Cilia metasurfaces for electronically programmable microfluidic manipulation.

Cilial pumping is a powerful strategy used by biological organisms to control and manipulate fluids at the microscale. However, despite numerous recent advances in optically, magnetically and electrically driven actuation, development of an engineered cilial platform with the potential for applications has remained difficult to realize1-6. Here we report on active metasurfaces of electronically actuated artificial cilia that can create arbitrary flow patterns in liquids near a surface. We first create voltage-actuated cilia that generate non-reciprocal motions to drive surface flows at tens of microns per second at actuation voltages of 1 volt. We then show that a cilia unit cell can locally create a range of elemental flow geometries. By combining these unit cells, we create an active cilia metasurface that can generate and switch between any desired surface flow pattern. Finally, we integrate the cilia with a light-powered complementary metal-oxide-semiconductor (CMOS) clock circuit to demonstrate wireless operation. As a proof of concept, we use this circuit to output voltage pulses with various phase delays to demonstrate improved pumping efficiency using metachronal waves. These powerful results, demonstrated experimentally and confirmed using theoretical computations, illustrate a pathway towards fine-scale microfluidic manipulation, with applications from microfluidic pumping to microrobotic locomotion.

Electronically integrated, mass-manufactured, microscopic robots.

Fifty years of Moore's law scaling in microelectronics have brought remarkable opportunities for the rapidly evolving field of microscopic robotics1-5. Electronic, magnetic and optical systems now offer an unprecedented combination of complexity, small size and low cost6,7, and could be readily appropriated for robots that are smaller than the resolution limit of human vision (less than a hundred micrometres)8-11. However, a major roadblock exists: there is no micrometre-scale actuator system that seamlessly integrates with semiconductor processing and responds to standard electronic control signals. Here we overcome this barrier by developing a new class of voltage-controllable electrochemical actuators that operate at low voltages (200 microvolts), low power (10 nanowatts) and are completely compatible with silicon processing. To demonstrate their potential, we develop lithographic fabrication-and-release protocols to prototype sub-hundred-micrometre walking robots. Every step in this process is performed in parallel, allowing us to produce over one million robots per four-inch wafer. These results are an important advance towards mass-manufactured, silicon-based, functional robots that are too small to be resolved by the naked eye.

Bifurcation instructed design of multistate machines.

We propose a design paradigm for multistate machines where transitions from one state to another are organized by bifurcations of multiple equilibria of the energy landscape describing the collective interactions of the machine components. This design paradigm is attractive since, near bifurcations, small variations in a few control parameters can result in large changes to the system's state providing an emergent lever mechanism. Further, the topological configuration of transitions between states near such bifurcations ensures robust operation, making the machine less sensitive to fabrication errors and noise. To design such machines, we develop and implement a new efficient algorithm that searches for interactions between the machine components that give rise to energy landscapes with these bifurcation structures. We demonstrate a proof of concept for this approach by designing magnetoelastic machines whose motions are primarily guided by their magnetic energy landscapes and show that by operating near bifurcations we can achieve multiple transition pathways between states. This proof of concept demonstration illustrates the power of this approach, which could be especially useful for soft robotics and at the microscale where typical macroscale designs are difficult to implement.

Gas-phase microactuation using kinetically controlled surface states of ultrathin catalytic sheets.

Biological systems convert chemical energy into mechanical work by using protein catalysts that assume kinetically controlled conformational states. Synthetic chemomechanical systems using chemical catalysis have been reported, but they are slow, require high temperatures to operate, or indirectly perform work by harnessing reaction products in liquids (e.g., heat or protons). Here, we introduce a bioinspired chemical strategy for gas-phase chemomechanical transduction that sequences the elementary steps of catalytic reactions on ultrathin (<10 nm) platinum sheets to generate surface stresses that directly drive microactuation (bending radii of 700 nm) at ambient conditions (T = 20 °C; Ptotal = 1 atm). When fueled by hydrogen gas and either oxygen or ozone gas, we show how kinetically controlled surface states of the catalyst can be exploited to achieve fast actuation (600 ms/cycle) at 20 °C. We also show that the approach can integrate photochemically controlled reactions and can be used to drive the reconfiguration of microhinges and complex origami- and kirigami-based microstructures.

