Creating three-dimensional magnetic functional microdevices via molding-integrated direct laser writing

Magnetically driven wireless miniature devices have become promising recently in healthcare, information technology, and many other fields. However, they lack advanced fabrication methods to go down to micrometer length scales with heterogeneous functional materials, complex three-dimensional (3D) geometries, and 3D programmable magnetization profiles. To fill this gap, we propose a molding-integrated direct laser writing-based microfabrication approach in this study and showcase its advanced enabling capabilities with various proof-of-concept functional microdevice prototypes. Unique motions and functionalities, such as metachronal coordinated motion, fluid mixing, function reprogramming, geometrical reconfiguring, multiple degrees-of-freedom rotation, and wireless stiffness tuning are exemplary demonstrations of the versatility of this fabrication method. Such facile fabrication strategy can be applied toward building next-generation smart microsystems in healthcare, robotics, metamaterials, microfluidics, and programmable matter.

Heat-Mitigated Design and Lorentz Force-Based Steering of an MRI-Driven Microcatheter toward Minimally Invasive Surgery

Catheters integrated with microcoils for electromagnetic steering under the high, uniform magnetic field within magnetic resonance (MR) scanners (3-7 Tesla) have enabled an alternative approach for active catheter operations. Achieving larger ranges of tip motion for Lorentz force-based steering have previously been dependent on using high power coupled with active cooling, bulkier catheter designs, or introducing additional microcoil sets along the catheter. This work proposes an alternative approach using a heat-mitigated design and actuation strategy for a magnetic resonance imaging (MRI)-driven microcatheter. A quad-configuration microcoil (QCM) design is introduced, allowing miniaturization of existing MRI-driven, Lorentz force-based catheters down to 1-mm diameters with minimal power consumption (0.44 W). Heating concerns are experimentally validated using noninvasive MRI thermometry. The Cosserat model is implemented within an MR scanner and results demonstrate a desired tip range up to 110° with 4° error. The QCM is used to validate the proposed model and power-optimized steering algorithm using an MRI-compatible neurovascular phantom and ex vivo kidney tissue. The power-optimized tip orientation controller conserves as much as 25% power regardless of the catheter's initial orientation. These results demonstrate the implementation of an MRI-driven, electromagnetic catheter steering platform for minimally invasive surgical applications without the need for camera feedback or manual advancement via guidewires. The incorporation of such system in clinics using the proposed design and actuation strategy can further improve the safety and reliability of future MRI-driven active catheter operations.

A Tissue Adhesion-Controllable and Biocompatible Small-Scale Hydrogel Adhesive Robot

Recently, the realization of minimally invasive medical interventions on targeted tissues using wireless small-scale medical robots has received an increasing attention. For effective implementation, such robots should have a strong adhesion capability to biological tissues and at the same time easy controlled detachment should be possible, which has been challenging. To address such issue, a small-scale soft robot with octopus-inspired hydrogel adhesive (OHA) is proposed. Hydrogels of different Young's moduli are adapted to achieve a biocompatible adhesive with strong wet adhesion by preventing the collapse of the octopus-inspired patterns during preloading. Introduction of poly(N-isopropylacrylamide) hydrogel for dome-like protuberance structure inside the sucker wall of polyethylene glycol diacrylate hydrogel provides a strong tissue attachment in underwater and at the same time enables easy detachment by temperature changes due to its temperature-dependent volume change property. It is finally demonstrated that the small-scale soft OHA robot can efficiently implement biomedical functions owing to strong adhesion and controllable detachment on biological tissues while operating inside the body. Such robots with repeatable tissue attachment and detachment possibility pave the way for future wireless soft miniature robots with minimally invasive medical interventions.

BirdBot achieves energy-efficient gait with minimal control using avian-inspired leg clutching

Designers of legged robots are challenged with creating mechanisms that allow energy-efficient locomotion with robust and minimalistic control. Sources of high energy costs in legged robots include the rapid loading and high forces required to support the robot's mass during stance and the rapid cycling of the leg's state between stance and swing phases. Here, we demonstrate an avian-inspired robot leg design, BirdBot, that challenges the reliance on rapid feedback control for joint coordination and replaces active control with intrinsic, mechanical coupling, reminiscent of a self-engaging and disengaging clutch. A spring tendon network rapidly switches the leg's slack segments into a loadable state at touchdown, distributes load among joints, enables rapid disengagement at toe-off through elastically stored energy, and coordinates swing leg flexion. A bistable joint mediates the spring tendon network's disengagement at the end of stance, powered by stance phase leg angle progression. We show reduced knee-flexing torque to a 10th of what is required for a nonclutching, parallel-elastic leg design with the same kinematics, whereas spring-based compliance extends the leg in stance phase. These mechanisms enable bipedal locomotion with four robot actuators under feedforward control, with high energy efficiency. The robot offers a physical model demonstration of an avian-inspired, multiarticular elastic coupling mechanism that can achieve self-stable, robust, and economic legged locomotion with simple control and no sensory feedback. The proposed design is scalable, allowing the design of large legged robots. BirdBot demonstrates a mechanism for self-engaging and disengaging parallel elastic legs that are contact-triggered by the foot's own lever-arm action.

