Programmable, Pattern‐Memorizing Polymer Surface

Wang, Zhen; Hansen, Curt; Ge, Qi; Maruf, Sajjad H.; Ahn, Dae Up; Hu, Qi; Ding, Yifu

doi:10.1002/adma.201101571

Cited by 118 publications

(97 citation statements)

References 31 publications

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“…The surface SME is not just limited to the conventional dual-SMPs. Utilizing the multi-SME, discussed in more detail later in this review, three sets of micro-patterns could be imprinted onto a multi-SMP at three different temperatures [106]. Interestingly, the individual sets of surface patterns could be independently recovered at three recovery temperatures.…”

Section: Phase Versus Molecular Switches and Thermal Versus Non-thermmentioning

confidence: 99%

Recent progress in shape memory polymer: New behavior, enabling materials, and mechanistic understanding

Zhao

Xie

2015

Progress in Polymer Science

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1,161

749

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Shape memory polymers (SMPs), as a class of programmable stimuliresponsive shape changing polymers, are attracting increasing attention from the standpoint of both fundamental research and technological innovations. Following a brief introduction of the conventional shape memory effect (SME), progress in new shape memory enabling mechanisms and triggering methods, variations of in shape memory forms (shape memory surfaces, hydrogels, and microparticles), new shape memory behavior (multi-SME and two-way-SME), and novel fabrication methods are reviewed. Progress in thermomechanical modeling of SMPs is also presented. Abbreviations:SCPs shape changing polymers; LCEs liquid crystalline elastomers; SMP shape memory polymer; SME shape memory effect; 2W two-way; 1W oneway; T trans transition temperature; T g glass transition temperature; T m melting temperature; T cl liquid crystal cleaning temperature; T d deformation temperature; T f shape fixing temperature; T c crystallization temperature; R f shape stability ratio; R r shape recovery ratio; T sw switching temperature; ε max maximum recoverable strain; σ max maximum recovery stress; SMC shape memory cycle; ε load strain under load; ε fixed strain; T r recovery Page 2 of 106 A c c e p t e d M a n u s c r i p t 2 temperature; ε rec recovered strain; V r strain recovery rate; T σmax temperature corresponding to σ max ; T sw,app apparent switching temperature; PCL poly(ε-caprolactone); SMPU shape memory polyurethane; EMU elemental memory unit; TME temperature memory effect; PU polyurethane; T i liquid-crystal isotropic transition temperature; T v vitrification temperature; CIE crystallization induced elongation; MIC melting induced contraction

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Section: Phase Versus Molecular Switches and Thermal Versus Non-thermmentioning

confidence: 99%

Recent progress in shape memory polymer: New behavior, enabling materials, and mechanistic understanding

Zhao

Xie

2015

Progress in Polymer Science

Self Cite

1,161

749

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“…When an environmental stimulus is applied, the SMP could either provide recovery stresses or return to their permanent shapes, depending on whether or not the external loads still exist, namely the constrained or free recovery condition [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] . Since SMPs can sense the environmental changes and then take reactions in a predetermined sequence with deformation, they are considered as a promising alternative for the future's spontaneous shape changing and tunable components in various applications such as microelectromechanical systems, surface patterning, biomedical devices, aerospace deployable structures and morphing structures [31][32][33][34][35][36][37][38][39] .…”

mentioning

confidence: 99%

Reduced time as a unified parameter determining fixity and free recovery of shape memory polymers

2014

Nat Commun

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231

179

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Shape memory polymers are at the forefront of recent materials research. Although the basic concept has been known for decades, recent advances in the research of shape memory polymers demand a unified approach to predict the shape memory performance under different thermo-temporal conditions. Here we report such an approach to predict the shape fixity and free recovery of thermo-rheologically simple shape memory polymers. The results show that the influence of programming conditions to free recovery can be unified by a reduced programming time that uniquely determines shape fixity, which consequently uniquely determines the shape recovery with a reduced recovery time. Furthermore, using the time-temperature superposition principle, shape recoveries under different thermo-temporal conditions can be extracted from the shape recovery under the reduced recovery time. Finally, a shape memory performance map is constructed based on a few simple standard polymer rheology tests to characterize the shape memory performance of the polymer.

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“…As a result, a surface pattern is formed but it is only a temporary structure and the deformation is reversed when the material is heated above T g or exposed to a favorable solvent, thereby recovering its permanent shape [16,24].…”

Section: Resultsmentioning

confidence: 98%

“…Because of the lack of plastic deformation, network polymers have previously only been patterned, albeit in a transient manner, utilizing the shape memory effect [16,24]. In this regard, stress relaxation or photoinduced plasticity of CANs, if successfully integrated with NIL, would enable reconfiguration of the permanent shape and/or surface patterns with feature sizes well below the diffraction limit of light.…”

Section: Introductionmentioning

confidence: 97%

Reconfigurable surface patterns on covalent adaptive network polymers using nanoimprint lithography

Cox

Sowan

Nair

et al. 2014

Polymer

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Programmable, Pattern‐Memorizing Polymer Surface

Cited by 118 publications

References 31 publications

Recent progress in shape memory polymer: New behavior, enabling materials, and mechanistic understanding

Recent progress in shape memory polymer: New behavior, enabling materials, and mechanistic understanding

Reduced time as a unified parameter determining fixity and free recovery of shape memory polymers

Reconfigurable surface patterns on covalent adaptive network polymers using nanoimprint lithography

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