Materials with Electroprogrammable Stiffness

Materials and Structural Designs toward Motion Artifact-Free Bioelectronics

Bioelectronics encompassing electronic components and circuits for accessing human information play a vital role in real-time and continuous monitoring of biophysiological signals of electrophysiology, mechanical physiology, and electrochemical physiology. However, mechanical noise, particularly motion artifacts, poses a significant challenge in accurately detecting and analyzing target signals. While software-based "postprocessing" methods and signal filtering techniques have been widely employed, challenges such as signal distortion, major requirement of accurate models for classification, power consumption, and data delay inevitably persist. This review presents an overview of noise reduction strategies in bioelectronics, focusing on reducing motion artifacts and improving the signal-to-noise ratio through hardware-based approaches such as "preprocessing". One of the main stress-avoiding strategies is reducing elastic mechanical energies applied to bioelectronics to prevent stress-induced motion artifacts. Various approaches including strain-compliance, strain-resistance, and stress-damping techniques using unique materials and structures have been explored. Future research should optimize materials and structure designs, establish stable processes and measurement methods, and develop techniques for selectively separating and processing overlapping noises. Ultimately, these advancements will contribute to the development of more reliable and effective bioelectronics for healthcare monitoring and diagnostics.

Learning Stiffness Tensors in Self-Activated Solids via a Local Rule

Mechanical metamaterials are often designed with particular properties for specific load-bearing functions. Alternatively, this study aims to create a class of active lattice metamaterials, dubbed self-activated solids, that can learn desired stiffness tensors from the elastic deformations they experienced, a crucial feature to improve the performance, efficiency, and functionality of materials. Artificial adaptive matters that combine sensory, control, and actuation elements can offer appealing solutions. However, challenges still remain: The designs will rely on accurate off-line and global computations, as well as intricate coordination among individual elements. Here, a simple online and local learning strategy is initiated based on contrastive Hebbian learning to gradually guide self-activated solids to possess sought-after stiffness tensors autonomously and reversibly. During learning, the bond stiffness of the active lattice varies depending only on its local strain. The numerical tests show that the self-activated solid can not only achieve the desired bulk, shear, and coupling moduli but also manifest uni-mode and bi-mode extremal materials by itself after experiencing the corresponding elastic deformations. Further, the self-activated solid can also achieve the desired time-varying moduli when exposed to temporally different loads. The design is applicable to any lattice geometries and is resistant to damage and instabilities. The material design approach and the physical learning strategy suggested can benefit the design of autonomous materials, physical learning machines, and adaptive robots.

Tunable Hydrogel Electronics for Diagnosis of Peripheral Neuropathy

Peripheral neuropathy characterized by rapidly increasing numbers of patients is commonly diagnosed via analyzing electromyography signals obtained from stimulation-recording devices. However, existing commercial electrodes have difficulty in implementing conformal contact with skin and gentle detachment, dramatically impairing stimulation/recording performances. Here, this work develops on-skin patches with polyaspartic acid-modified dopamine/ethyl-based ionic liquid hydrogel (PDEH) as stimulation/recording devices to capture electromyography signals for the diagnosis of peripheral neuropathy. Triggered by a one-step electric field treatment, the hydrogel achieves rapid and wide-range regulation of adhesion and substantially strengthened mechanical performances. Moreover, hydrogel patches assembled with a silver-liquid metal (SLM) layer exhibit superior charge injection and low contact impedance, capable of capturing high-fidelity electromyography. This work further verifies the feasibility of hydrogel devices for accurate diagnoses of peripheral neuropathy in sensory, motor, and mixed nerves. For various body parts, such as fingers, the elderly's loose skin, hairy skin, and children's fragile skin, this work regulates the adhesion of PDEH-SLM devices to establish intimate device/skin interfaces or ensure benign removal. Noticeably, hydrogel patches achieve precise diagnoses of nerve injuries in these clinical cases while providing extra advantages of more effective stimulation/recording performances. These patches offer a promising alternative for the diagnosis and rehabilitation of neuropathy in future.

