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Ilievski F.,Harvard University | Mazzeo A.D.,Harvard University | Shepherd R.F.,Harvard University | Chen X.,Harvard University | And 2 more authors.
Angewandte Chemie - International Edition

Soft robots: A methodology based on embedded pneumatic networks (PneuNets) is described that enables large-amplitude actuations in soft elastomers by pressurizing embedded channels. Examples include a structure that can change its curvature from convex to concave, and devices that act as compliant grippers for handling fragile objects (e.g., a chicken egg). © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

Ilievski F.,Harvard University | Mirica K.A.,Harvard University | Ellerbee A.K.,Harvard University | Whitesides G.M.,Harvard University | And 2 more authors.
Soft Matter

Although self-assembly (SA) in two dimensions (2D) is highly developed (especially using surfaces as a templates), SA in three dimensions (3D) has been more difficult. This paper describes a strategy for SA in 3D of diamagnetic plastic objects (mm- to cm-sized in this work, but in principle in sizes from ∼10 μm to m) supported in a paramagnetic fluid by a non-uniform magnetic field. The magnetic field and its gradient levitate the objects, template their self-assembly, and influence the shape of the assembled cluster. The structure of the 3D assembling objects can be further directed using hard mechanical templates - either the walls of the container or co-levitating components - which coincide spatially with the soft template of the magnetic field gradient. Mechanical agitation anneals the levitating clusters; the addition of photocurable adhesive, followed by UV illumination, can permanently fuse components together. © 2011 The Royal Society of Chemistry. Source

Grinthal A.,Harvard University | Kang S.H.,Harvard University | Kang S.H.,Wyss Institute for Biologically Inspired Engineering | Epstein A.K.,Harvard University | And 6 more authors.
Nano Today

As seen throughout the natural world, nanoscale fibers exhibit a unique combination of mechanical and surface properties that enable them to wind and bend around each other into an immense diversity of complex forms. In this review, we discuss how this versatility can be harnessed to transform a simple array of anchored nanofibers into a variety of complex, hierarchically organized dynamic functional surfaces. We describe a set of recently developed benchtop techniques that provide a straightforward way to generate libraries of fibrous surfaces with a wide range of finely tuned, nearly arbitrary geometric, mechanical, material, and surface characteristics starting from a single master array. These simple systematic controls can be used to program the fibers to bundle together, twist around each other into chiral swirls, and assemble into patterned arrays of complex hierarchical architectures. The delicate balance between fiber elasticity and surface adhesion plays a critical role in determining the shape, chirality, and higher order of the assembled structures, as does the dynamic evolution of the geometric, mechanical, and surface parameters throughout the assembly process. Hierarchical assembly can also be programmed to run backwards, enabling a wide range of reversible, responsive behaviors to be encoded through rationally chosen surface chemistry. These strategies provide a foundation for designing a vast assortment of functional surfaces with anti-fouling, adhesive, optical, water and ice repellent, memory storage, microfluidic, capture and release, and many more capabilities with the structural and dynamic sophistication of their biological counterparts. © 2012 Elsevier Ltd. All rights reserved. Source

Grinthal A.,Harvard University | Aizenberg J.,Harvard University | Aizenberg J.,Wyss Institute for Biologically Inspired Engineering | Aizenberg J.,Kavli Institute for Bionano Science and Technology
Chemical Society Reviews

A living organism is a bundle of dynamic, integrated adaptive processes: not only does it continuously respond to constant changes in temperature, sunlight, nutrients, and other features of its environment, but it does so by coordinating hierarchies of feedback among cells, tissues, organs, and networks all continuously adapting to each other. At the root of it all is one of the most fundamental adaptive processes: the constant tug of war between chemistry and mechanics that interweaves chemical signals with endless reconfigurations of macromolecules, fibers, meshworks, and membranes. In this tutorial we explore how such chemomechanical feedback-as an inherently dynamic, iterative process connecting size and time scales-can and has been similarly evoked in synthetic materials to produce a fascinating diversity of complex multiscale responsive behaviors. We discuss how chemical kinetics and architecture can be designed to generate stimulus-induced 3D spatiotemporal waves and topographic patterns within a single bulk material, and how feedback between interior dynamics and surface-wide instabilities can further generate higher order buckling and wrinkling patterns. Building on these phenomena, we show how yet higher levels of feedback and spatiotemporal complexity can be programmed into hybrid materials, and how these mechanisms allow hybrid materials to be further integrated into multicompartmental systems capable of hierarchical chemo-mechano-chemical feedback responses. These responses no doubt represent only a small sample of the chemomechanical feedback behaviors waiting to be discovered in synthetic materials, and enable us to envision nearly limitless possibilities for designing multiresponsive, multifunctional, self-adapting materials and systems. © 2013 The Royal Society of Chemistry. Source