High shear rate propulsion of acoustic microrobots in complex biological fluids

Untethered microrobots offer a great promise for localized targeted therapy in hard-to-access spaces in our body. Despite recent advancements, most microrobot propulsion capabilities have been limited to homogenous Newtonian fluids. However, the biological fluids present in our body are heterogeneous and have shear rate-dependent rheological properties, which limit the propulsion of microrobots using conventional designs and actuation methods. We propose an acoustically powered microrobotic system, consisting of a three-dimensionally printed 30-micrometer-diameter hollow body with an oscillatory microbubble, to generate high shear rate fluidic flow for propulsion in complex biofluids. The acoustically induced microstreaming flow leads to distinct surface-slipping and puller-type propulsion modes in Newtonian and non-Newtonian fluids, respectively. We demonstrate efficient propulsion of the microrobots in diverse biological fluids, including in vitro navigation through mucus layers on biologically relevant three-dimensional surfaces. The microrobot design and high shear rate propulsion mechanism discussed herein could open new possibilities to deploy microrobots in complex biofluids toward minimally invasive targeted therapy.

Miniature coiled artificial muscle for wireless soft medical devices

Wireless small-scale soft-bodied devices are capable of precise operation inside confined internal spaces, enabling various minimally invasive medical applications. However, such potential is constrained by the small output force and low work capacity of the current miniature soft actuators. To address this challenge, we report a small-scale soft actuator that harnesses the synergetic interactions between the coiled artificial muscle and radio frequency-magnetic heating. This wirelessly controlled actuator exhibits a large output force (~3.1 N) and high work capacity (3.5 J/g). Combining this actuator with different mechanical designs, its tensile and torsional behaviors can be engineered into different functional devices, such as a suture device, a pair of scissors, a driller, and a clamper. In addition, by assuming a spatially varying magnetization profile, a multilinked coiled muscle can have both magnetic field-induced bending and high contractile force. Such an approach could be used in various future untethered miniature medical devices.

Soft actuators for real-world applications

Inspired by physically adaptive, agile, reconfigurable and multifunctional soft-bodied animals and human muscles, soft actuators have been developed for a variety of applications, including soft grippers, artificial muscles, wearables, haptic devices and medical devices. However, the complex performance of biological systems cannot yet be fully replicated in synthetic designs. In this Review, we discuss new materials and structural designs for the engineering of soft actuators with physical intelligence and advanced properties, such as adaptability, multimodal locomotion, self-healing and multi-responsiveness. We examine how performance can be improved and multifunctionality implemented by using programmable soft materials, and highlight important real-world applications of soft actuators. Finally, we discuss the challenges and opportunities for next-generation soft actuators, including physical intelligence, adaptability, manufacturing scalability and reproducibility, extended lifetime and end-of-life strategies.

Light-driven carbon nitride microswimmers with propulsion in biological and ionic media and responsive on-demand drug delivery

We propose two-dimensional poly(heptazine imide) (PHI) carbon nitride microparticles as light-driven microswimmers in various ionic and biological media. Their high-speed (15 to 23 micrometer per second; 9.5 ± 5.4 body lengths per second) swimming in multicomponent ionic solutions with concentrations up to 5 M and without dedicated fuels is demonstrated, overcoming one of the bottlenecks of previous light-driven microswimmers. Such high ion tolerance is attributed to a favorable interplay between the particle's textural and structural nanoporosity and optoionic properties, facilitating ionic interactions in solutions with high salinity. Biocompatibility of these microswimmers is validated by cell viability tests with three different cell lines and primary cells. The nanopores of the swimmers are loaded with a model cancer drug, doxorubicin (DOX), resulting in a high (185%) loading efficiency without passive release. Controlled drug release is reported under different pH conditions and can be triggered on-demand by illumination. Light-triggered, boosted release of DOX and its active degradation products are demonstrated under oxygen-poor conditions using the intrinsic, environmentally sensitive and light-induced charge storage properties of PHI, which could enable future theranostic applications in oxygen-deprived tumor regions. These organic PHI microswimmers simultaneously address the current light-driven microswimmer challenges of high ion tolerance, fuel-free high-speed propulsion in biological media, biocompatibility, and controlled on-demand cargo release toward their biomedical, environmental, and other potential applications.

