Rubber-like electrically conductive polymeric materials with shape memory

2013 ◽  
Vol 22 (5) ◽  
pp. 055024 ◽  
Author(s):  
H P Cui ◽  
C L Song ◽  
W M Huang ◽  
C C Wang ◽  
Y Zhao
Polymers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1900
Author(s):  
Ramin Hosseinnezhad ◽  
Iurii Vozniak ◽  
Fahmi Zaïri

The paper discusses the possibility of using in situ generated hybrid polymer-polymer nanocomposites as polymeric materials with triple shape memory, which, unlike conventional polymer blends with triple shape memory, are characterized by fully separated phase transition temperatures and strongest bonding between the polymer blends phase interfaces which are critical to the shape fixing and recovery. This was demonstrated using the three-component system polylactide/polybutylene adipateterephthalate/cellulose nanofibers (PLA/PBAT/CNFs). The role of in situ generated PBAT nanofibers and CNFs in the formation of efficient physical crosslinks at PLA-PBAT, PLA-CNF and PBAT-CNF interfaces and the effect of CNFs on the PBAT fibrillation and crystallization processes were elucidated. The in situ generated composites showed drastically higher values of strain recovery ratios, strain fixity ratios, faster recovery rate and better mechanical properties compared to the blend.


2008 ◽  
Vol 47-50 ◽  
pp. 714-717 ◽  
Author(s):  
Xin Lan ◽  
Jin Song Leng ◽  
Yan Ju Liu ◽  
Shan Yi Du

A new system of thermoset styrene-based shape-memory polymer (SMP) filled with carbon black (CB) is investigated. To realize the electroactive stimuli of SMP, the electrical conductivity of SMP filled with various amounts of CB is characterized. The percolation threshold of electrically conductive SMP filled with CB is about 3% (volume fraction of CB), which is much lower than many other electrically conductive polymers. When applying a voltage of 30V, the shape recovery process of SMP/CB(10 vol%) can be realized in about 100s. In addition, the thermomechanical properties are also characterized by differential scanning calorimetery (DSC).


2016 ◽  
Vol 97 ◽  
pp. 93-99
Author(s):  
Jin Lian Hu ◽  
Harishkumar Narayana

Materials, structures and systems, responsive to an external stimulus are smart and adaptive to our human demands. Among smart materials, polymers with shape memory effect are at the forefront of research leading to comprehensive publications and wide applications. In this paper, we extend the concept of shape memory polymers to stress memory ones, which have been discovered recently. Like shape memory, stress memory represents a phenomenon where the stress in a polymer can be programmed, stored and retrieved reversibly with an external stimulus such as temperature and magnetic field. Stress memory may be mistaken as the recovery stress which was studied quite broadly. Our further investigation also reveals that stress memory is quite different from recovery stress containing multi-components including elastic and viscoelastic forces in addition to possible memory stress. Stress memory could be used into applications such as sensors, pressure garments, massage devices, electronic skins and artificial muscles. The current revelation of stress memory potentials is emanated from an authentic application of memory fibres, films, and foams in the smart compression devices for the management of chronic and therapeutic disorders.


2017 ◽  
Vol 9 (37) ◽  
pp. 32270-32279 ◽  
Author(s):  
Yu Zheng ◽  
Xiaoying Ji ◽  
Min Yin ◽  
Jiabin Shen ◽  
Shaoyun Guo

2011 ◽  
Vol 2011 (1) ◽  
pp. 000090-000098 ◽  
Author(s):  
Michelle Velderrain ◽  
Matthew Lindberg

Silicones have been used for decades in aerospace and other harsh environments where temperature extremes are common. As the level of sophistication increases for electronic devices to serve these industries where failure is not an option, the material supplier has to also be able to meet these needs. Silicones are polymeric materials composed primarily of repeating silicon and oxygen bonds, known as siloxanes, which can be optimized for various chemical and physical properties by incorporating different organic groups onto the silicon atom. Employing advanced processing techniques to the siloxane system can also greatly reduce mobile siloxane molecules to reduce contamination that can cause electronic failures during assembly or operation. Siloxane based polymeric systems are also unique polymers compared to standard organic based materials in that they have a large free volume that imparts a low modulus which absorbs stresses during thermal cycling as well as not degrading at continuous operating temperatures up to 250 C. They are also slightly polar which allows the incorporation of fillers to impart a variety of unique properties. Filler technology is also a rapidly growing enterprise where fillers with various particle sizes and shapes can be added to silicones to impart key properties such as maintaining electric conductivity at elevated temperatures. This paper will explain fundamentals of silicone chemistry and processing related to getting the optimal performance in harsh environments. A case study comparing two different electrically conductive fillers and how they can influence the electrical conductivity at elevated temperatures will be presented.


2017 ◽  
Vol 8 (26) ◽  
pp. 3867-3873 ◽  
Author(s):  
Xingjian Li ◽  
Yi Pan ◽  
Jingjuan Lai ◽  
Ruiqing Wu ◽  
Zhaohui Zheng ◽  
...  

A well-defined shape memory network with high homogeneity was engineered via step-growth thiol-norbornene photopolymerization.


Author(s):  
Richard V. Beblo ◽  
Lisa Mauck Weiland

Presented is a multiscale modeling method applied to light activated shape memory polymers (LASMP). LASMP are a new class of shape memory polymer (SMP) being developed for applications where a thermal stimulus is undesired. Rotational Isomeric State (RIS) theory is used to build a molecular scale model of the polymer chain yielding a list of distances between the predicted cross-link locations, or r-values. The r-values are then fit with Johnson probability density functions and used with Boltzmann statistical mechanics to predict stress as a function of strain of the phantom network. Junction constraint theory is then used to calculate the stress contribution due to interactions with neighboring chains, resulting in previously unattainable numerically accurate Young’s modulus predictions based on the molecular formula of the polymer. The system is modular in nature and thus lends itself well to being adapted for specific applications. The results of the model are presented with experimental data for confirmation of correctness along with discussion of the potential of the model to be used to computationally adjust the chemical composition of LASMP to achieve specified material characteristics, greatly reducing the time and resources required for formula development.


2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Liangliang Cao ◽  
Liwei Wang ◽  
Cihui Zhou ◽  
Xin Hu ◽  
Liang Fang ◽  
...  

Shape-memory polymers (SMPs) are one kind of smart polymers and can change their shapes in a predefined manner under stimuli. Shape-memory effect (SME) is not a unique ability for specific polymeric materials but results from the combination of a tailored shape-memory creation procedure (SMCP) and suitable molecular architecture that consists of netpoints and switching domains. In the last decade, the trend toward the exploration of SMPs to recover structures at micro-/nanoscale occurs with the development of SMPs. Here, the progress of the exploration in micro-/nanoscale structures, particles, and fibers of SMPs is reviewed. The preparation method, SMCP, characterization of SME, and applications of surface structures, free-standing particles, and fibers of SMPs at micro-/nanoscale are summarized.


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