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
  • [21] Understanding the thermomechanical behavior of graphene-reinforced conjugated polymer nanocomposites via coarse-grained modeling
    Wang, Yang
    Li, Zhaofan
    Sun, Dali
    Jiang, Naisheng
    Niu, Kangmin
    Giuntoli, Andrea
    Xia, Wenjie
    NANOSCALE, 2023, 15 (42) : 17124 - 17137
  • [22] Mechanical Properties of PC-ABS-Based Graphene-Reinforced Polymer Nanocomposites Fabricated by FDM Process
    Tambrallimath, Vijay
    Keshavamurthy, R.
    Bavan, Saravana D.
    Patil, Arun Y.
    Khan, T. M. Yunus
    Badruddin, Irfan Anjum
    Kamangar, Sarfaraz
    POLYMERS, 2021, 13 (17)
  • [23] Characterization of Interfacial Properties of Graphene-Reinforced Polymer Nanocomposites by Molecular Dynamics-Shear Deformation Model
    Park, Chanwook
    Yun, Gun Jin
    JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME, 2018, 85 (09):
  • [24] Composite negative stiffness structure with tunable and temperature-dependent properties induced by viscoelastic and shape-memory materials
    Liu, Tianzhen
    Deng, Ren
    Zhang, Yonglin
    Yang, Jinglei
    Cai, Jianguo
    COMPOSITES COMMUNICATIONS, 2024, 48
  • [25] Experimental and modelling of temperature-dependent mechanical properties of CNT/polymer nanocomposites
    Tamayo-Vegas, S.
    Lafdi, K.
    MATERIALS TODAY-PROCEEDINGS, 2022, 57 : 607 - 614
  • [26] Recovery torque modeling of carbon fiber reinforced shape memory polymer nanocomposites
    Shen, He
    Xu, Yunjun
    Liang, Fei
    Gou, Jihua
    Mabbott, Bob
    APPLIED PHYSICS LETTERS, 2013, 103 (20)
  • [27] Numerical homogenization of coiled carbon nanotube reinforced shape memory polymer nanocomposites
    Yarali, Ebrahim
    Baniassadi, Majid
    Baghani, Mostafa
    SMART MATERIALS AND STRUCTURES, 2019, 28 (03)
  • [28] Effect of curing temperature on shape memory properties of graphene oxide-carbon fiber hybrid-reinforced shape memory polymer composites
    Ma, Yuqin
    Guo, Haiyin
    Xu, Yi
    Li, Puda
    Xu, Wei
    Ji, Jing
    Shi, Yanni
    POLYMER COMPOSITES, 2024, 45 (03) : 2140 - 2155
  • [29] Barocaloric properties of reduced graphene oxide-shape memory polymer nanocomposites
    Weerasekera, Naveen
    Sudan, Kavish
    Ajjarapu, Kameswara Pavan Kumar
    Vithanage, Dinushika
    Weerahennedige, Hiruni
    Sumanasekera, Gamini
    Kate, Kunal
    Bhatia, Bikram
    JOURNAL OF MATERIALS SCIENCE, 2025, 60 (01) : 280 - 290
  • [30] Temperature-Dependent Shape-Memory Textiles: Physical Principles and Applications
    Ornaghi, Heitor Luiz
    Bianchi, Otavio
    TEXTILES, 2023, 3 (02): : 257 - 274