Self-sensing coaxial muscle fibers with bi-lengthwise actuation

Carbon Nanotube-Directed 7 GPa Heterocyclic Aramid Fiber and Its Application in Artificial Muscles

Poly(p-phenylene-benzimidazole-terephthalamide) (PBIA) fibers with excellent mechanical properties are widely used in fields that require impact-resistant materials such as ballistic protection and aerospace. The introduction of heterocycles in polymer chains increases their flexibility and makes it easier to optimize the fiber structure. However, the inadequate orientation of polymer chains is one of the main reasons for the large difference between the measured and theoretical mechanical properties of PBIA fibers. Herein, carbon nanotubes (CNTs) are selected as an orientation seed. Their structural features allow CNTs to orient during the spinning process, which can induce an orderly arrangement of polymers and improve the orientation of the fiber microstructure. To ensure the complete 1D topology of long CNTs (≈10 µm), PBIA is used as an efficient dispersant to overcome dispersion challenges. The p-CNT/PBIA fibers (10 µm single-walled carbon nanotube 0.025 wt%) exhibit an increase of 22% in tensile strength and 23% in elongation, with a maximum tensile strength of 7.01 ± 0.31 GPa and a reinforcement efficiency of 893.6. The artificial muscle fabricated using CNT/PBIA fibers exhibits a 34.8% contraction and a 25% lifting of a 2 kg dumbbell, providing a promising paradigm for high-performance organic fibers as high-load smart actuators.

A Solvent-Templated Porous Liquid Crystal Elastomer with Tactile Sensation beyond Reversible Actuation toward Versatile Artificial Muscles

Liquid crystal elastomers (LCEs), as a classical two-way shape-memory material, are good candidates for developing artificial muscles that mimic the contraction, expansion, or rotational behavior of natural muscles. However, biomimicry is currently focused more on the actuation functions of natural muscles dominated by muscle fibers, whereas the tactile sensing functions that are dominated by neuronal receptors and synapses have not been well captured. Very few studies have reported the sensing concept for LCEs, but the signals were still donated by macroscopic actuation, that is, variations in angle or length. Herein, we develop a conductive porous LCE (CPLCE) using a solvent (dimethyl sulfoxide (DMSO))-templated photo-cross-linking strategy, followed by carbon nanotube (CNT) incorporation. The CPLCE has excellent reversible contraction/elongation behavior in a manner similar to the actuation functions of skeletal muscles. Moreover, the CPLCE shows excellent pressure-sensing performance by providing real-time electrical signals and is capable of microtouch sensing, which is very similar to natural tactile sensing. Furthermore, macroscopic actuation and tactile sensation can be integrated into a single system. Proof-of-concept studies reveal that the CPLCE-based artificial muscle is sensitive to external touch while maintaining its excellent actuation performance. The CPLCE with tactile sensation beyond reversible actuation is expected to benefit the development of versatile artificial muscles and intelligent robots.

Moisture-Adaptive Contractile Biopolymer-Derived Fibers for Wound Healing Promotion

The advancement in thermosensitive active hydrogels has opened promising opportunities to dynamic full-thickness skin wound healing. However, conventional hydrogels lack breathability to avoid wound infection and cannot adapt to wounds with different shapes due to the isotropic contraction. Herein, a moisture-adaptive fiber that rapidly absorbs wound tissue fluid and produces a large lengthwise contractile force during the drying process is reported. The incorporation of hydroxyl-rich silica nanoparticles in the sodium alginate/gelatin composite fiber greatly improves the hydrophilicity, toughness, and axial contraction performance of the fiber. This fiber exhibits a dynamic contractile behavior as a function of humidity, generating ≈15% maximum contraction strain or ≈24 MPa maximum isometric contractile stress. The textile knitted by the fibers features excellent breathability and generates adaptive contraction in the target direction during the natural desorption of tissue fluid from the wounds. In vivo animal experiments further demonstrate the advantages of the textiles over traditional dressings in accelerating wound healing.

Tethering of twisted-fiber artificial muscles

Twisted-fiber artificial muscles, a new type of soft actuator, exhibit significant potential for use in applications related to lightweight smart devices and soft robotics. Fiber twisting generates internal torque and a spiral architecture, exhibiting rotation, contraction, or elongation as a result of fiber volume change. Untethering a twisted fiber often results in fiber untwisting and loss of stored torque energy. Preserving the torque in twisted fibers during actuation is necessary to realize a reversible and stable artificial muscle performance; this is a key issue that has not yet been systematically discussed and reviewed. This review summarizes the mechanisms for preserving the torque within twisted fibers and the potential applications of such systems. The potential challenges and future directions of research related to twisted-fiber artificial muscles are also discussed.

Self-Aware Artificial Coiled Yarn Muscles with Enhanced Electrical Conductivity and Durability via a Two-Step Process

Muscles are capable of modulating the body and adapting to environmental changes with a highly integrated sensing and actuation. Inspired by biological muscles, coiled/twisted fibers are adopted that can convert volume expansion into axial contraction and offer the advantages of flexibility and light weight. However, the sensing-actuation integrated fish line/yarn-based artificial muscles are still barely reported due to the poor actuation-sensing interface with off-the-shelf fibers. We report herein artificial coiled yarn muscles with self-sensing and actuation functions using the commercially available yarns. Via a two-step process, the artificial coiled yarn muscles are proved to obtain enhanced electrical conductivity and durability, which facilitates the long-term application in human-robot interfaces. The resistivity is successfully reduced from 172.39 Ω·cm (first step) to 1.27 Ω·cm (second step). The multimode sense of stretch strain, pressure, and actuation-sensing are analyzed and proved to have good linearity, stability and durability. The muscles could achieve a sensitivity (gauge factor, GF) of the contraction strain perception up to 1.5. We further demonstrate this self-aware artificial coiled yarn muscles could empower non-active objects with actuation and real-time monitoring capabilities without causing damage to the objects. Overall, this work provides a facile and versatile tool in improving the actuation-sensing performances of the artificial coiled yarn muscles and has the potential in building smart and interactive soft actuation systems.

Artificial neuromuscular fibers by multilayered coaxial integration with dynamic adaption

Integrating sense in a thin artificial muscle fiber for environmental adaption and actuation path tracing, as a snail tentacle does, is highly needed but still challenging because of the interfacing mismatch between the fiber's actuation and sensing components. Here, we report an artificial neuromuscular fiber by wrapping a carbon nanotube (CNT) fiber core in sequence with an elastomer layer, a nanofiber network, and an MXene/CNT thin sheath, achieving the ingenious sense-judge-act intelligent system in an elastic fiber. The CNT/elastomer components provide actuation, and the sheath enables touch/stretch perception and hysteresis-free cyclic actuation tracing due to its strain-dependent resistance. As a whole, the coaxial structure builds a dielectric capacitor that enables sensitive touchless perception. The key to seamless integration is to use a nanofiber interface that allows the sensing layer to adaptively trace but not restrict actuation. This work provides promising solutions for closed-loop control for future intelligent soft robots.