Machine Learning-Based Shear Optimal Adhesive Microstructures with Experimental Validation.

Bioinspired fibrillar structures are promising for a wide range of disruptive adhesive applications. Especially micro/nanofibrillar structures on gecko toes can have strong and controllable adhesion and shear on a wide range of surfaces with residual-free, repeatable, self-cleaning, and other unique features. Synthetic dry fibrillar adhesives inspired by such biological fibrils are optimized in different aspects to increase their performance. Previous fibril designs for shear optimization are limited by predefined standard shapes in a narrow range primarily based on human intuition, which restricts their maximum performance. This study combines the machine learning-based optimization and finite-element-method-based shear mechanics simulations to find shear-optimized fibril designs automatically. In addition, fabrication limitations are integrated into the simulations to have more experimentally relevant results. The computationally discovered shear-optimized structures are fabricated, experimentally validated, and compared with the simulations. The results show that the computed shear-optimized fibrils perform better than the predefined standard fibril designs. This design optimization method can be used in future real-world shear-based gripping or nonslip surface applications, such as robotic pick-and-place grippers, climbing robots, gloves, electronic devices, and medical and wearable devices.

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.

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.

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 array­based 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.

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.

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.

Liquid-Superrepellent Bioinspired Fibrillar Adhesives.

Bioinspired elastomeric fibrillar surfaces have significant potential as reversible dry adhesives, but their adhesion performance is sensitive to the presence of liquids at the contact interface. Like their models in nature, many artificial mimics can effectively repel water, but fail when low-surface-tension liquids are introduced at the contact interface. A bioinspired fibrillar adhesive surface that is liquid-superrepellent even toward ultralow-surface-tension liquids while retaining its adhesive properties is proposed herein. This surface combines the effective adhesion principle of mushroom-shaped fibrillar arrays with liquid repellency based on double re-entrant fibril tip geometry. The adhesion performance of the proposed microfibril structures is retained even when low-surface-tension liquids are added to the contact interface. The extreme liquid repellency enables real-world applications of fibrillar adhesives for surfaces covered with water, oil, and other liquids. Moreover, fully elastomeric liquid-superrepellent surfaces are mechanically not brittle, highly robust against physical contact, and highly deformable and stretchable, which can increase the real-world uses of such antiwetting surfaces.

Magnetically Actuated Soft Capsule Endoscope for Fine-Needle Biopsy.

Wireless capsule endoscopes have revolutionized diagnostic procedures in the gastrointestinal (GI) tract by minimizing discomfort and trauma. Biopsy procedures, which are often necessary for a confirmed diagnosis of an illness, have been incorporated recently into robotic capsule endoscopes to improve their diagnostic functionality beyond only imaging. However, capsule robots to date have only been able to acquire biopsy samples of superficial tissues of the GI tract, which could generate false-negative diagnostic results if the diseased tissue is under the surface of the GI tract. To improve their diagnostic accuracy for submucosal tumors/diseases, we propose a magnetically actuated soft robotic capsule robot, which takes biopsy samples in a deep tissue of a stomach using the fine-needle biopsy technique. We present the design, control, and human-machine interfacing methods for the fine-needle biopsy capsule robot. Ex vivo experiments in a porcine stomach show 85% yield for the biopsy of phantom tumors located underneath the first layers of the stomach wall.

A 5-D Localization Method for a Magnetically Manipulated Untethered Robot using a 2-D Array of Hall-effect Sensors.

This paper introduces a new five-dimensional localization method for an untethered meso-scale magnetic robot, which is manipulated by a computer-controlled electromagnetic system. The developed magnetic localization setup is a two-dimensional array of mono-axial Hall-effect sensors, which measure the perpendicular magnetic fields at their given positions. We introduce two steps for localizing a magnetic robot more accurately. First, the dipole modeled magnetic field of the electromagnet is subtracted from the measured data in order to determine the robot's magnetic field. Secondly, the subtracted magnetic field is twice differentiated in the perpendicular direction of the array, so that the effect of the electromagnetic field in the localization process is minimized. Five variables regarding the position and orientation of the robot are determined by minimizing the error between the measured magnetic field and the modeled magnetic field in an optimization method. The resulting position error is 2.1±0.8 mm and angular error is 6.7±4.3° within the applicable range (5 cm) of magnetic field sensors at 200 Hz. The proposed localization method would be used for the position feedback control of untethered magnetic devices or robots for medical applications in the future.

Phosphatidic acid and tumor necrosis factor-alpha induce the expression of CD83 through mitogen activated protein kinase pathway in a CD34+ hematopoietic progenitor cell line, KG1.

To elucidate the signaling pathways involved in the expression of CD83, which is linked to the differentiation and maturation states of dendritic cells, we examined the effect of phosphatidic acid (PA) on the expression of CD83 in KG1, a CD34(+) hematopoietic progenitor cell. In the presence of tumor necrosis factor (TNF)-alpha, PA but not lyso-PA up-regulated CD83 on KG1 cells. Moreover, PA and TNF-alpha-induced expression of CD83 was slightly increased by propranolol, an inhibitor of PA phosphohydrolase but was unaffected by phospholipase A2 inhibitor. PA and TNF-alpha increased the phosphorylation of extracellular signal-regulated kinase (ERK)-1/2, p38-kinase, and c-Jun N-terminal kinase (JNK) by Western blotting. However, the up-regulation of CD83 by PA/TNF-alpha on KG1 was significantly abrogated by PD98059, a specific inhibitor of ERK kinase, but was enhanced by SP600125, a JNK inhibitor. Bis-indolylmaleimide, an inhibitor of protein kinase C, partially blocked the up-regulation of CD83 and ERK phosphorylation induced by PA and TNF-alpha. Moreover, the incubation of KG1 cells with phorbol ester and TNF-alpha for 5 days increased the protein level of phospholipase D. These results suggest that PA and TNF-alpha induce the up-regulation of CD83 and that their action is regulated by ERK and JNK.