Order and information in the patterns of spinning magnetic micro-disks at the air-water interface

The application of the Shannon entropy to study the relationship between information and structures has yielded insights into molecular and material systems. However, the difficulty in directly observing and manipulating atoms and molecules hampers the ability of these systems to serve as model systems for further exploring the links between information and structures. Here, we use, as a model experimental system, hundreds of spinning magnetic micro-disks self-organizing at the air-water interface to generate various spatiotemporal patterns with varying degrees of order. Using the neighbor distance as the information-bearing variable, we demonstrate the links among information, structure, and interactions. We establish a direct link between information and structure without using explicit knowledge of interactions. Last, we show that the Shannon entropy by neighbor distances is a powerful observable in characterizing structural changes. Our findings are relevant for analyzing natural self-organizing systems and for designing collective robots.

Bayesian Machine Learning for Efficient Minimization of Defects in ALD Passivation Layers

Atomic layer deposition (ALD) is an enabling technology for encapsulating sensitive materials owing to its high-quality, conformal coating capability. Finding the optimum deposition parameters is vital to achieving defect-free layers; however, the high dimensionality of the parameter space makes a systematic study on the improvement of the protective properties of ALD films challenging. Machine-learning (ML) methods are gaining credibility in materials science applications by efficiently addressing these challenges and outperforming conventional techniques. Accordingly, this study reports the ML-based minimization of defects in an ALD-Al₂O₃ passivation layer for the corrosion protection of metallic copper using Bayesian optimization (BO). In all experiments, BO consistently minimizes the layer defect density by finding the optimum deposition parameters in less than three trials. Electrochemical tests show that the optimized layers have virtually zero film porosity and achieve five orders of magnitude reduction in corrosion current as compared to control samples. Optimized parameters of surface pretreatment using Ar/H₂ plasma, the deposition temperature above 200 °C, and 60 ms pulse time quadruple the corrosion resistance. The significant optimization of ALD layers presented in this study demonstrates the effectiveness of BO and its potential outreach to a broader audience, focusing on different materials and processes in materials science applications.

Permanent magnet array-driven navigation of wireless millirobots inside soft tissues

Creating wireless milliscale robots that navigate inside soft tissues of the human body for medical applications has been a challenge because of the limited onboard propulsion and powering capacity at small scale. Here, we propose around 100 permanent magnet array–based remotely propelled millirobot system that enables a cylindrical magnetic millirobot to navigate in soft tissues via continuous penetration. By creating a strong magnetic force trap with magnetic gradients on the order of 7 T/m inside a soft tissue, the robot is attracted to the center of the array even without active control. By combining the array with a motion stage and a fluoroscopic x-ray imaging system, the magnetic robot followed complex paths in an ex vivo porcine brain with extreme curvatures in sub-millimeter precision. This system enables future wireless medical millirobots that can deliver drugs; perform biopsy, hyperthermia, and cauterization; and stimulate neurons with small incisions in body tissues.

Shape-programmable liquid crystal elastomer structures with arbitrary three-dimensional director fields and geometries

Liquid crystal elastomers exhibit large reversible strain and programmable shape transformations, enabling various applications in soft robotics, dynamic optics, and programmable origami and kirigami. The morphing modes of these materials depend on both their geometries and director fields. In two dimensions, a pixel-by-pixel design has been accomplished to attain more flexibility over the spatial resolution of the liquid crystal response. Here we generalize this idea in two steps. First, we create independent, cubic light-responsive voxels, each with a predefined director field orientation. Second, these voxels are in turn assembled to form lines, grids, or skeletal structures that would be rather difficult to obtain from an initially connected material sample. In this way, the orientation of the director fields can be made to vary at voxel resolution to allow for programmable optically- or thermally-triggered anisotropic or heterogeneous material responses and morphology changes in three dimensions that would be impossible or hard to implement otherwise.

