4D printed hydrogel scaffold with swelling-stiffening properties and programmable deformation for minimally invasive implantation
Bo LiuHui LiFengzhen MengZiyang XuLiuzhi HaoYuan YaoHao ZhuChenmin WangJun WuShaoquan BianWillima W LuWenguang LiuHaobo PanXiaoli Zhao
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Abstract The power of three-dimensional printing in designing personalized scaffolds with precise dimensions and properties is well-known. However, minimally invasive implantation of complex scaffolds is still challenging. Here, we develop amphiphilic dynamic thermoset polyurethanes catering for multi-material four-dimensional printing to fabricate supportive scaffolds with body temperature-triggered shape memory and water-triggered programmable deformation. Shape memory effect enables the two-dimensional printed pattern to be fixed into temporary one-dimensional shape, facilitating transcatheter delivery. Upon implantation, the body temperature triggers shape recovery of the one-dimensional shape to its original two-dimensional pattern. After swelling, the hydrated pattern undergoes programmable morphing into the desired three-dimensional structure because of swelling mismatch. The structure exhibits unusual soft-to-stiff transition due to the water-driven microphase separation formed between hydrophilic and hydrophobic chain segments. The integration of shape memory, programmable deformability, and swelling-stiffening properties makes the developed dynamic thermoset polyurethanes promising supportive void-filling scaffold materials for minimally invasive implantation.Keywords:
Thermosetting polymer
Morphing
Stiffening
Shape-memory polymer
Smart material
Soft Robotics
There is significant ongoing interest to develop smart structure technologies, such as those that can automatically detect their condition and/or actively change their geometry or material behaviors to adapt to adverse conditions or otherwise improve operational efficiency. Of the structural materials under development for smart structure applications, active smart materials are attracting increasing attentions due to their abilities to exhibit controlled variable stiffness through activation (e.g., thermal, electrical, or light activation) and experience extremely large deformations and shape changes without damage. Active smart materials, such as shape memory polymers, are currently being explored and show promise as morphing skins, replacements to mechanical hinges, and other structural components. Moreover, in a general sense any structure or structural component that is fully composed of active smart materials could have limitless shape-changing functionality if provided sufficient activation and actuation. Towards the design or control of smart structures to utilize such functionality, it is of paramount importance to develop strategies to efficiently solve the coupled multi-physics inverse problems of identifying the optimal activation stimulus and mechanical actuation to achieve desired morphing processes.
The objective of the present work is to develop and investigate a computational strategy for computationally efficient estimation of the parameters relating to the distribution and sequencing of activation and actuation for a morphing smart material structure or structural component to efficiently and effectively achieve a desired morphing function. This strategy combines a numerical representation of the morphing process with an optimization algorithm to estimate the activation and actuation parameters that best address cost functions and constraints relating to energy consumption, target shape change(s), morphing time, and/or damage prevention. In particular, the strategy is presented in the context of morphing structures or structural components composed of thermally responsive smart materials, and with specific properties based on thermally responsive shape memory polymers.
First, as a proof of concept, an initial computational framework is presented which combines a numerical representation of linear thermo-mechanical behavior of conceptual smart material structures with a non-gradient based optimization technique to identify the activation and actuation parameters to achieve the desired morphing process. The computational inverse mechanics approach is shown through numerical tests to provide a generalized and flexible means to facilitate the use of smart material structures to achieve desired morphing processes with controllable localized activation and actuation. Towards improving the computational efficiency, a variation of the computational framework based on a gradient-based optimization algorithm using the adjoint method is then presented. Numerical examples are shown to verify and test the computational approach, in which the synchronization of multiple activation and actuation parameters is optimized with respect to the energy cost and target shape changes in morphing skeletal structural components. The computational design approach with the adjoint method is shown to provide the capability to efficiently identify activation and actuation parameters to achieve desired morphing capabilities. Moreover, the computational approach is shown to be capable of determining energy-efficient design solutions for a diverse set of target shape changes with fixed instrumentation, providing the potential for substantial functionality beyond what could be expected through traditional empirical design strategies. Finally, to establish the theories and implementation aspects that would be applicable to a variety of structural behaviors, material types and morphing concepts, the efficient computational framework using the adjoint method is generalized to be applicable to various thermally-responsive smart materials. Numerical tests are shown to verify the generalized computational framework, in which the synchronization of multiple activation and actuation parameters is optimized with respect to energy cost and target shape changes in morphing structures with nonlinear thermo-mechanical behaviors (rather than the purely linear behaviors considered previously). In addition, the significant influence of the nonlinearity in the thermal modeling on the morphing processes, and ultimately the design solutions is explored.
