Applications In Soft Robotics Research Articles

High-Performing Conductive Hydrogels for Wearable Applications.

Conductive hydrogels have gained significant attention for their extensive applications in healthcare monitoring, wearable sensors, electronic devices, soft robotics, energy storage, and human-machine interfaces. To address the limitations of conductive hydrogels, researchers are focused on enhancing properties such as sensitivity, mechanical strength, electrical performance at low temperatures, stability, antibacterial properties, and conductivity. Composite materials, including nanoparticles, nanowires, polymers, and ionic liquids, are incorporated to improve the conductivity and mechanical strength. Biocompatibility and biosafety are emphasized for safe integration with biological tissues. Conductive hydrogels exhibit unique properties such as stretchability, self-healing, wet adhesion, anti-freezing, transparency, UV-shielding, and adjustable mechanical properties, making them suitable for specific applications. Researchers aim to develop multifunctional hydrogels with antibacterial characteristics, self-healing capabilities, transparency, UV-shielding, gas-sensing, and strain-sensitivity.

Ionic Liquid-Optoelectronics-Based Multimodal Soft Sensor

Multimodal soft sensors have attracted significant attention due to their ability to simultaneously measure multiple physical properties of objects, offering immense potential for the use of smart wearable devices and soft robots. However, achieving simultaneous detection of multiple physical quantities and integrating these functions in a limited sensor space remains a challenge. In this paper, a novel multimodal soft sensor is proposed for the simultaneous detection of mechanical stretching and bending deformations, which is based on room temperature ionic liquid (RTIL)-optoelectronics. The method employs RTIL as the light propagation medium and shares the same geometric unit with optoelectronics, effectively reducing the geometry of the sensor. It is capable of detecting three deformation modes, namely stretching, bending, and simultaneous stretching & bending. The compound deformation of stretching and bending is decoupled by detecting the difference between RTIL and optoelectronic signals, thus combining with the deep learning of long and short memory (LSTM) neural networks. Moreover, the proposed multimodal sensor exhibits high sensitivity, wide measurement range, and good stability, making it a promising option for future applications in soft robots and wearable devices.

Modeling Based on a Two-Step Parameter Identification Strategy for Liquid Crystal Elastomer Actuator Considering Dynamic Phase Transition Process.

Liquid crystal elastomer (LCE) is a promising candidate for actuation in light-driven soft robot applications. Due to the fact that LCE has complex hysteretic nonlinearities, which are highly dependent on the environment, modeling of actuators made of LCE is a very challenging issue. In this article, a model is proposed to describe the deformation of the LCE actuator accurately and analytically by considering the dynamic phase transition process of LCE molecules. First, an overview of the physical process of LCE's deformation is presented, and the schematic of the LCE actuator, as well as the modeling scheme are then introduced. Next, a thermodynamic analysis of the system's free energy is performed to establish the model for the LCE actuator, which gives the relationship between the system's deformation and the temperature. Here, to describe the complex hysteretic nonlinearity in the model, the dynamic process of the phase transition of LCE molecules is exploited. To effectively identify the model parameters, a two-step parameter identification strategy based on the differential evolution algorithm and nonlinear least-squares method is utilized. Finally, experimental results verify the validity of the proposed model. This modeling provides an approach to describe LCE's deformation with high accuracy and can fully reflect the physical nature of LCE's deformation, especially hysteresis. It can be utilized as a basis for accurate control over LCE actuators in photoresponsive soft robot applications.