Robust Grasping of a Variable Stiffness Soft Gripper in High-Speed Motion Based on Reinforcement Learning

Industrial robots are widely deployed to perform pick-and-place tasks at high speeds to minimize manufacturing time and boost productivity. When dealing with delicate or fragile goods, soft robotic grippers are better end effectors than rigid grippers due to their softness and safe interaction. However, high-speed motion causes the soft robotic gripper to vibrate, leading to damage of the objects or failed grasping. Soft grippers with variable stiffness are considered to be effective in suppressing vibrations by adding damping devices, but it is quite challenging to compromise between stiffness and compliance. In this article, a controller based on deep reinforcement learning is proposed to control the stiffness of the soft robotic gripper, which can accurately suppress the vibration with only a minor influence on its compliance and softness. The proposed controller is a real-time vibration control strategy, which estimates the output of the controller based on the current operating environment. To demonstrate the effectiveness of the proposed controller, experiments were done with a UR5 robotic arm. For different situations, experimental results show that the proposed controller responds quickly and reduces the amplitude of the oscillation substantially.

Variable stiffness soft robotic gripper: design, development, and prospects

The advent of variable stiffness soft robotic grippers furnishes a conduit for exploration and manipulation within uncharted, non-structured environments. The paper provides a comprehensive review of the necessary technologies for the configuration design of soft robotic grippers with variable stiffness, serving as a reference for innovative gripper design. The design of variable stiffness soft robotic grippers typically encompasses the design of soft robotic grippers and variable stiffness modules. To adapt to unfamiliar environments and grasp unknown objects, a categorization and discussion have been undertaken based on the contact and motion manifestations between the gripper and the things across various dimensions: points contact, lines contact, surfaces contact, and full-bodies contact, elucidating the advantages and characteristics of each gripping type. Furthermore, when designing soft robotic grippers, we must consider the effectiveness of object grasping methods but also the applicability of the actuation in the target environment. The actuation is the propelling force behind the gripping motion, holding utmost significance in shaping the structure of the gripper. Given the challenge of matching the actuation of robotic grippers with the target scenario, we reviewed the actuation of soft robotic grippers. We analyzed the strengths and limitations of various soft actuation, providing insights into the actuation design for soft robotic grippers. As a crucial technique for variable stiffness soft robotic grippers, variable stiffness technology can effectively address issues such as poor load-bearing capacity and instability caused by the softness of materials. Through a retrospective analysis of variable stiffness theory, we comprehensively introduce the development of variable stiffness theory in soft robotic grippers and showcase the application of variable stiffness grasping technology through specific case studies. Finally, we discuss the future prospects of variable stiffness grasping robots from several perspectives of applications and technologies.

A Low-Voltage, High-Force Capacity Electroadhesive Clutch Based on Ionoelastomer Heterojunctions

Electroadhesive devices with dielectric films can electrically program changes in stiffness and adhesion, but require hundreds of volts and are subject to failure by dielectric breakdown. Recent work on ionoelastomer heterojunctions has enabled reversible electroadhesion with low voltages, but these materials exhibit limited force capacities and high detachment forces. It is a grand challenge to engineer electroadhesives with large force capacities and programmable detachment at low voltages (<10 V). In this work, tough ionoelastomer/metal mesh composites with low surface energies are synthesized and surface roughness is controlled to realize sub-ten-volt clutches that are small, strong, and easily detachable. Models based on fracture and contact mechanics explain how clutch compliance and surface texture affect force capacity and contact area, which is validated over different geometries and voltages. These ionoelastomer clutches outperform the best existing electroadhesive clutches by fivefold in force capacity per unit area (102 N cm-2 ), with a 40-fold reduction in operating voltage (± 7.5 V). Finally, the ability of the ionoelastomer clutches to resist bending moments in a finger wearable and as a reversible adhesive in an adjustable phone mount is demonstrated.

A multifunctional soft robotic shape display with high-speed actuation, sensing, and control

Shape displays which actively manipulate surface geometry are an expanding robotics domain with applications to haptics, manufacturing, aerodynamics, and more. However, existing displays often lack high-fidelity shape morphing, high-speed deformation, and embedded state sensing, limiting their potential uses. Here, we demonstrate a multifunctional soft shape display driven by a 10 × 10 array of scalable cellular units which combine high-speed electrohydraulic soft actuation, magnetic-based sensing, and control circuitry. We report high-performance reversible shape morphing up to 50 Hz, sensing of surface deformations with 0.1 mm sensitivity and external forces with 50 mN sensitivity in each cell, which we demonstrate across a multitude of applications including user interaction, image display, sensing of object mass, and dynamic manipulation of solids and liquids. This work showcases the rich multifunctionality and high-performance capabilities that arise from tightly-integrating large numbers of electrohydraulic actuators, soft sensors, and controllers at a previously undemonstrated scale in soft robotics.

