A Shape Memory Polymer with Improved Shape Recovery

2004 ◽  
Vol 855 ◽  
Author(s):  
Changdeng Liu ◽  
Patrick T. Mather
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Shape Memory ◽  
Shape Memory Polymer ◽  
Model Fit ◽  
Mechanical Reinforcement ◽  
Conducting Filler ◽  
Thermal Conducting ◽  
Thermally Actuated ◽  
Triggering Process

ABSTRACTThermally actuated shape memory polymers (SMPs) interest, both academically and industrially, due to their ability to memorize a permanent shape that is set during processing and a temporary shape that is later programmed by manipulation above a critical temperature, either Tg or Tm. However, the thermal triggering process for SMPs is usually retarded compared to that of shape memory alloys, because the thermal conductivity of polymers is much lower (<0.30 W/m.K). In the present study, we incorporated a highly thermal conducting filler into a shape memory matrix to increase its thermal conductivity and therefore, shorten the heat transfer progress. A mathematical was worked out that quantitatively relates the material's thermal conductivity with the heat transfer time, τ, also defined as a shape memory induction time. The model fit nicely with our experimental data. In addition, mechanical reinforcement was observed with the addition of this rigid thermal conducting filler.

scholarly journals Thermomechanical performance and shape recovery behaviour of shape memory polymer nanocomposite incorporated with hexagonal boron nitride

2017 ◽  
Vol 46 (1) ◽  
pp. 79-83 ◽  
Author(s):  
Zhenghong Li ◽  
Haibao Lu ◽  
Yongtao Yao ◽  
Long Lin
Keyword(s):  
Thermal Conductivity ◽  
Shape Memory ◽  
Shape Recovery ◽  
Hexagonal Boron Nitride ◽  
Shape Memory Polymer ◽  
Polymer Nanocomposite ◽  
Thermomechanical Properties ◽  
Content Type ◽  
Thermally Responsive ◽  
Thermally Actuated

Purpose The purpose of this paper is to develop an effective approach to significantly improve the thermomechanical properties of shape memory polymer (SMP) nanocomposites that show fast thermally responsive shape recovery. Design/methodology/approach Hexagonal boron nitrides (h-BNs) were incorporated into polymer matrix in an attempt to improve the thermal conductivity and thermally responsive shape recovery behaviour of SMP, respectively. Thermally actuated shape recovery behaviour was recorded and monitored instrumentally. Findings The results show that both glass transition temperature (Tg) and thermomechanical properties of the SMP nanocomposites have been progressively improved with increasing concentration of h-BNs. Analytical results also suggest that the fast-responsive recovery behaviour of the SMP nanocomposite incorporated with h-BNs was due to the increased thermal conductivity. Research limitations/implications A simple way for fabricating SMP nanocomposites with enhanced thermally responsive shape recovery based on the incorporation of h-BNs was developed. Originality/value The outcome of this study may help fabrication of SMP nanocomposites with fast responsive recovery behaviour.

Stretching-Induced Thermal Conductivity Change in Shape-Memory Polymer Composites

2020 ◽  
Author(s):  
Stephen Hostler ◽  
Mohnish Peswani ◽  
Han Yang ◽  
Harrison Paul ◽  
Stuart J. Rowan ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Shape Memory ◽  
Thermal Management ◽  
Energy Savings ◽  
Thermal State ◽  
Shape Memory Polymer ◽  
Applied Strain ◽  
Proof Of Concept ◽  
Conductivity Change ◽  
The Matrix

Abstract Active thermal materials like thermal diodes, regulators, and switches have the potential to revolutionize thermal management, creating an opportunity for significant energy savings. We present results on a thermal switching composite that changes its thermal conductivity based on applied strain. The composite is constructed of highly-crystalline, high aspect ratio cellulose nanocrystal (CNC) nanorods embedded in a shape-memory polymer matrix. The properties of the matrix allow for changes to the thermal state to be indefinitely retained and also for the state to be reversed. A switching ratio of two is achieved for this proof-of-concept composite. By comparing the measured results to a Maxwell mixing model, the primary drivers of the thermal conductivity change are traced to changes in crystallinity of the matrix and CNC alignment.

