Solvent-Free and Cost-Efficient Fabrication of a High-Performance Nanocomposite Sensor for Recording of Electrophysiological Signals.

Carbon nanotube (CNT)-based nanocomposites have found applications in making sensors for various types of physiological sensing. However, the sensors' fabrication process is usually complex, multistep, and requires longtime mixing and hazardous solvents that can be harmful to the environment. Here, we report a flexible dry silver (Ag)/CNT/polydimethylsiloxane (PDMS) nanocomposite-based sensor made by a solvent-free, low-temperature, time-effective, and simple approach for electrophysiological recording. By mechanical compression and thermal treatment of Ag/CNT, a connected conductive network of the fillers was formed, after which the PDMS was added as a polymer matrix. The CNTs make a continuous network for electrons transport, endowing the nanocomposite with high electrical conductivity, mechanical strength, and durability. This process is solvent-free and does not require a high temperature or complex mixing procedure. The sensor shows high flexibility and good conductivity. High-quality electroencephalography (EEG) and electrooculography (EOG) were performed using fabricated dry sensors. Our results show that the Ag/CNT/PDMS sensor has comparable skin-sensor interface impedance with commercial Ag/AgCl-coated dry electrodes, better performance for noninvasive electrophysiological signal recording, and a higher signal-to-noise ratio (SNR) even after 8 months of storage. The SNR of electrophysiological signal recording was measured to be 26.83 dB for our developed sensors versus 25.23 dB for commercial Ag/AgCl-coated dry electrodes. Our process of compress-heating the functional fillers provides a universal approach to fabricate various types of nanocomposites with different nanofillers and desired electrical and mechanical properties.

Shape and stiffness memory ionogels with programmable pressure-resistance response.

Flexible pressure sensors usually require functional materials with both mechanical compliance and appropriate electrical performance. Most sensors based on materials with limited compressibility can hardly balance between high sensitivity and broad pressure range. Here, we prepare a heterophasic ionogel with shape and stiffness memory for adaptive pressure sensors. By combining the microstructure alignment for stiffness changing and shape memory micro-inclusions for stiffness fixing, the heterophasic ionogels reveal tunable compressibility. This controllable pressure-deformation property of the ionogels results in the pressure sensors' programmable pressure-resistance behavior with tunable pressure ranges, varied detection limits, and good resolution at high pressure. Broad pressure ranges to 220 and 380 kPa, and tunable detection limit from 120 to 330 and 950 Pa are realized by the stiffness memory ionogel sensors. Adaptive detection is also brought out to monitor tiny pressure changes at low stiffness and distinguish different human motions at high stiffness. Using shape and stiffness memory materials in pressure sensors is a general design to achieve programmable performance for more complex application scenarios.

Complex multiphase organohydrogels with programmable mechanics toward adaptive soft-matter machines.

Many biological organisms can tune their mechanical properties to adapt to environments in multistable modes, but the current synthetic materials, with bistable states, have a limited ability to alter mechanical stiffness. Here, we constructed programmable organohydrogels with multistable mechanical states by an on-demand modular assembly of noneutectic phase transition components inside microrganogel inclusions. The resultant multiphase organohydrogel exhibits precisely controllable thermo-induced stepwise switching (i.e., triple, quadruple, and quintuple switching) mechanics and a self-healing property. The organohydrogel was introduced into the design of soft-matter machines, yielding a soft gripper with adaptive grasping through stiffness matching with various objects under pneumatic-thermal hybrid actuation. Meanwhile, a programmable adhesion of octopus-inspired robotic tentacles on a wide range of surface morphologies was realized. These results demonstrated the applicability of these organohydrogels in lifelike soft robotics in unconstructed and human body environments.

Dual-Programmable Shape-Morphing and Self-Healing Organohydrogels Through Orthogonal Supramolecular Heteronetworks.

Programmable materials that can change their inherent shapes or properties are highly desirable due to their promising applications. However, among various programmable shape-morphing materials, the single control route allows temporary states to recover the unchangeable former state, thus lacking the sophisticated programmability for their shape-encoding behaviors and mechanics. Herein, dual-programmable shape-morphing organohydrogels featuring supramolecular heteronetworks are developed. In the system, the metallo-supramolecular hydrogel framework and micro-organogels featuring semicrystalline comb-type networks independently respond to different stimuli, thereby providing orthogonal dual-switching mechanics and ultrahigh mechanical strength. The supramolecular heteronetworks also possess excellent self-healing properties. More notably, such orthogonal supramolecular heteronetworks demonstrate hierarchical shape morphing performance that far exceeds conventional shape-morphing materials. Utilizing this dual programming strategy of the orthogonal supramolecular heteronetworks, the material's permanent shape can be manipulated in a step-wise shape morphing process, thereby realizing sophisticated shape changes with a high degree of freedom. The organohydrogels can act as a biomimetic smart device for the on-demand control of unidirectional liquid transport. Based on these characteristics, it is anticipated that the supramolecular organohydrogels may serve as adaptive programmable materials for a variety of applications.

Biphasic Synergistic Gel Materials with Switchable Mechanics and Self-Healing Capacity.

A fabrication strategy for biphasic gels is reported, which incorporates high-internal-phase emulsions. Closely packed micro-inclusions within the elastic hydrogel matrix greatly improve the mechanical properties of the materials. The materials exhibit excellent switchable mechanics and shape-memory performance because of the switchable micro- inclusions that are incorporated into the hydrogel matrix. The produced materials demonstrated a self-healing capacity that originates from the noncovalent effect of the biphasic heteronetwork. The aforementioned characteristics suggest that the biphasic gels may serve as ideal composite gel materials with validity in a variety of applications, such as soft actuators, flexible devices, and biological materials.