Electronically configurable microscopic metasheet robots.

Shape morphing is vital to locomotion in microscopic organisms but has been challenging to achieve in sub-millimetre robots. By overcoming obstacles associated with miniaturization, we demonstrate microscopic electronically configurable morphing metasheet robots. These metabots expand locally using a kirigami structure spanning five decades in length, from 10 nm electrochemically actuated hinges to 100 µm splaying panels making up the ~1 mm robot. The panels are organized into unit cells that can expand and contract by 40% within 100 ms. These units are tiled to create metasheets with over 200 hinges and independent electronically actuating regions that enable the robot to switch between multiple target geometries with distinct curvature distributions. By electronically actuating independent regions with prescribed phase delays, we generate locomotory gaits. These results advance a metamaterial paradigm for microscopic, continuum, compliant, programmable robots and pave the way to a broad spectrum of applications, including reconfigurable micromachines, tunable optical metasurfaces and miniaturized biomedical devices.

Motor cortical inactivation impairs corrective submovements in mice performing a hold-still center-out reach task.

Holding still and aiming reaches to spatial targets may depend on distinct neural circuits. Using automated homecage training and a sensitive joystick, we trained freely moving mice to contact a joystick, hold their forelimb still, and then reach to rewarded target locations. Mice learned the task by initiating forelimb sequences with clearly resolved submillimeter-scale micromovements followed by millimeter-scale reaches to learned spatial targets. Hundreds of thousands of trajectories were decomposed into millions of kinematic submovements, while photoinhibition was used to test roles of motor cortical areas. Inactivation of both caudal and rostral forelimb areas preserved the ability to produce aimed reaches, but reduced reach speed. Inactivation specifically of contralateral caudal forelimb area (CFA) additionally impaired the ability to aim corrective submovements to remembered locations following target undershoots. Our findings show that motor cortical inactivations reduce the gain of forelimb movements but that inactivation specifically of contralateral CFA impairs corrective movements important for reaching a target location.NEW & NOTEWORTHY To test the role of different cortical areas in holding still and reaching to targets, this study combined home-cage training with optogenetic silencing as mice engaged in a learned center-out-reach task. Inactivation specifically of contralateral caudal forelimb area (CFA) impaired corrective movements necessary to reach spatial targets to earn reward.

Steering self-organisation through confinement.

Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement. Confinement is an action over a system that limits its units' translational and rotational degrees of freedom, thus also influencing the system's phase space probability density; it can function as either a catalyst or inhibitor of self-organisation. Confinement can then become a means to actively steer the emergence or suppression of collective phenomena in space and time. Here, to provide a common framework and perspective for future research, we examine the role of confinement in the self-organisation of soft-matter systems and identify overarching scientific challenges that need to be addressed to harness its full scientific and technological potential in soft matter and related fields. By drawing analogies with other disciplines, this framework will accelerate a common deeper understanding of self-organisation and trigger the development of innovative strategies to steer it using confinement, with impact on, e.g., the design of smarter materials, tissue engineering for biomedicine and in guiding active matter.

Rigidity and fracture of biopolymer double networks.

Tunable mechanics and fracture resistance are hallmarks of biological tissues whose properties arise from extracellular matrices comprised of double networks. To elucidate the origin of these desired properties, we study the shear modulus and fracture properties of a rigidly percolating double network model comprised of a primary network of stiff fibers and a secondary network of flexible fibers. We find that when the primary network density is just above its rigidity percolation threshold, the secondary network density can be tuned to facilitate stress relaxation via non-affine deformations and provide mechanical reinforcement. In contrast, when the primary network is far above its rigidity threshold, the double network is always stiff and brittle. These results highlight an important mechanism behind the tunability and resilience of biopolymer double networks: the secondary network can dramatically alter mechanical properties from compliant and ductile to stiff and brittle only when the primary network is marginally rigid.