Modeling of Heat Transfer in Shape Memory Polymer Nanocomposites

2012 ◽  
Author(s):  
John Carrell ◽  
Hong-Chao Zhang ◽  
Kevin Long ◽  
Senay Imam
Keyword(s):  
Heat Transfer ◽  
Shape Memory ◽  
Polymer Nanocomposites ◽  
Deformation Process ◽  
Thermal Field ◽  
Shape Memory Polymer ◽  
Equation Model ◽  
Heat Transfer Characteristics ◽  
Thermal Change ◽  
Mechanical Methods

Diaplex MS5520, SMP Technologies, Inc. transition temperature 55°C, was filled with varying proportions (5 wt.%, 15.00 wt.%, and 25 wt.%) of magnetite nanoparticles, NanoArc and Iron(III) Oxide; 20–40 nm APS Powder from Alfa Aesar. The SMP nanocomposite was tested by thermomechanical methods, derived thermo-magnetic-mechanical methods, and shape memory methods. The results of such methods show an ability of the SMP nanocomposite to be controlled in shape deformation and recovery with an applied thermal then applied magnetic field. This paper focuses on the thermal field needed to help trigger the SMP nanocomposite. The objective of the study is to investigate the heat transfer characteristics of a SMP filled with magnetite nanoparitcles. A transient heat equation model is developed, and numerical simulation is performed in Sundance to show the underlying state of thermal change in recovery and deformation process. Result of the simulations roughly match those observed in the experiment.

A constitutive model for shape memory polymers with application to torsion of prismatic bars

2012 ◽  
Vol 23 (2) ◽  
pp. 107-116 ◽  
Author(s):  
Mostafa Baghani ◽  
Reza Naghdabadi ◽  
Jamal Arghavani ◽  
Saeed Sohrabpour
Keyword(s):  
Heat Transfer ◽  
Constitutive Model ◽  
Shape Memory ◽  
Shape Memory Polymer ◽  
Shape Memory Polymers ◽  
Second Law Of Thermodynamics ◽  
Considerable Effect ◽  
Heat Transfer Analysis ◽  
Internal Variables ◽  
Rate Dependent

In this article, satisfying the second law of thermodynamics, we present a 3D constitutive model for shape memory polymers. The model is based on an additive decomposition of the strain into four parts. Also, evolution laws for internal variables during both cooling and heating processes are proposed. Since temperature has considerable effect on the shape memory polymer behavior, for simulation of a shape memory polymer–based structure, it is required to perform a heat-transfer analysis. Commonly, an experimentally observed temperature rate–dependent behavior of shape memory polymers is justified by a rate-dependent glassy temperature, but using the heat-transfer analysis, it is shown that the glassy temperature could be considered as a constant material parameter. To this end, implementing the constitutive model within a nonlinear finite element code, we simulate torsion of a shape memory polymer rectangular bar and a circular tube. Moreover, we compare the predicted results with experimental data recently reported in the literature, which shows a good agreement.

Effect of microstructural features on the thermal conducting behavior of carbon nanofiber–reinforced styrene-based shape memory polymer composites

2020 ◽  
Vol 31 (14) ◽  
pp. 1716-1730
Author(s):  
Ning Liu ◽  
Lilin Jiang
Keyword(s):  
Thermal Resistance ◽  
Shape Memory ◽  
Polymer Composites ◽  
Carbon Nanofibers ◽  
Carbon Nanofiber ◽  
Shape Memory Polymer ◽  
Interfacial Thermal Resistance ◽  
Interfacial Resistance ◽  
Thermal Conducting ◽  
Thermal Conductivities

