Unlocking the potential of self-healing and recyclable ionic elastomers for soft robotics applications

In the field of soft robotics, current materials face challenges related to their load capacity, durability, and sustainability. Innovative solutions are required to address these problems beyond conventional strategies, which often lack long-term ecological viability. This study aims to overcome these limitations using mechanically robust, self-healing, and recyclable ionic elastomers based on carboxylated nitrile rubber (XNBR). The designed materials exhibited excellent mechanical properties, including tensile strengths (TS) exceeding 19 MPa and remarkable deformability, with maximum elongations (EB) over 650%. Moreover, these materials showed high self-healing capabilities, with 100% recovery efficiency of TS and EB at 110 °C after 3 to 5 h, and full recyclability, preserving their mechanical performance even after three recycling cycles. Furthermore, they were also moldable and readily scalable. Tendon-driven soft robotic grippers were successfully developed out of ionic elastomers, illustrating the potential of self-healing and recyclability in the field of soft robotics to reduce maintenance costs, increase material durability, and improve sustainability.

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.

Fast Self-Healing at Room Temperature in Diels-Alder Elastomers

Despite being primarily categorized as non-autonomous self-healing polymers, we demonstrate the ability of Diels-Alder polymers to heal macroscopic damages at room temperature, resulting in complete restoration of their mechanical properties within a few hours. Moreover, we observe immediate partial recovery, occurring mere minutes after reuniting the fractured surfaces. This fast room-temperature healing is accomplished by employing an off-stoichiometric maleimide-to-furan ratio in the polymer network. Through an extensive investigation of seven Diels-Alder polymers, the influence of crosslink density on self-healing, thermal, and (thermo-)mechanical performance was thoroughly examined. Crosslink density variations were achieved by adjusting the molecular weight of the monomers or utilizing the off-stoichiometric maleimide-to-furan ratio. Quasistatic tensile testing, dynamic mechanical analysis, dynamic rheometry, differential scanning calorimetry, and thermogravimetric analysis were employed to evaluate the individual effects of these parameters on material performance. While lowering the crosslink density in the polymer network via decreasing the off-stoichiometric ratio demonstrated the greatest acceleration of healing, it also led to a slight decrease in (dynamic) mechanical performance. On the other hand, reducing crosslink density using longer monomers resulted in faster healing, albeit to a lesser extent, while maintaining the (dynamic) mechanical performance.

Vitrimeric shape memory polymer-based fingertips for adaptive grasping

The variability in the shapes and sizes of objects presents a significant challenge for two-finger robotic grippers when it comes to manipulating them. Based on the chemistry of vitrimers (a new class of polymer materials that have dynamic covalent bonds, which allow them to reversibly change their mechanical properties under specific conditions), we present two designs as 3D-printed shape memory polymer-based shape-adaptive fingertips (SMP-SAF). The fingertips have two main properties needed for an effective grasping. First, the ability to adapt their shape to different objects. Second, exhibiting variable rigidity, to lock and retain this new shape without the need for any continuous external triggering system. Our two design strategies are: 1) A curved part, which is suitable for grasping delicate and fragile objects. In this mode and prior to gripping, the SMP-SAFs are straightened by the force of the parallel gripper and are adapted to the object by shape memory activation. 2) A straight part that takes on the form of the objects by contact force with them. This mode is better suited for gripping hard bodies and provides a more straightforward shape programming process. The SMP-SAFs can be programmed by heating them up above glass transition temperature (54°C) via Joule-effect of the integrated electrically conductive wire or by using a heat gun, followed by reshaping by the external forces (without human intervention), and subsequently fixing the new shape upon cooling. As the shape programming process is time-consuming, this technique suits adaptive sorting lines where the variety of objects is not changed from grasp to grasp, but from batch to batch.

Assisted damage closure and healing in soft robots by shape memory alloy wires

Self-healing soft robots show enormous potential to recover functional performance after healing the damages. However, healing in these systems is limited by the recontact of the fracture surfaces. This paper presents for the first time a shape memory alloy (SMA) wire-reinforced soft bending actuator made out of a castor oil-based self-healing polymer, with the incorporated ability to recover from large incisions via shape memory assisted healing. The integrated SMA wires serve three major purposes; (i) Large incisions are closed by contraction of the current-activated SMA wires that are integrated into the chamber. These pull the fracture surfaces into contact, enabling the healing. (ii) The heat generated during the activation of the SMA wires is synergistically exploited for accelerating the healing. (iii) Lastly, during pneumatic actuation, the wires constrain radial expansion and one-side longitudinal extension of the soft chamber, effectuating the desired actuator bending motion. This novel approach of healing is studied via mechanical and ultrasound tests on the specimen level, as well as via bending characterization of the pneumatic robot in multiple damage healing cycles. This technology allows soft robots to become more independent in terms of their self-healing capabilities from human intervention.

An Interdisciplinary Tutorial: A Self-Healing Soft Finger with Embedded Sensor

In the field of soft robotics, knowledge of material science is becoming more and more important. However, many researchers have a background in only one of both domains. To aid the understanding of the other domain, this tutorial describes the complete process from polymer synthesis over fabrication to testing of a soft finger. Enough background is provided during the tutorial such that researchers from both fields can understand and sharpen their knowledge. Self-healing polymers are used in this tutorial, showing that these polymers that were once a specialty, have become accessible for broader use. The use of self-healing polymers allows soft robots to recover from fatal damage, as shown in this tutorial, which increases their lifespan significantly.