3D Printing of Elastomeric Bioinspired Complex Adhesive Microstructures

Bioinspired elastomeric structural adhesives can provide reversible and controllable adhesion on dry/wet and synthetic/biological surfaces for a broad range of commercial applications. Shape complexity and performance of the existing structural adhesives are limited by the used specific fabrication technique, such as molding. To overcome these limitations by proposing complex 3D microstructured adhesive designs, a 3D elastomeric microstructure fabrication approach is implemented using two-photon-polymerization-based 3D printing. A custom aliphatic urethane-acrylate-based elastomer is used as the 3D printing material. Two designs are demonstrated with two combined biological inspirations to show the advanced capabilities enabled by the proposed fabrication approach and custom elastomer. The first design focuses on springtail- and gecko-inspired hybrid microfiber adhesive, which has the multifunctionalities of side-surface liquid super-repellency, top-surface liquid super-repellency, and strong reversible adhesion features in a single fiber array. The second design primarily centers on octopus- and gecko-inspired hybrid adhesive, which exhibits the benefits of both octopus- and gecko-inspired microstructured adhesives for strong reversible adhesion on both wet and dry surfaces, such as skin. This fabrication approach could be used to produce many other 3D complex elastomeric structural adhesives for future real-world applications.

Machine Learning-Based and Experimentally Validated Optimal Adhesive Fibril Designs

Setae, fibrils located on a gecko's feet, have been an inspiration of synthetic dry microfibrillar adhesives in the last two decades for a wide range of applications due to unique properties: residue-free, repeatable, tunable, controllable and silent adhesion; self-cleaning; and breathability. However, designing dry fibrillar adhesives is limited by a template-based-design-approach using a pre-determined bioinspired T- or wedge-shaped mushroom tip. Here, a machine learning-based computational approach to optimize designs of adhesive fibrils is shown, exploring a much broader design space. A combination of Bayesian optimization and finite element methods creates novel optimal designs of adhesive fibrils, which are fabricated by two-photon-polymerization-based 3D microprinting and double-molding-based replication out of polydimethylsiloxane. Such optimal elastomeric fibril designs outperform previously proposed designs by maximum 77% in the experiments of dry adhesion performance on smooth surfaces. Furthermore, finite-element-analyses reveal that the adhesion of the fibrils is sensitive to the 3D fibril stem shape, tensile deformation, and fibril microfabrication limits, which contrast with the previous assumptions that mostly neglect the deformation of the fibril tip and stem, and focus only on the fibril tip geometry. The proposed computational fibril design could help design future optimal fibrils with less help from human intuition.

3D printed personalized magnetic micromachines from patient blood-derived biomaterials

While recent wireless micromachines have shown increasing potential for medical use, their potential safety risks concerning biocompatibility need to be mitigated. They are typically constructed from materials that are not intrinsically compatible with physiological environments. Here, we propose a personalized approach by using patient blood–derivable biomaterials as the main construction fabric of wireless medical micromachines to alleviate safety risks from biocompatibility. We demonstrate 3D printed multiresponsive microswimmers and microrollers made from magnetic nanocomposites of blood plasma, serum albumin protein, and platelet lysate. These micromachines respond to time-variant magnetic fields for torque-driven steerable motion and exhibit multiple cycles of pH-responsive two-way shape memory behavior for controlled cargo delivery and release applications. Their proteinaceous fabrics enable enzymatic degradability with proteinases, thereby lowering risks of long-term toxicity. The personalized micromachine fabrication strategy we conceptualize here can affect various future medical robots and devices made of autologous biomaterials to improve biocompatibility and smart functionality.

Liquid Crystal Structure of Supercooled Liquid Gallium and Eutectic Gallium-Indium

Understanding the origin of structural ordering in supercooled liquid gallium (Ga) has been a great scientific quest in the past decades. Here, reflective polarized optical microscopy on Ga sandwiched between glasses treated with rubbed polymers reveals the onset of an anisotropic reflection at 120 °C that increases on cooling and persists down to room temperature or below. The polymer rubbing usually aligns the director of thermotropic liquid crystals (LCs) parallel to the rubbing direction. On the other hand, when Ga is sandwiched between substrates that align conventional LC molecules normal to the surface, the reflection is isotropic, but mechanical shear force induces anisotropic reflection that relaxes in seconds. Such alignment effects and shear-induced realignment are typical to conventional thermotropic LCs and indicate a LC structure of liquid Ga. Specifically, Ga textures obtained by atomic force and scanning electron microscopy reveal the existence of a lamellar structure corresponding to a smectic LC phase, while the nanometer-thin lamellar structure is transparent under transmission polarized optical microscopy. Such spatial molecular arrangements may be attributed to dimer molecular entities in the supercooled liquid Ga. The LC structure observation of electrically conductive liquid Ga can provide new opportunities in materials science and LC applications.