Programmable spatial deformation by controllable off-center freestanding 4D printing of continuous fiber reinforced liquid crystal elastomer composites

Owing to their high deformation ability, 4D printed structures have various applications in origami structures, soft robotics and deployable mechanisms. As a material with programmable molecular chain orientation, liquid crystal elastomer is expected to produce the freestanding, bearable and deformable three-dimensional structure. However, majority of the existing 4D printing methods for liquid crystal elastomers can only fabricate planar structures, which limits their deformation designability and bearing capacity. Here we propose a direct ink writing based 4D printing method for freestanding continuous fiber reinforced composites. Continuous fibers can support freestanding structures during the printing process and improve the mechanical property and deformation ability of 4D printed structures. In this paper, the integration of 4D printed structures with fully impregnated composite interfaces, programmable deformation ability and high bearing capacity are realized by adjusting the off-center distribution of the fibers, and the printed liquid crystal composite can carry a load of up to 2805 times its own weight and achieve a bending deformation curvature of 0.33 mm−1 at 150 °C. This research is expected to open new avenues for creating soft robotics, mechanical metamaterials and artificial muscles.

Self-Sustained Oscillation of Electrothermally Responsive Liquid Crystal Elastomer Film in Steady-State Circuits.

Self-excited oscillations have the advantages of absorbing energy from a stable environment and Self-control; therefore, Self-excited motion patterns have broader applications in micro devices, autonomous robots, sensors and energy-generating devices. In this paper, a Self-sustained curling liquid crystal elastomer (LCE) film-mass system is proposed on the basis of electrothermally responsive materials, which can realize Self-oscillation under a steady-state current. Based on the contact model and dynamic LCE model, a nonlinear dynamics model of LCE film in steady-state circuits is developed and numerical calculations are carried out using the Runge-Kutta method. Through numerical calculations, it is demonstrated that LCE film-mass systems have two motion patterns in steady-state circuits: namely, a Self-oscillation pattern and a stationary pattern. Self-sustained curling of LCE film originates from the fact that the energy absorbed by the system exceeds the energy dissipated due to the damping effect. In addition, the critical conditions for triggering Self-oscillation and the effects of several key dimensionless system parameters on the amplitude and period of Self-oscillation are investigated in detail. Calculation results show that the height of electrolyte solution, gravitational acceleration, elastic modulus of LCE film, limit temperature, curvature coefficient, thermal shrinkage coefficient and damping factor all have a modulating effect on the amplitude and period of Self-oscillation. This research may deepen the understanding of Self-excited oscillation, with promising applications in energy harvesting, power generation, monitoring, soft robotics, medical devices, and micro and nano devices.

Emerging Functional Polymer Composites for Tactile Sensing.

In recent years, extensive research has been conducted on the development of high-performance flexible tactile sensors, pursuing the next generation of highly intelligent electronics with diverse potential applications in self-powered wearable sensors, human-machine interactions, electronic skin, and soft robotics. Among the most promising materials that have emerged in this context are functional polymer composites (FPCs), which exhibit exceptional mechanical and electrical properties, enabling them to be excellent candidates for tactile sensors. Herein, this review provides a comprehensive overview of recent advances in FPCs-based tactile sensors, including the fundamental principle, the necessary property parameter, the unique device structure, and the fabrication process of different types of tactile sensors. Examples of FPCs are elaborated with a focus on miniaturization, self-healing, self-cleaning, integration, biodegradation, and neural control. Furthermore, the applications of FPC-based tactile sensors in tactile perception, human-machine interaction, and healthcare are further described. Finally, the existing limitations and technical challenges for FPCs-based tactile sensors are briefly discussed, offering potential avenues for the development of electronic products.

Structure-induced Intelligence of Liquid Crystal Elastomers.

Liquid crystal elastomers (LCEs) are active soft matter-based materials with strong stimulus responsiveness and reversible, large-shape morphing capabilities. LCEs have demonstrated broad and growing applications in soft robotics, wearable devices, artificial muscles, and optical machines. The actuation intelligence and advanced functionality of LCEs depend on the smartness and properties of structures. In this review, we discuss recent advances in structure-induced intelligence of LCEs, specifically the integration of structural properties with the alignment and processing of LCEs. The structural design principles for three categories consisting of common structures (film, fiber, and tubule), smart structures (origami, kirigami, mechanical metamaterial, topology, and topography), and complex structures (monolithic and integrated) are presented. Various alignment controls of LCEs, including mechanical, surface, field-assisted, and shear alignment, are capable of inducing structural properties. The coupling and collaboration mechanisms of the LCE structures and the generated functions are discussed. The review concludes with perspectives on current challenges and emerging opportunities.