This article presents a novel hierarchical micromechanics approach to carefully investigate the thermal conductivities of styrene-based shape memory polymer composites containing carbon nanofibers. The research is mainly focused on the simulation of carbon nanofiber/shape memory polymer interfacial thermal resistance and carbon nanofiber agglomeration as two critical microstructural features of carbon nanofiber–shape memory polymer composite materials. The computed results are compared with the available experimental measurements. It is found that both of those microstructural factors along with carbon nanofiber non-straight shape significantly affecting the thermal conducting behavior must be incorporated in the analysis to have a more realistic prediction. The thermal conductivity of carbon nanofiber–reinforced shape memory polymer composites reduces significantly due to the effects of carbon nanofiber/shape memory polymer interfacial resistance and carbon nanofiber agglomeration and waviness. It is suggested to uniformly disperse carbon nanofibers into the shape memory polymers and reduce interfacial resistance for improving the carbon nanofiber–styrene composite thermal properties. In addition, the present study reveals that the effective thermal conductivities of the shape memory polymer composites reinforced by aligned carbon nanofibers are greatly enhanced over those of the shape memory polymer composites containing randomly dispersed carbon nanofibers. The effects of percentage, waviness parameters, degree of agglomeration, material properties, length and diameter of carbon nanofibers as well as interfacial thermal resistance value on the thermal behavior of carbon nanofiber–reinforced styrene-based shape memory polymer composites are investigated.

Thermal Properties of Polyurethane Shape Memory Polymer Filled With Magnetite Particles

2011 ◽  
Author(s):  
Bernd Weidenfeller ◽  
Mathias Anhalt ◽  
Hauke Marquardt ◽  
Frank R. Schilling ◽  
Muhammad Y. Razzaq ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Thermal Diffusivity ◽  
Specific Heat ◽  
Shape Memory ◽  
Specific Heat Capacity ◽  
Shape Memory Polymer ◽  
Particle Sizes ◽  
Magnetite Particles ◽  
Increasing Temperature

Temperature dependent thermal diffusivity (295K ≤ T ≤ 375K), specific heat capacity (290K ≤ T ≤ 380K) and thermal conductivity (300K ≤ T ≤ 340K) were measured on extrusion compounded and injection molded polyurethane shape memory polymers filled with different volume fractions (0%, 10%, 20%, 30%, 40%) of magnetite particles (10μm, 50μm and 150μm). With increasing particle content thermal diffusivity arises from α(PU + 0% Fe3O4) ≈ 0.13mm2/s to α(PU + 40% Fe3O4) ≈ 0.31mm2/s whereas d = 10μm particle sizes lead to higher values than larger particle sizes. Values measured for 150μm large particles are lying between values of composites with 10μm and 50μm particle sizes in the whole investigated temperature range. For higher filler contents differences in thermal diffusivity between composites of different particle sizes disappear. Thermal diffusivity decreases with increasing temperature, while thermal conductivity is increasing from λ(PU+0% Fe3O4) ≈ 0.2W/mK to λ(PU+40% Fe3O4) ≈ 0.6W/mK. Corresponding to glass transition temperatures of the polymer, the specific heat capacity shows a rise between 300K and 320K and a decrease between 350K and 370K.

scholarly journals Thermally Conductive Shape Memory Polymer Composites Filled with Boron Nitride for Heat Management in Electrical Insulation

Polymers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 2191
Author(s):  
Andrzej Rybak ◽  
Lukasz Malinowski ◽  
Agnieszka Adamus-Wlodarczyk ◽  
Piotr Ulanski
Keyword(s):  
Thermal Conductivity ◽  
Boron Nitride ◽  
Shape Memory ◽  
Polymer Composites ◽  
Heat Dissipation ◽  
Shape Memory Polymer ◽  
Electrical Insulation ◽  
Heat Management ◽  
Crosslinked Polymer ◽  
Thermally Conductive

The evaluation of a possible application of functional shrinkable materials in thermally conductive electrical insulation elements was investigated. The effectiveness of an electron beam and gamma radiation on the crosslinking of a selected high density polyethylene grade was analyzed, both qualitatively and quantitatively. The crosslinked polymer composites filled with ceramic particles were successfully fabricated and tested. On the basis of the performed investigation, it was concluded that the selected filler, namely a boron nitride powder, is suitable for the preparation of the crosslinked polymer composites with enhanced thermal conductivity. The shape memory effect was fully observed in the crosslinked samples with a recovery factor reaching nearly 99%. There was no significant influence of the crosslinking, stretching, and recovery of the polymer composite during shape memory phenomenon on the value of thermal conductivity. The proposed boron nitride filled polyethylene composite subjected to crosslinking is a promising candidate for fabrication of thermally shrinkable material with enhanced heat dissipation functionality for application as electrically insulating components.

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