Synthesis and Shape Memory Property of a MDI Based Liquid Crystalline Polyurethane

2016 ◽  
Vol 848 ◽  
pp. 132-139
Author(s):  
Yue Ting Li ◽  
Hui Qin Lian ◽  
Yan Ou Hu ◽  
Lei Zu ◽  
Xiu Guo Cui ◽  
...  

Liquid crystalline polyurethanes (LCPU) were prepared from 4,4’-methylenediphenyl diisocyanate (MDI), 1,6-hexanediol (HDO), 2,2-dimethylol propionic acid (DMPA) and polytetramethylene ether glycol (PTMG). The experiments synthesized three liquid crystalline polyurethane films with different soft/hard segment ratio. Chemical and structural characterization of the polyurethanes were investigated by Fourier transform infrared, X-ray diffraction, thermogravimetric analysis, differential scanning calorimeter and polarized microscopy respectively. Swelling rate and shape memory property were tested. The results indicated that the polyurethane with 62% soft segment and large group of carboxyl displayed excellent swelling and shape memory properties, and the shape recovery rate reached 100%. It was found that the crystallinity, thermal stability decreased and the temperature flexibility, water absorption and shape recovery rate increased with the increase of polytetramethylene ether glycol.

Polymers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1600 ◽  
Author(s):  
Shahbaj Kabir ◽  
Sunhee Lee

This study evaluated the shape memory and tensile property of 3D-printed sinusoidal sample/nylon composite for various thickness and cycles. Sinusoidal pattern of five thicknesses: 0.2 mm, 0.4 mm, 0.6 mm, 0.8 mm, and 1.0 mm were 3D-printed on nylon fabric by the fused deposition modeling (FDM) 3D printer using shape memory thermoplastic polyurethane (SMTPU). Afterward, shape memory and tensile property was investigated up to 50 shape memory cycles. The study found that 3D-printed sinusoidal sample/nylon composite had a 100% shape recovery ratio for various thicknesses up to 50 cycles. The average shape recovery rate gradually decreased from 3.0°/s to 0.7°/s whereas the response time gradually increased with the increase of a 3D-printed pattern thickness. The stress and initial modulus gradually increased with the increase of the cycle’s number. Thus, the shape memory property had a similar tendency for various cycles whereas the tensile property gradually increased with the increase of the cycle number. Moreover, this study demonstrated that this 3D-printed sinusoidal sample/nylon composite can go through more than 50 cycles without losing its tensile or shape memory property. This 3D-printed sinusoidal sample/nylon composite has vast potential as smart, reinforced, and protective clothing that requires complex three-dimensional shapes.


RSC Advances ◽  
2016 ◽  
Vol 6 (98) ◽  
pp. 95527-95534 ◽  
Author(s):  
Wei Liu ◽  
Ruoyu Zhang ◽  
Miaoming Huang ◽  
Xia Dong ◽  
Wei Xu ◽  
...  

Shape memory property of segmented poly(ester urethane) with poly(butylene 1,4-cyclohexanedicarboxylate) as the soft segment.


2021 ◽  
pp. 095400832199676
Author(s):  
Yuting Ouyang ◽  
Qiu Zhang ◽  
Xiukun Liu ◽  
Ruan Hong ◽  
Xu Xu ◽  
...  

Different ionic liquid modified graphene nanosheets (IG) were induced into polyimide (PI) to improve the tribological, thermal, and mechanical properties of shape memory IG/PI composites. The results demonstrated that when using 1-aminoethyl-3-methylimidazole bromide to modify graphene nanosheets (IG-1), the laser-driven shape recovery rate of IG-1/PI composites (IGPI-1) reached 73.02%, which was 49.36% higher than that of pure PI. In addition, the IGPI-1 composite materials reached the maximum shape recovery rate within 15 s. Additionally, under dry sliding, the addition of IG can significantly improve the tribological properties of composite materials. IGPI-1 exhibited the best self-lubricating properties. Compared with pure PI, the friction coefficient (0.19) and wear rate (2.62 × 10–5) mm3/Nm) were reduced by 44.1% and 24.2%, respectively, and the T10% of IGPI-1 increased by 32.2°C. The Tg of IGPI-1 reached 256.5°C, which was 8.4°C higher than that of pure PI. In addition, the tensile strength and modulus of IGPI-1 reached 82.3 MPa and 1.18 GPa, which were significantly increased by 33.6% and 29.8%, respectively, compared with pure PI. We hope that this work will be helpful for the preparation of shape memory materials with excellent tribological, thermal, and mechanical properties.


2017 ◽  
Vol 38 (23) ◽  
pp. 1700450 ◽  
Author(s):  
Wenkai Liu ◽  
Yun Zhao ◽  
Rong Wang ◽  
Jiehua Li ◽  
Jianshu Li ◽  
...  

2018 ◽  
Vol 51 (7-8) ◽  
pp. 626-643
Author(s):  
Chengliang Li ◽  
Xingxing Ji ◽  
Yang Lyu ◽  
Xinyan Shi

In this work, a damping material was successfully prepared by blending acrylic rubber (ACM) and polylactide (PLA) with sulfur and soap salt as the curing agents. A phenol-formaldehyde (PF) resin was used as a modifier. The effects of PF on the mechanical properties, damping properties, compatibility and shape memory properties of the blends were studied. The compatibility and damping properties were characterized by dynamic mechanical analysis, Fourier transform infrared spectroscope and microstructure analysis. The shape memory properties were examined by thermal mechanical analyser. The results revealed that the tensile strength of the blends was decreased and the toughness was increased with the increase of PF loadings. The introduction of PF improved the compatibility between PLA and ACM, which was deduced from the fact that the glass transition temperature of ACM was increased and the two loss factor peaks became closer. It was also found that the loss factor peak became higher and the effective damping temperature range became wider due to the formation of hydrogen bonding, implying that the damping properties of ACM/PLA blends were significantly improved. The ACM/PLA blends exhibited good dual-shape memory effect and its shape recovery ratio was increased by introduction of PF and raising the trigger temperature. The blends also exhibited good triple-shape memory property, which was dramatically improved by the introduction of PF. The mechanisms for the enhanced shape memory effects were then analysed.


2018 ◽  
Vol 56 (19) ◽  
pp. 1281-1286 ◽  
Author(s):  
Yan Jie Wang ◽  
Chen Yu Li ◽  
Zhi Jian Wang ◽  
Yiping Zhao ◽  
Li Chen ◽  
...  

2018 ◽  
Vol 192 ◽  
pp. 507-515 ◽  
Author(s):  
Yongtao Yao ◽  
Yun Luo ◽  
Haibao Lu ◽  
Bing Wang

2007 ◽  
Vol 8 (9) ◽  
pp. 2774-2780 ◽  
Author(s):  
Mei-Chin Chen ◽  
Hung-Wen Tsai ◽  
Yen Chang ◽  
Wei-Yun Lai ◽  
Fwu-Long Mi ◽  
...  

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