Soft Robotic Arm With Extensible Stiffening Layer

When talking about soft robots, softness is considered the most important feature, which brings dexterity and safety in interactive tasks with humans and environments. Such softness sometimes limits the real application of soft robots because load capability and rigidity are widely needed on many occasions. Often the inspiration for soft robots, soft animals such as octopus and sea cucumbers still preserve the ability to turn rigid when needed, and, more importantly, they can rapidly turn rigid at any deformed states. Intrigued by these capabilities, differently from existing stiffening technologies that do not adapt to soft robots' variety of morphological changes, we explored a new approach to create a flexible layer that can easily stiffen soft robots without affecting their original flexibility. We built an extensible chain of particles with a peculiar geometry, which can jam and stiffen. We enclosed it in a flexible membrane so that we can stiffen the structure by removing air. The overall structure is flexible enough and can withstand large elongation. So, it can be used around a soft robot arm for stiffening it in different deformed states. Experimental results show that such a stiffening layer does not affect the flexible motion of the soft robot, the stiffening function works even under the robot's 90% elongation state, and the stiffness can be increased by 15 times. By adopting the stiffening layer and different end effectors, we show that an assistive soft robot can simultaneously have the flexibility to collect food and the rigidity to hold it and help in feeding a participant. The results from this work may provide new design and application insights into the creation of soft robots with both flexible and rigid features.

A mechanics model of hard-magnetic soft rod with deformable cross-section under three-dimensional large deformation

Hard-magnetic soft (HMS) materials are soft active materials prepared by embedding the hard-magnetic particles (e.g. NdFeB) into soft elastomer, which can be actuated by applied magnetic fields. With the ability to retain remnant magnetism, HMS materials have many applications in soft robotics, haptic sensors and other fields. For HMS structures used in soft robotics, mechanics models have been developed for better exploiting the potential of the HMS materials. However, for rod-like structures made of soft materials, the nonlinear stress–strain relation and the areal change of the cross-section have not been considered in previous modeling work. In the present three-dimensional HMS rod model, started with the geometrically exact beam theory, the rigid cross-section assumption is replaced with a planar areal change assumption for soft rods, incompressible neo-Hookean material model is used to model the hyperelastic behavior of elastomers, which will be more accurate than linear relation under large deformation. Consistent with the deformable cross-section assumption, the magneto-elastic energy distribution is formulated and reduced to the line of centroid of the soft rod. To verify the accuracy and efficiency of the model, some simulation examples and experiments are performed. The error between the experimental results and the simulation results calculated by using 5 elements is within 10%. Our model can accurately and efficiently predict the 3D large deformation of the HMS rod, which can reduce the design and optimization cost and shorten the design cycle of HMS structure.

Sine-based lattice plates: additive manufacturing and their mechanical properties when loaded out of plane

PurposeDemanding applications could benefit from the mathematical parametrization of lattice structures as this could lead not only to the characterization of structure–property relation but also facilitates the tailoring of the effective mechanical properties. This paper aims to characterize the mechanical performance of sine-based lattices. The characterization includes the results of in-plane Poisson’s ratio plates models, and the stiffness of additively manufactured lattice plates when loaded in the out-of-plane direction, with the objective of obtaining a relation with their geometrical parameters.Design/methodology/approachThe geometrical parameter–Poisson’s ratio relationship was characterized via finite element (FE) simulations. The stiffness was also measured on additively manufactured polylactic acid lattice plates and contrasted with FE computations.FindingsThe characterization of auxetic lattice plates performed using in-plane and out-of-plane loading leads to key properties when deciding the geometry specific for applications: relative density, auxetic behavior and stiffness. Approximately 26% reduction of stiffness was observed between the square lattice and sine-based lattices of the same volume fraction.Originality/valueAuxetic metamaterials are potential candidates for applications in biomedical engineering, smart sensors, sports and soft robotics. This paper aims to contribute to the existing gap in the study of auxetic metamaterials subjected to complex loading conditions, other than simple tension and compression, required for the mentioned applications.