Stiffness Variable Polymer for Soft Actuators with Sharp Stiffness Switch and Fast Response

Stiffness variable polymers are an essential family of materials that have aroused considerable attention in soft actuators. Although lots of strategies have been proposed to achieve variable stiffness, it remains a formidable challenge to achieve a polymer with a wide stiffness range and fast stiffness change. Herein, a series of variable stiffness polymers with a fast stiffness change and wide stiffness range were successfully synthesized, and the formulas were optimized via Pearson correlation tests. The rigid/soft stiffness ratio of the designed polymer samples can reach up to 1376-folds. Impressively, owing to the phase-changing side chains, the narrow endothermic peak can be observed with full width at half-maximum within 5 °C. Moreover, the shape memory properties of the shape fixity (R_f) and shape recovery ratio (R_r) values of the shape memory properties could reach up to 99.3 and 99.2%, respectively. Then, the obtained polymer was introduced into a kind of designed 3D printing soft actuator. The soft actuator can achieve sharp heating-cooling cycle of 19 s under a 1.2 A current with 4 °C water as coolant and can lift a 200 g weight at the actuating state. Moreover, the stiffness of the soft actuator can reach up to 718 mN/mm. The soft actuator exhibits an outstanding actuate behavior and stiffness switchable capability. We expect our design strategy and obtained variable stiffness polymers to be potentially applied in soft actuators and other devices.

Stiff skin, soft core: soft backings enhance the conformability and friction of fibre-reinforced adhesives

Biomimetic adhesives with a stiff fibre-reinforced base layer generate strong attachment, even without bioinspired micropatterning of the contact surface. However, current fibre-reinforced adhesive designs are still less versatile with respect to substrate variability than their biological counterparts. In this study, we enhance the comformability of a fibre-reinforced adhesive on curved substrates by adding bioinspired soft backings. We designed and fabricated soft backing variations (polyurethane foams and silicone hydroskeletons) with varying compressive stiffnesses that mimic the soft viscoelastic structures in the adhesive appendages of tree frogs, geckos and other animals. The backings were mounted on a smooth silicone layer enforced with a polyester mesh, and we experimentally investigated the contact area and friction performance of these adhesives on a curved substrate. The results show that the contact area and friction created by a fibre-reinforced adhesive with a soft backing in contact with a non-flat substrate scale inversely with backing stiffness. The integration of stiff fibre-reinforcement with a compressible backing represents an important step in bringing bioinspired adhesives out of the laboratory and into the real world, for example in soft robotic grippers. Moreover, our findings stimulate further research into the role of soft tissues in biological adhesive systems.

A mechanics-based approach to realize high–force capacity electroadhesives for robots

Materials with electroprogrammable stiffness and adhesion can enhance the performance of robotic systems, but achieving large changes in stiffness and adhesive forces in real time is an ongoing challenge. Electroadhesive clutches can rapidly adhere high stiffness elements, although their low force capacities and high activation voltages have limited their applications. A major challenge in realizing stronger electroadhesive clutches is that current parallel plate models poorly predict clutch force capacity and cannot be used to design better devices. Here, we use a fracture mechanics framework to understand the relationship between clutch design and force capacity. We demonstrate and verify a mechanics-based model that predicts clutch performance across multiple geometries and applied voltages. On the basis of this approach, we build a clutch with 63 times the force capacity per unit electrostatic force of state-of-the-art electroadhesive clutches. Last, we demonstrate the ability of our electroadhesives to increase the load capacity of a soft, pneumatic finger by a factor of 27 times compared with a finger without an electroadhesive.

Dynamic and static biomechanical traits of cardiac fibrosis

Cardiac fibrosis is a common pathology in cardiovascular diseases which are reported as the leading cause of death globally. In recent decades, accumulating evidence has shown that the biomechanical traits of fibrosis play important roles in cardiac fibrosis initiation, progression and treatment. In this review, we summarize the four main distinct biomechanical traits (i.e., stretch, fluid shear stress, ECM microarchitecture, and ECM stiffness) and categorize them into two different types (i.e., static and dynamic), mainly consulting the unique characteristic of the heart. Moreover, we also provide a comprehensive overview of the effect of different biomechanical traits on cardiac fibrosis, their transduction mechanisms, and in-vitro engineered models targeting biomechanical traits that will aid the identification and prediction of mechano-based therapeutic targets to ameliorate cardiac fibrosis.

