamma, Deepalekshmi
    Deshmukh, Rajendra R.
    Trimukhe, Ajinkya M.
    Pasha, S. K. Khadheer
    Polu, Anji Reddy
    AlMaadeed, Mariam Al-Ali
    Chidambaram, K.
    JOURNAL OF POLYMER RESEARCH, 2017, 24 (02) : 1 - 14
  • [45] Micromechanics-based characterization of elastic properties of shape memory polymer nanocomposites containing SiO2 nanoparticles
    Hassanzadeh-Aghdam, Mohammad Kazem
    Mahmoodi, Mohammad Javad
    JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, 2018, 29 (11) : 2392 - 2405
  • [46] Temperature-dependent shear failure modes and tensile strength model of CNT/polymer nanocomposites
    Zhang, Xuyao
    Li, Weiguo
    Zheng, Shifeng
    Zhao, Ziyuan
    He, Yi
    Wang, Shubin
    Zhang, Xi
    Shen, Zheng
    Xu, Jiasen
    COMPOSITES COMMUNICATIONS, 2021, 25
  • [47] Solution-processed white graphene-reinforced ferroelectric polymer nanocomposites with improved thermal conductivity and dielectric properties for electronic encapsulation
    Kalim Deshmukh
    M. Basheer Ahamed
    Kishor Kumar Sadasivuni
    Deepalekshmi Ponnamma
    Rajendra R. Deshmukh
    Ajinkya M. Trimukhe
    S. K. Khadheer Pasha
    Anji Reddy Polu
    Mariam Al-Ali AlMaadeed
    K. Chidambaram
    Journal of Polymer Research, 2017, 24
  • [48] Graphene Polyimide Nanocomposites; Thermal, Mechanical, and High-Temperature Shape Memory Effects
    Yoonessi, Mitra
    Shi, Ying
    Scheiman, Daniel A.
    Lebron-Colon, Marisabel
    Tigelaar, Dean M.
    Weiss, R. A.
    Meador, Michael A.
    ACS NANO, 2012, 6 (09) : 7644 - 7655
  • [49] Force sensor utilizing stiffness change of shape-memory polymer based on temperature
    Takashima K.
    Kamizono H.
    Takenaka M.
    Mukai T.
    ROBOMECH Journal, 4 (1):
  • [50] Recent advancement in self-healing graphene polymer nanocomposites, shape memory, and coating materials
    Idumah, Christopher Igwe
    Odera, S. R.
    POLYMER-PLASTICS TECHNOLOGY AND MATERIALS, 2020, 59 (11): : 1167 - 1190