A DNA Based Dissipation System that Synchronizes Multiple Fuels.

Artificial dissipative networks have emerged as advanced bionic systems for the development of material technology and synthetic biology. Here, we demonstrate a DNA-based artificial dissipation system that synchronizes multiple energy-rich molecules (fuels) including oligonucleotide, dNTP, and ATP. The autonomous operation of the dissipation system relies on the integration of DNA reaction network including polymerase extension, kinase phosphorylation, and exonuclease digestion. The use of multiple fuels provides multiple transient states with different energy levels and fine-tuning dissipative kinetics. The lifetime of the transient state can be programmed to increase or decrease just by varying one of the fuel molecules unlike conventional DNA-based dissipative systems where the increase in the concentration of fuel molecule increases the lifetime. This design greatly expands the toolkits for establishing dissipative/dynamic DNA networks. The dissipation system is harnessed to dynamically regulate the assembly of DNA nanotubes allowing for controlling the assembly kinetics via multiple fuels. Owing to the multiple transient states in the dissipation system, two nanotubes can be regulated in parallel. We envision that the system would find broad applications in responsive materials, soft robotics, biosensors, and on-demand drug delivery.

An efficient technique in dynamic modeling and analysis of soft fluidic actuator

Soft actuators with embedded fluidic channels are promising for soft robotics, but their continuous nature presents challenges in accurate and efficient modeling. Existing studies on dynamic behavior have shown that both approximate and exact methods have limitations in accurately predicting the deflection of soft actuators. Additionally, conventional methods require experimental parameter extraction for each individual actuator. To address these challenges, we propose a modified analytical method and use finite element analysis as the defined correction functions to improve accuracy and computational efficiency, providing a promising tool for the design and control of soft robotic systems. In this work, we propose a solution methodology for simulating the dynamic behavior of fluidic soft actuators, which are widely used in soft robotics applications. Our approach takes into account the cross-sectional geometry and the number of channels in the actuator’s configuration. By scrutinizing various fluidic actuation designs, we can deduce the most suitable cross-sectional configuration for optimal performance. Compared to existing analytical methods, our approach is more accurate and does not require additional calculation time. As the method is adaptable with experimental models, it can be used to design and optimize soft actuators while can be refined and improved through experimental model updating.

Nonlinear Multimaterial Architecture for Greater Soft Material's Toughness and Delaying Damage Propagation.

Designing soft robots that have greater toughness and better resistance to damage propagation while at the same time retaining their properties of compliance is fundamentally important for soft robotics applications. This study's main contribution is proposing a framework for nonlinear multimaterial architectural design of soft structures to increase their toughness and delay damage propagation. What are the limits when combining significantly different materials in one structure that will delay crack propagation while significantly maintaining postdamage toughness? Through this study, we observed that there is a very dynamic interplay when combining significantly different materials in one structure; this interplay could weaken or strengthen the multimaterial structure's toughness. In biological evolutionary terms, the Pangolin, Seashell, and Arapaima have found their answer for deflecting the crack and maintaining strength in their bodies. How does nature put these multimaterial structures together? Our research led us to find that the multimaterial toughness limits depend largely on the following parameters: components' relative morphology, architecture, spatial distribution, surface areas, and Young's Modulus. We found that a linear geometry, when it comes to morphology and/or architecture relative to surface area in multimaterial design, significantly reduces total toughness and fails to delay crack propagation. In contrast, incorporating geometric nonlinearities in both morphology and architecture significantly maintains higher total toughness even after damage, and significantly delays crack propagation. We believe that this study can open the door to further research and ultimately to promising and wide applications in soft robotics.