Self-Reporting Joule Heating Modulated Stiffness of Polymeric Nanocomposites for Shape Reconfiguration

Shape reconfigurable devices, e.g., foldable phones, have emerged with the development of flexible electronics. But their rigid frames limit the feasible shapes for the devices. To achieve freely changeable shapes yet keep the rigidity of devices for user-friendly operations, stiffness-tunable materials are desired, especially under electrical control. However, current such systems are multilayer with at least a heater layer and a structural layer, leading to complex fabrication, high cost, and loss of reprocessability. Herein, we fabricate covalent adaptable networks-carbon nanotubes (CAN-CNT) composites to realize Joule heating controlled stiffness. The nanocomposites function as stiffness-tunable matrices, electric heaters, and softening sensors all by themselves. The self-reporting of softening is used to regulate the power control, and the sensing mechanism is investigated by simulating the CNT-polymer chain interactions at the nanoscale during the softening process. The nanocomposites not only have adjustable mechanical and thermodynamic properties but also are easy to fabricate at low cost and exhibit reprocessability and recyclability benefiting from the dynamic exchange reactions of CANs. Shape and stiffness control of flexible display systems are demonstrated with the nanocomposites as framing material, where freely reconfigurable shapes are realized to achieve convenient operation, wearing, or storage, fully exploiting their flexible potential.

Programmable gear-based mechanical metamaterials

Elastic properties of classical bulk materials can hardly be changed or adjusted in operando, while such tunable elasticity is highly desired for robots and smart machinery. Although possible in reconfigurable metamaterials, continuous tunability in existing designs is plagued by issues such as structural instability, weak robustness, plastic failure and slow response. Here we report a metamaterial design paradigm using gears with encoded stiffness gradients as the constituent elements and organizing gear clusters for versatile functionalities. The design enables continuously tunable elastic properties while preserving stability and robust manoeuvrability, even under a heavy load. Such gear-based metamaterials enable excellent properties such as continuous modulation of Young's modulus by two orders of magnitude, shape morphing between ultrasoft and solid states, and fast response. This allows for metamaterial customization and brings fully programmable materials and adaptive robots within reach.

Biohybrid Variable-Stiffness Soft Actuators that Self-Create Bone

Inspired by the dynamic process of initial bone development, in which a soft tissue turns into a solid load-bearing structure, the fabrication, optimization, and characterization of bioinduced variable-stiffness actuators that can morph in various shapes and change their properties from soft to rigid are hereby presented. Bilayer devices are prepared by combining the electromechanically active properties of polypyrrole with the compliant behavior of alginate gels that are uniquely functionalized with cell-derived plasma membrane nanofragments (PMNFs), previously shown to mineralize within 2 days, which promotes the mineralization in the gel layer to achieve the soft to stiff change by growing their own bone. The mineralized actuator shows an evident frozen state compared to the movement before mineralization. Next, patterned devices show programmed directional and fixated morphing. These variable-stiffness devices can wrap around and, after the PMNF-induced mineralization in and on the gel layer, adhere and integrate onto bone tissue. The developed biohybrid variable-stiffness actuators can be used in soft (micro-)robotics and as potential tools for bone repair or bone tissue engineering.

Recent Progress in Active Mechanical Metamaterials and Construction Principles

Active mechanical metamaterials (AMMs) (or smart mechanical metamaterials) that combine the configurations of mechanical metamaterials and the active control of stimuli-responsive materials have been widely investigated in recent decades. The elaborate artificial microstructures of mechanical metamaterials and the stimulus response characteristics of smart materials both contribute to AMMs, making them achieve excellent properties beyond the conventional metamaterials. The micro and macro structures of the AMMs are designed based on structural construction principles such as, phase transition, strain mismatch, and mechanical instability. Considering the controllability and efficiency of the stimuli-responsive materials, physical fields such as, the temperature, chemicals, light, electric current, magnetic field, and pressure have been adopted as the external stimuli in practice. In this paper, the frontier works and the latest progress in AMMs from the aspects of the mechanics and materials are reviewed. The functions and engineering applications of the AMMs are also discussed. Finally, existing issues and future perspectives in this field are briefly described. This review is expected to provide the basis and inspiration for the follow-up research on AMMs.