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Untethered soft magnetoresponsive actuators (SMRAs), which can realize rapid shape transformation, have attracted widespread attention for their strategic applications in exploration, transportation, and minimally invasive medicine. It remains a challenge to fabricate SMRAs with complicated morphing modes (more than bending and folding), limiting their applications to simple shape-morphing and locomotion. Herein, a method integrating the ancient kirigami art and an advanced mechanical assembly method is proposed, which realizes 2D-to-3D and 3D-to-3D complicated shape-morphing and precise magnetization programming through cut-guided deformation. The kirigami-inspired SMRAs exhibit good robustness after actuating more than 10000 times. An integrated finite element analysis method is developed to quantitatively predict the shape transformation of SMRAs under magnetic actuation. By leveraging this method, a set of 3D curved responsive morphologies with programmed Gaussian curvature are fabricated (e.g., ellipsoid and saddle structures), specifically 3D multilayer structures and face-like shapes with different expressions, which are difficult to realize using previous approaches. Furthermore, a bionic-scaled soft crawling robot with significant obstacle surmounting ability is fabricated using the kirigami-inspired method. The ability of the method to achieve programmable SMRAs with versatile morphing modes may broaden its applications in soft robotics, color-switchable devices, and clinical treatments.
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Smart materials have intrinsic properties that change in a controlled fashion in response to external stimuli. Currently, the only smart materials with a significant clinical impact in cardiovascular implant design are shape memory alloys, particularly Nitinol. Recent prodigious progress in material science has resulted in the development of sophisticated shape memory polymers. In this article, we have reviewed the literature and outline the characteristics, advantages, and disadvantages of shape memory alloys and shape memory polymers which are relevant to clinical cardiovascular applications, and describe the potential of these smart materials for applications in coronary stents and transcatheter valves.
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Shape-morphing hydrogels can be widely used to develop artificial muscles, reconfigurable biodevices, and soft robotics. However, conventional approaches for developing shape-morphing hydrogels highly rely on composite materials or complex manufacturing techniques, which limit their practical applications. Herein, we develop an unprecedented strategy to edit the shape morphing of monocomponent natural polysaccharide hydrogel films via integrating gradient cross-linking density and geometry effect. Owing to the synergistic effect, the shape morphing of chitosan (CS) hydrogel films with gradient cross-linking density can be facilely edited by changing their geometries (length-to-width ratios or thicknesses). Therefore, helix, short-side rolling, and long-side rolling can be easily customized. Furthermore, various complex artificial 3D deformations such as artificial claw, horn, and flower can also be obtained by combining various flat CS hydrogel films with different geometries into one system, which can further demonstrate various shape transformations as triggered by pH. This work offers a simple strategy to construct a monocomponent hydrogel with geometry-directing programmable deformations, which provides universal insights into the design of shape-morphing polymers and will promote their applications in biodevices and soft robotics.
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In article number 1606580, Min-Woo Han and Sung-Hoon Ahn report soft morphing structures, in which loop-linked structures made from thermally responsive fibers allow the creation of three-dimensional morphologies, including flowers. Based on the design methodology of loop patterning, the proposed morphing structures enable three-dimensional volumetric transformation as well as bending, twisting, and torsional deformation, through functional fiber actuation.
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Abstract Shape‐morphing robotic structures can provide innovative approaches for various applications ranging from soft robotics to flexible electronics. However, the programmed deformation of direct‐3D printed polymer‐based structures cannot be separated from their subsequent conventional shape‐programming process. This work aims to simplify the fabrication process and demonstrates a rapid and adaptable approach for building stimulus‐responsive polymer‐based shape‐morphing structures of any shape. This is accomplished through mechanically assembling a set of identical self‐bending units in different patterns to form morphing structures using auxiliary hard connectors. A self‐bending unit fabricated by a 3D printing method can be actuated upon heating without the need for tethered power sources and is able to transform from a flat shape to a bending shape. This enables the assembled morphing‐structure to achieve the programmed integral shape without the need for a shape‐programming process. Differently assembled morphing structures used as independent robotic mechanisms are sequentially demonstrated with applications in biomimetic morphing structures, grasping mechanisms, and responsive electrical devices. This proposed approach based on a mechanical assembling method paves the way for rapid and simple prototyping of stimulus‐responsive polymer‐based shape‐morphing structures with arbitrary architectures for a variety of applications in deployable structures, bionic mechanisms, robotics, and flexible electronics.
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Soft Robotics
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