Shape Memory Soft Robotics with Yield Stress Fluids

Biological movement is a source of inspiration for designing soft robots that use fluidic actuation for adaptive gripping and locomotion. While many biological systems use networks of non‐Newtonian fluid for movement, to date, most soft robots use Newtonian fluids or pneumatics. Herein, yield stress fluids to manufacture and operate soft devices are exploited, particularly to create soft actuators that exhibit shape memory. Our soft robots are fabricated through embedded 3D printing where the suspension media is a yield stress fluid. Moreover, this complex fluid is encapsulated and used as the hydraulic transmission fluid. Diagnostic designs are developed to characterize the force and shape memory of the yield stress fluid, and the findings are used to create a gripper common in modern soft robotic applications. The diagnostic devices have deformable reservoirs that demonstrate force response, flow behavior, and deformation profiles dependent on the yield stress features of the transmission fluid. The actuation using the yield stress fluid from the retained suspension media creates avenues for partial shape retention and unconventional expansion from localized fluid flow. Looking toward the future of soft robotics, these fabrication and operational approaches using yield stress fluids can provide greater tunability for applications requiring nonlinear actuation and shape memory.

Optimal humidity-responsive actuators of heterostructured MXene nanosheets/3D-MXene membrane

Intelligent actuators offer a lot of potential for use in soft robots, artificial muscles, sensors since it can alter shape in response to external stimuli. However, the stiffness of the material and the constrained specific surface area brought on by the dense stacking of materials restrict the response of the conventional humidity-responsive actuators. Herein, optimal humidity-responsive actuators of MXene were developed by designing topologies of heterostructured membrane of stacked nanosheets and 3D wrinkled MXene (3D-MXene). In this configuration, the stacked MXene nanosheets sustain the device’s overall strength, while the 3D-MXene layer significantly improves the device’s moisture absorption and decreases its stiffness. Importantly, the actuators have been strengthened due to the van der Waals forces at the interface of the stacked nanosheets and 3D-MXene. The fabricated MXene/3D-MXene actuator has exhibited remarkable response speed and deformation ability, obviously superior to any previously reported humidity-responsive actuators. By combining excellent electrical conductivity, the developed actuators demonstrated rapid response for electrical switches. This work highlights the significant potential for developing high performance responsive actuators by designing heterostructured configurations for applications in intelligent switches, soft robotics and synthetic muscles.

Design improvement of the conversion mechanism from balloon inflation to bending motion for inflatable film actuators

Various soft actuators have been investigated to overcome the drawbacks of conventional solid machines and explore the applications of soft robotics. In particular, and because they are expected to be applicable in minimally invasive medicine because of their safety, soft inflatable microactuators using an actuation conversion mechanism from balloon inflation to bending motion have been proposed for high-output bending motion. These microactuators could be applied to create an operation space by safely moving organs and tissues; however, the conversion efficiency could be further improved. This study aimed to improve conversion efficiency by investigating the design of the conversion mechanism. The contact conditions between the inflated balloon and conversion film were examined to improve the contact area for force transmission, with the contact area dependent on the length of the contact arc between the balloon and force conversion mechanism and on the amount of balloon deformation. In addition, surface contact friction between the balloon and film, which affects actuator performance, was also investigated. The generated force of the improved device is 1.21 N at 80 kPa when it bends 10 mm, which is 2.2 times the generated force of the previous design. This improved soft inflatable microactuator is expected to assist in performing operations in a limited space, such as in endoscopic or laparoscopic operations.

Stimuli‐Responsive Peptide Self‐Assembly to Construct Hydrogels with Actuation and Shape Memory Behaviors

AbstractHydrogel actuators, capable of generating reversible deformation in response to external stimulus, are widely considered as new emerging intelligent materials for applications in soft robots, smart sensors, artificial muscles, and so on. Peptide self‐assembly is widely applied in the construction of intelligent hydrogel materials due to their excellent stimulus response. However, hydrogel actuators based on peptide self‐assembly are rarely reported and explored. In this study, a pH‐responsive peptide (MA‐FIID) is designed and introduced into a poly(N‐isopropyl acrylamide) backbone (PNIPAM) to construct bilayer and heterogeneous hydrogel actuators based on the assembly and disassembly of peptide molecules under different pH conditions. These peptide‐containing hydrogel actuators can perform controllable bending, bucking, and complex deformation under pH stimulation. Meanwhile, the Hofmeister effect of PNIPAM hydrogels endows these peptide‐containing hydrogels with enhanced mechanical strength, ionic stimulus response (CaCl2), and excellent shape‐memory property. This work broadens the application of supramolecular self‐assembly in the construction of intelligent hydrogels, and also provides new inspirations for peptide self‐assembly to construct smart materials.