News Article
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The distinctive troughs and crests of the human brain are not present in most animals; highly folded brains are seen only in a handful of species, including some primates, dolphins, elephants, and pigs. In humans, folding begins in fetal brains around the 20th week of gestation and is completed only when the child is about 18 months old. Why the brain is folded can be rationalized easily from an evolutionary perspective: Folded brains likely evolved to fit a large cortex into a small volume with the benefit of reducing neuronal wiring length and improving cognitive function. Less understood is how the brain folds. Several hypotheses have been proposed, but none have been directly used to make testable predictions. Now, researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences, collaborating with scientists in Finland and France, have shown that while many molecular processes are important in determining cellular events, what ultimately causes the brain to fold is a simple mechanical instability associated with buckling. The research is published in Nature Physics. Understanding how the brain folds could help unlock the inner workings of the brain and unravel brain-related disorders, as function often follows form. “We found that we could mimic cortical folding using a very simple physical principle and get results qualitatively similar to what we see in real fetal brains,” said L. Mahadevan, the Lola England de Valpine Professor of Applied Mathematics, Organismic and Evolutionary Biology, and Physics. The number, size, shape, and position of neuronal cells present during brain growth all lead to the expansion of the gray matter, known as the cortex, relative to the underlying white matter. This puts the cortex under compression, leading in turn to a mechanical instability that causes it to crease locally. “This simple evolutionary innovation, with iterations and variations, allows for a large cortex to be packed into a small volume, and is likely the dominant cause behind brain folding, known as gyrification,” said Mahadevan, who is also a core faculty member of the Wyss Institute for Biologically Inspired Engineering and a member of the Kavli Institute for Bionano Science and Technology, both at Harvard University. Mahadevan’s previous research found that the growth differential between the brain’s outer cortex and the soft tissue underneath explains the variations in the folding patterns across organisms in terms of just two parameters, the relative size of the brain and the relative expansion of the cortex. Building on this, the team collaborated with neuroanatomists and radiologists in France and directly tested this theory using data from human fetuses. The team made a 3-D, gel model of a smooth fetal brain based on MRI images. The model’s surface was coated with a thin layer of elastomer gel, as an analog of the cortex. To mimic cortical expansion, the gel brain was immersed in a solvent that is absorbed by the outer layer, causing it to swell relative to the deeper regions. Within minutes of being immersed in liquid solvent, the resulting compression led to the formation of folds similar in size and shape to real brains. The extent of the similarities surprised even the researchers. “When I put the model into the solvent, I knew there should be folding but I never expected that kind of close pattern compared to human brain,” said Jun Young Chung, a postdoctoral fellow and co-first author of the paper. “It looks like a real brain.” The key to those similarities lies in the unique shape of the human brain. “The geometry of the brain is really important because it serves to orient the folds in certain directions,” said Chung. “Our model, which has the same large-scale geometry and curvature as a human brain, leads to the formation of folds that matches those seen in real fetal brains quite well.” The largest folds seen in the model gel brain are similar in shape, size, and orientation to what is seen in the fetal brain, and can be replicated in multiple gel experiments. The smallest folds are not conserved, mirroring similar variations across human brains. “Brains are not exactly the same from one human to another, but we should all have the same major folds in order to be healthy,” said Chung. “Our research shows that if a part of the brain does not grow properly, or if the global geometry is disrupted, we may not have the major folds in the right place, which may cause dysfunction in the brain.”

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