Programming interactions in magnetic handshake materials.

The ability to rapidly manufacture building blocks with specific binding interactions is a key aspect of programmable assembly. Recent developments in DNA nanotechnology and colloidal particle synthesis have significantly advanced our ability to create particle sets with programmable interactions, based on DNA or shape complementarity. The increasing miniaturization underlying magnetic storage offers a new path for engineering programmable components for self assembly, by printing magnetic dipole patterns on substrates using nanotechnology. How to efficiently design dipole patterns for programmable assembly remains an open question as the design space is combinatorially large. Here, we present design rules for programming these magnetic interactions. By optimizing the structure of the dipole pattern, we demonstrate that the number of independent building blocks scales super linearly with the number of printed domains. We test these design rules using computational simulations of self assembled blocks, and experimental realizations of the blocks at the mm scale, demonstrating that the designed blocks give high yield assembly. In addition, our design rules indicate that with current printing technology, micron sized magnetic panels could easily achieve hundreds of different building blocks.

Magnetic handshake materials as a scale-invariant platform for programmed self-assembly.

Programmable self-assembly of smart, digital, and structurally complex materials from simple components at size scales from the macro to the nano remains a long-standing goal of material science. Here, we introduce a platform based on magnetic encoding of information to drive programmable self-assembly that works across length scales. Our building blocks consist of panels with different patterns of magnetic dipoles that are capable of specific binding. Because the ratios of the different panel-binding energies are scale-invariant, this approach can, in principle, be applied down to the nanometer scale. Using a centimeter-sized version of these panels, we demonstrate 3 canonical hallmarks of assembly: controlled polymerization of individual building blocks; assembly of 1-dimensional strands made of panels connected by elastic backbones into secondary structures; and hierarchical assembly of 2-dimensional nets into 3-dimensional objects. We envision that magnetic encoding of assembly instructions into primary structures of panels, strands, and nets will lead to the formation of secondary and even tertiary structures that transmit information, act as mechanical elements, or function as machines on scales ranging from the nano to the macro.

Multivalued Inverse Design: Multiple Surface Geometries from One Flat Sheet.

Designing flat sheets that can be made to deform into three-dimensional shapes is an area of intense research with applications in micromachines, soft robotics, and medical implants. Thus far, such sheets were designed to adopt a single target shape. Here, we show that through anisotropic deformation applied inhomogeneously throughout a sheet, it is possible to design a single sheet that can deform into multiple surface geometries upon different actuations. The key to our approach is development of an analytical method for solving this multivalued inverse problem. Such sheets open the door to fabricating machines that can perform complex tasks through cyclic transitions between multiple shapes. As a proof of concept, we design a simple swimmer capable of moving through a fluid at low Reynolds numbers.

Graphene-based bimorphs for micron-sized, autonomous origami machines.

Origami-inspired fabrication presents an attractive platform for miniaturizing machines: thinner layers of folding material lead to smaller devices, provided that key functional aspects, such as conductivity, stiffness, and flexibility, are persevered. Here, we show origami fabrication at its ultimate limit by using 2D atomic membranes as a folding material. As a prototype, we bond graphene sheets to nanometer-thick layers of glass to make ultrathin bimorph actuators that bend to micrometer radii of curvature in response to small strain differentials. These strains are two orders of magnitude lower than the fracture threshold for the device, thus maintaining conductivity across the structure. By patterning 2-[Formula: see text]m-thick rigid panels on top of bimorphs, we localize bending to the unpatterned regions to produce folds. Although the graphene bimorphs are only nanometers thick, they can lift these panels, the weight equivalent of a 500-nm-thick silicon chip. Using panels and bimorphs, we can scale down existing origami patterns to produce a wide range of machines. These machines change shape in fractions of a second when crossing a tunable pH threshold, showing that they sense their environments, respond, and perform useful functions on time and length scales comparable with microscale biological organisms. With the incorporation of electronic, photonic, and chemical payloads, these basic elements will become a powerful platform for robotics at the micrometer scale.