3D Electronic Sensors for Bio‐Interfaced Electronics and Soft Robotics

AbstractMulti‐dimensional electronic devices for sensing applications have received immense attention in the fields of bio‐interface electronics and soft robotics to achieve structural manifolds in recent years. The structural diversities of sensors are tuned based on the environments in which they encounter multipurpose and complex form factors of electronics. 3D electronics are one of the emerging sensor platforms characterized by structural adaptability and compatibility on free target surfaces, resulting in unprecedented improvement of spatial resolution. Herein, the recent progress made in the fabrication and usage of 3D electronic sensors that are classified into two groups based on the methodological concepts used for fabrication in bio‐interfaced electronics and soft robotics applications, is reviewed. The latest advances in the design and development of 3D printable and 2D to 3D shape‐deformable electronic sensors are reviewed with a focus on printable materials and deformation mechanisms, respectively. 3D printing techniques enable the facile fabrication of arbitrary and seamless electronics without the use of conventional microfabrication technologies. Deformable electronics cover their self‐tune architectures and functions depending on mechanical deformation based on buckling, origami, and kirigami fabrication strategies. Finally, the printed and deformable 3D sensors show their potential for use in next‐generation sensing platforms.

Super-Stretchable Resistive Strain Sensor Based on Ecoflex–Gold Nanocomposites

Superstretchable resistive strain sensors can reversibly undergo severe deformations in response to different mechanical stimuli, leading to a variation in their ohmic resistance. They are finding an increasing number of applications in wearable electronics, biomedical devices, and soft robotics. The development of fabrication process of reliable, highly sensitive, and biocompatible superstretchable strain sensors remains a challenge, especially in view of their integration with medical devices. Here, we demonstrate the fabrication of a high-strain resistive sensor based on Ecoflex elastomeric films and conductive Au clusters, obtained by supersonic cluster beam deposition. An extensive characterization of the electromechanical behavior of the sensor shows stable operation up to 4500 working cycles, with a maximum strain of 500% and a gauge factor of 124. Different mechanical stimuli, such as elongation and indentation, can be detected, and the easy coupling of the sensor with an inflatable balloon-type urinary catheter is demonstrated. Aiming at shedding light on the observed electromechanical mechanisms, the nanostructured morphology of the metal–polymer hybrid layer was investigated by low-vacuum scanning electron microscopy.

High performance electro-active artificial muscles based on 3D dendritic nickel cobalt sulfide nanorods-graphene electrodes

As the desire for biomimicry that utilizes the advantages of natural organisms, increases, electroactive artificial muscles, an emerging technology, have been phasing-in to bioinspired applications in medicine, electronics, and soft robotics. However, it remains challenging to simultaneously obtain stable response characteristics and high bending displacement, considering the instability of electrode materials in open air environments. Here, 3D dendritic nickel cobalt sulfide nanorods grown on graphene electrodes, exhibiting stable electrochemical reactivity owing to their structural and material advantages, are employed to realize high-performance artificial muscles. Importantly, the significant influence of the phase transition of nickel-cobalt metals and graphene template in the synthesis steps on tuning the electrical and electrochemical properties is reported. The resulting artificial muscles show an almost 98 % enhanced bending performance and stable response to both AC and DC input signals without significant phase delay or distortion. These substantial improvements in the performance of artificial muscles enable the demonstration of bioinspired soft locomotive robots; these artificial muscles will thus expand the soft electronics industry in the field of next-generation human-machine interfaces.