Data-driven method for damage localization on soft robotic grippers based on motion dynamics

Damage detection is one of the critical challenges in operating soft robots in an industrial setting. In repetitive tasks, even a small cut or fatigue can propagate to large damage ceasing the complete operation process. Although research has shown that damage detection can be performed through an embedded sensor network, this approach leads to complicated sensorized systems with additional wiring and equipment, made using complex fabrication processes and often compromising the flexibility of the soft robotic body. Alternatively, in this paper, we proposed a non-invasive approach for damage detection and localization on soft grippers. The essential idea is to track changes in non-linear dynamics of a gripper due to possible damage, where minor changes in material and morphology lead to large differences in the force and torque feedback over time. To test this concept, we developed a classification model based on a bidirectional long short-time memory (biLSTM) network that discovers patterns of dynamics changes in force and torque signals measured at the mounting point. To evaluate this model, we employed a two-fingered Fin Ray gripper and collected data for 43 damage configurations. The experimental results show nearly perfect damage detection accuracy and 97% of its localization. We have also tested the effect of the gripper orientation and the length of time-series data. By shaking the gripper with an optimal roll angle, the localization accuracy can exceed 95% and increase further with additional gripper orientations. The results also show that two periods of the gripper oscillation, i.e., roughly 50 data points, are enough to achieve a reasonable level of damage localization.

Processing of Self-Healing Polymers for Soft Robotics

Soft robots are, due to their softness, inherently safe and adapt well to unstructured environments. However, they are prone to various damage types. Self-healing polymers address this vulnerability. Self-healing soft robots can recover completely from macroscopic damage, extending their lifetime. For developing healable soft robots, various formative and additive manufacturing methods have been exploited to shape self-healing polymers into complex structures. Additionally, several novel manufacturing techniques, noted as (re)assembly binding techniques that are specific to self-healing polymers, have been created. Herein, the wide variety of processing techniques of self-healing polymers for robotics available in the literature is reviewed, and limitations and opportunities discussed thoroughly. Based on defined requirements for soft robots, these techniques are critically compared and validated. A strong focus is drawn to the reversible covalent and (physico)chemical cross-links present in the self-healing polymers that do not only endow healability to the resulting soft robotic components, but are also beneficial in many manufacturing techniques. They solve current obstacles in soft robots, including the formation of robust multi-material parts, recyclability, and stress relaxation. This review bridges two promising research fields, and guides the reader toward selecting a suitable processing method based on a self-healing polymer and the intended soft robotics application.

Additive Manufacturing for Self-Healing Soft Robots

The field of self-healing soft robots was initiated a few years ago. A healing ability can be integrated in soft robots by manufacturing their soft membranes out of synthetic self-healing polymers, more specifically elastomeric Diels-Alder (DA) networks. As such they can recover completely from macroscopic damage, including scratches, cuts, and ruptures. Before this research, these robots were manufactured using a technique named "shaping-through-folding-and-self-healing." This technique requires extensive manual labor, is relatively slow, and does not allow for complex shapes. In this article, an additive manufacturing methodology, fused filament fabrication, is developed for the thermoreversible DA polymers, and the approach is validated on a soft robotic gripper. The reversibility of their network permits manufacturing these flexible self-healing polymers through reactive printing into the complex shapes required in soft robotics. The degree of freedom in the design of soft robotics that this new manufacturing technique offers is illustrated through the construction of adaptive DHAS gripper fingers, based on the design by FESTO. Being constructed out of self-healing soft flexible polymer, the fingers can recover entirely from large cuts, tears, and punctures. This is highlighted through various damage-heal cycles.

Development of a self-healing soft pneumatic actuator: a first concept

Inspired by the intrinsic softness and the corresponding embodied intelligence principles, soft pneumatic actuators (SPA) have been developed, which ensure safe interaction in unstructured, unknown environments. Due to their intrinsic softness, these actuators have the ability to resist large mechanical impacts. However, the soft materials used in these structures are in general susceptible to damage caused by sharp objects found in the unstructured environments. This paper proposes to integrate a self-healing (SH-) mechanism in SPAs, such that cuts, tears and perforations in the actuator can be self-healed. Diels-Alder (DA-) polymers, covalent polymer network systems based on the thermoreversible DA-reaction, were selected and their mechanical, as well as SH-properties, are described. To evaluate the feasibility of developing an SPA constructed out of SH-material, a single cell prototype, a SH-soft pneumatic cell (SH-SPC), was constructed entirely out of DA-polymers. Exploiting the SH-property of the DA-polymers, a completely new shaping process is presented in this paper, referred to as 'shaping through folding and self-healing'. 3D polygon structures, like the cubic SH-SPC, can be constructed by folding SH-polymer sheet. The sides of the structures can be sealed and made airtight using a SH-procedure at relatively low temperatures (<90 °C). Both the (thermo) mechanical and SH-properties of the SH-SPC prototype were experimentally validated and showed excellent performances. Macroscopic incisions in the prototype were completely healed using a SH-procedure (<70 °C). Starting from this single-cell prototype, it is straight-forward to develop a multi-cell prototype, the first SPA ever built completely out of SH-polymers.