Bidirectional Self-Folding with Atomic Layer Deposition Nanofilms for Microscale Origami.

Origami design principles are scale invariant and enable direct miniaturization of origami structures provided the sheets used for folding have equal thickness to length ratios. Recently, seminal steps have been taken to fabricate microscale origami using unidirectionally actuated sheets with nanoscale thickness. Here, we extend the full power of origami-inspired fabrication to nanoscale sheets by engineering bidirectional folding with 4 nm thick atomic layer deposition (ALD) SiNx-SiO2 bilayer films. Strain differentials within these bilayers result in bending, producing microscopic radii of curvature. We lithographically pattern these bilayers and localize the bending using rigid panels to fabricate a variety of complex micro-origami devices. Upon release, these devices self-fold according to prescribed patterns. Our approach combines planar semiconductor microfabrication methods with computerized origami design, making it easy to fabricate and deploy such microstructures en masse. These devices represent an important step forward in the fabrication and assembly of deployable micromechanical systems that can interact with and manipulate micro- and nanoscale environments.

Embedding orthogonal memories in a colloidal gel through oscillatory shear.

It has recently been shown that in a broad class of disordered systems oscillatory shear training can embed memories of specific shear protocols in relevant physical parameters such as the yield strain. These shear protocols can be used to change the physical properties of the system and memories of the protocol can later be "read" out. Here we investigate shear training memories in colloidal gels, which include an attractive interaction and network structure, and discover that such systems can support memories both along and orthogonal to the training flow direction. We use oscillatory shear protocols to set and read out the yield strain memories and confocal microscopy to analyze the rearranging gel structure throughout the shear training. We find that the gel bonds remain largely isotropic in the shear-vorticity plane throughout the training process suggesting that structures formed to support shear along the training shear plane are also able to support shear along the orthogonal plane. Orthogonal memory extends the usefulness of shear memories to more applications and should apply to many other disordered systems as well.

Capillary Origami with Atomically Thin Membranes.

Small-scale optical and mechanical components and machines require control over three-dimensional structure at the microscale. Inspired by the analogy between paper and two-dimensional materials, origami-style folding of atomically thin materials offers a promising approach for making microscale structures from the thinnest possible sheets. In this Letter, we show that a monolayer of molybdenum disulfide (MoS2) can be folded into three-dimensional shapes by a technique called capillary origami, in which the surface tension of a droplet drives the folding of a thin sheet. We define shape nets by patterning rigid metal panels connected by MoS2 hinges, allowing us to fold micron-scale polyhedrons. Finally, we demonstrate that these shapes can be folded in parallel without the use of micropipettes or microfluidics by means of a microemulsion of droplets that dissolves into the bulk solution to drive folding. These results demonstrate controllable folding of the thinnest possible materials using capillary origami and indicate a route forward for design and parallel fabrication of more complex three-dimensional micron-scale structures and machines.

Automated home cage training of mice in a hold-still center-out reach task.