Adaptive Self-Sealing Suction-Based Soft Robotic Gripper

While suction cups prevail as common gripping tools for a wide range of real-world parts and surfaces, they often fail to seal the contact interface when engaging with irregular shapes and textured surfaces. In this work, the authors propose a suction-based soft robotic gripper where suction is created inside a self-sealing, highly conformable and thin flat elastic membrane contacting a given part surface. Such soft gripper can self-adapt the size of its effective suction area with respect to the applied load. The elastomeric membrane covering edge of the soft gripper can develop an air-tight self-sealing with parts even smaller than the gripper diameter. Such gripper shows 4 times higher adhesion than the one without the membrane on various textured surfaces. The two major advantages, underactuated self-adaptability and enhanced suction performance, allow the membrane-based suction mechanism to grip various three-dimensional (3D) geometries and delicate parts, such as egg, lime, apple, and even hydrogels without noticeable damage, which can have not been gripped with the previous adhesive microstructures-based and active suction-based soft grippers. The structural and material simplicity of the proposed soft gripper design can have a broad use in diverse fields, such as digital manufacturing, robotic manipulation, transfer printing, and medical gripping.

Remote Modular Electronics for Wireless Magnetic Devices

Small-scale wireless magnetic robots and devices offer an effective solution to operations in hard-to-reach and high-risk enclosed places, such as inside the human body, nuclear plants, and vehicle infrastructure. In order to obtain functionalities beyond the capability of magnetic forces and torques exerted on magnetic materials used in these robotic devices, electronics need to be also integrated into them. However, their capabilities and power sources are still very limited compared to their larger-scale counterparts due to their much smaller sizes. Here, groups of milli/centimeter-scale wireless magnetic modules are shown to enable on-site electronic circuit construction and operation of highly demanding wireless electrical devices with no batteries, that is, with wireless power. Moreover, the mobility of the modular components brings remote modification and reconfiguration capabilities. When these small-scale robotic modules are remotely assembled into specific geometries, they can achieve, if not impossible, challenging electrical tasks for individual modules. Using such a method, several wireless and battery-free robotic devices are demonstrated using milli/centimeter-scale robotic modules, such as a wireless circuit to power light-emitting diodes with lower external fields, a device to actuate relatively high force-output shape memory alloy actuators, and a wireless force sensor, all of which can be modified on-site.

Physical intelligence as a new paradigm

Intelligence of physical agents, such as human-made (e.g., robots, autonomous cars) and biological (e.g., animals, plants) ones, is not only enabled by their computational intelligence (CI) in their brain, but also by their physical intelligence (PI) encoded in their body. Therefore, it is essential to advance the PI of human-made agents as much as possible, in addition to their CI, to operate them in unstructured and complex real-world environments like the biological agents. This article gives a perspective on what PI paradigm is, when PI can be more significant and dominant in physical and biological agents at different length scales and how bioinspired and abstract PI methods can be created in agent bodies. PI paradigm aims to synergize and merge many research fields, such as mechanics, materials science, robotics, mechanical design, fluidics, active matter, biology, self-assembly and collective systems, to enable advanced PI capabilities in human-made agent bodies, comparable to the ones observed in biological organisms. Such capabilities would progress the future robots and other machines beyond what can be realized using the current frameworks.

Wireless MRI-Powered Reversible Orientation-Locking Capsule Robot

Magnetic resonance imaging (MRI) scanners do not provide only high-resolution medical imaging but also magnetic robot actuation and tracking. However, the rotational motion capabilities of MRI-powered wireless magnetic capsule-type robots have been limited due to the very high axial magnetic field inside the MRI scanner. Medical functionalities of such robots also remain a challenge due to the miniature robot designs. Therefore, a wireless capsule-type reversible orientation-locking robot (REVOLBOT) is proposed that has decoupled translational motion and planar orientation change capability by locking and unlocking the rotation of a spherical ferrous bead inside the robot on demand. Such an on-demand locking/unlocking mechanism is achieved by a phase-changing wax material in which the ferrous bead is embedded inside. Controlled and on-demand hyperthermia and drug delivery using wireless power transfer-based Joule heating induced by external alternating magnetic fields are the additional features of this robot. The experimental feasibility of the REVOLBOT prototype with steerable navigation, medical function, and MRI tracking capabilities with an 1.33 Hz scan rate is demonstrated inside a preclinical 7T small-animal MRI scanner. The proposed robot has the potential for future clinical use in teleoperated minimally invasive treatment procedures with hyperthermia and drug delivery capabilities while being wirelessly powered and monitored inside MRI scanners.