An obstacle to understanding neural mechanisms of movement is the complex, distributed nature of the mammalian motor system. Here we present a novel behavioral paradigm for high-throughput dissection of neural circuits underlying mouse forelimb control. Custom touch-sensing joysticks were used to quantify mouse forelimb trajectories with micron-millisecond spatiotemporal resolution. Joysticks were integrated into computer-controlled, rack-mountable home cages, enabling batches of mice to be trained in parallel. Closed loop behavioral analysis enabled online control of reward delivery for automated training. We used this system to show that mice can learn, with no human handling, a direction-specific hold-still center-out reach task in which a mouse first held its right forepaw still before reaching out to learned spatial targets. Stabilogram diffusion analysis of submillimeter-scale micromovements produced during the hold demonstrate that an active control process, akin to upright balance, was implemented to maintain forepaw stability. Trajectory decomposition methods, previously used in primates, were used to segment hundreds of thousands of forelimb trajectories into millions of constituent kinematic primitives. This system enables rapid dissection of neural circuits for controlling motion primitives from which forelimb sequences are built. NEW & NOTEWORTHY A novel joystick design resolves mouse forelimb kinematics with micron-millisecond precision. Home cage training is used to train mice in a hold-still center-out reach task. Analytical methods, previously used in primates, are used to decompose mouse forelimb trajectories into kinematic primitives.

Using Acoustic Perturbations to Dynamically Tune Shear Thickening in Colloidal Suspensions.

Colloidal suspensions in industrial processes often exhibit shear thickening that is difficult to control actively. Here, we use piezoelectric transducers to apply acoustic perturbations to dynamically tune the suspension viscosity in the shear-thickening regime. We attribute the mechanism of dethickening to the disruption of shear-induced force chains via perturbations that are large relative to the particle roughness scale. The ease with which this technique can be adapted to various flow geometries makes it a powerful tool for actively controlling suspension flow properties and investigating system dynamics.

Kirigami Mechanics as Stress Relief by Elastic Charges.

We develop a geometric approach to understand the mechanics of perforated thin elastic sheets, using the method of strain-dependent image elastic charges. This technique recognizes the buckling response of a hole under an external load as a geometrically tuned mechanism of stress relief. We use a diagonally pulled square paper frame as a model system to quantitatively test and validate our approach. Specifically, we compare nonlinear force-extension curves and global displacement fields in theory and experiment. We find a strong softening of the force response accompanied by curvature localization at the inner corners of the buckled frame. Counterintuitively, though in complete agreement with our theory, for a range of intermediate hole sizes, wider frames are found to buckle more easily than narrower ones. Upon extending these ideas to many holes, we demonstrate that interacting elastic image charges can provide a useful kirigami design principle to selectively relax stresses in elastic materials.

Tunable shear thickening in suspensions.

Shear thickening, an increase of viscosity with shear rate, is a ubiquitous phenomenon in suspended materials that has implications for broad technological applications. Controlling this thickening behavior remains a major challenge and has led to empirical strategies ranging from altering the particle surfaces and shape to modifying the solvent properties. However, none of these methods allows for tuning of flow properties during shear itself. Here, we demonstrate that by strategic imposition of a high-frequency and low-amplitude shear perturbation orthogonal to the primary shearing flow, we can largely eradicate shear thickening. The orthogonal shear effectively becomes a regulator for controlling thickening in the suspension, allowing the viscosity to be reduced by up to 2 decades on demand. In a separate setup, we show that such effects can be induced by simply agitating the sample transversely to the primary shear direction. Overall, the ability of in situ manipulation of shear thickening paves a route toward creating materials whose mechanical properties can be controlled.

Measuring and Manipulating the Adhesion of Graphene.

We present a technique to precisely measure the surface energies between two-dimensional materials and substrates that is simple to implement and allows exploration of spatial and chemical control of adhesion at the nanoscale. As an example, we characterize the delamination of single-layer graphene from monolayers of pyrene tethered to glass in water and maximize the work of separation between these surfaces by varying the density of pyrene groups in the monolayer. Control of this energy scale enables high-fidelity graphene-transfer protocols that can resist failure under sonication. Additionally, we find that the work required for graphene peeling and readhesion exhibits a dramatic rate-independent hysteresis, differing by a factor of 100. This work establishes a rational means to control the adhesion of 2D materials and enables a systematic approach to engineer stimuli-responsive adhesives and mechanical technologies at the nanoscale.