Elvis K. Boahen

Ionic diodes, which enable unidirectional ion transport, hold great promise for adaptive and energy-efficient ionotronic systems. However, conventional designs often rely on high ion concentrations, which promote ion pairing and clustering, thereby reducing mobility and impeding the formation of stable ion depletion layers (IDLs). Here, we report a mechano-gated ionic diode with balanced ionic conductivity between cationic and anionic polymer layers, achieved through copolymer engineering. This conductivity matching enables the formation of well-defined IDLs, yielding a record-high rectification ratio of 23.5 and pressure-sensitive piezo-ionic behavior. The device transduces mechanical stimuli into discrete ionic spikes via threshold-gated current modulation, consuming only 0.41 nanojoules per spike at rest and 1.49 nanojoules under pressure, achieving up to a 24-fold enhancement in signal-to-noise ratio. When integrated into a tactile interface, the diode exhibits synaptic-like plasticity and activity-dependent signal encoding. These findings establish a material-driven strategy for real-time, low-power ionic sensing and neuromorphic functionality.

Recent advancements in polymer science have enabled the development of plastic bioelectronics, providing soft, stretchable, and tissue‐conformable technologies for continuous health monitoring, diagnostics, and therapeutic interventions. Unlike conventional silicon‐based electronics that often exhibit mechanical mismatches with biological tissues, plastic bioelectronic systems leverage intrinsically soft and mechanically compliant organic and polymer materials to achieve enhanced conformability. This reduces interfacial stress and enables high‐fidelity signal acquisition from dynamic tissue interfaces. However, the low mechanical modulus that enables their unique advantages also makes these systems susceptible to mechanical damage, weak adhesion, and functional degradation under physiological conditions. To overcome these limitations, emerging research focuses on integrating autonomous polymer frameworks (auto‐POFs)–engineered materials that endow the polymer matrix with self‐adhesion, self‐protection, self‐healing, self‐degradation, and self‐sensing capabilities. These features enable real‐time responsiveness to stimuli and extend device lifespan without external intervention. This review provides a comprehensive overview of recent progress in auto‐POF‐based systems, including their material design strategies, functional mechanisms, and roles in enhancing the reliability and adaptability of sustainable, wearable, and implantable tissue‐interfaced plastic bioelectronics. By highlighting key material innovations and device architectures, the path is outlined toward next‐generation biomedical platforms capable of autonomous and sustainable operation in dynamic biological environments.

Sensorineural hearing loss is the most common form of deafness, typically resulting from the loss of sensory cells on the basilar membrane, which cannot regenerate and thus lose sensitivity to sound vibrations. Here, we report a reconfigurable piezo-ionotropic polymer membrane engineered for biomimetic sustainable multi-resonance acoustic sensing, offering exceptional sensitivity (530 kPa^-1) and broadband frequency discrimination (20 Hz to 3300 Hz) while remaining resistant to "dying". The acoustic sensing capability is driven by an ion hitching-in cage effect intrinsic to the ion gel combined with fluorinated polyurethane. In this platform, the engineered ionotropic polymer stretches under acoustic vibrations, allowing cations to penetrate the widened hard segments and engage in strong ion-dipole interactions (cation···F), thereby restricting ion flux and amplifying impedance changes. Additionally, the sensor's sustainability is ensured through its self-healing properties and hydrophobic components, which enable effective self-repair in both conventional and aqueous environments without ion leakage, achieving a room-temperature healing speed of 0.3-0.4 μm/min. This sustainable acoustic sensing technology enables the devices to reliably identify specific sounds in everyday environments (e.g., human voices, piano notes), demonstrating their potential application as artificial basilar membranes.

Sensorineural hearing loss is the most common form of deafness, typically resulting from the loss of sensory cells on the basilar membrane, which cannot regenerate and thus lose sensitivity to sound vibrations. Here, we report a reconfigurable piezo-ionotropic polymer membrane engineered for biomimetic sustainable multi-resonance acoustic sensing, offering exceptional sensitivity (530 kPa⁻¹) and broadband frequency discrimination (20 to 3300 Hz) while remaining resistant to "dying." The acoustic sensing capability is driven by an ion hitching-in cage effect intrinsic to the ion gel combined with fluorinated polyurethane. In this platform, the engineered ionotropic polymer stretches under acoustic vibrations, allowing cations to penetrate the widened hard segments and engage in strong ion-dipole interactions (cation···F), thereby restricting ion flux and amplifying impedance changes. Additionally, the sensor’s sustainability is ensured through its self-healing properties and hydrophobic components, which enable effective self-repair in both conventional and aqueous environments without ion leakage, achieving a room-temperature healing speed of 0.3–0.4 µm/min. Leveraging this newly developed sustainable acoustic sensing technology, our devices demonstrate high proficiency in identifying specific sounds in everyday environments (e.g., human voices, piano notes), underscoring their potential as artificial basilar membranes.

Inspired by the extensive signal processing capabilities of the human nervous system, neuromorphic artificial sensory systems have emerged as a pivotal technology in advancing brain‐like computing for applications in humanoid robotics, prosthetics, and wearable technologies. These systems mimic the functionalities of the central and peripheral nervous systems through the integration of sensory synaptic devices and neural network algorithms, enabling external stimuli to be converted into actionable electrical signals. This review delves into the intricate relationship between synaptic device technologies and neural network processing algorithms, highlighting their mutual influence on artificial intelligence capabilities. This study explores the latest advancements in artificial synaptic properties triggered by various stimuli, including optical, auditory, mechanical, and chemical inputs, and their subsequent processing through artificial neural networks for applications in image recognition and multimodal pattern recognition. The discussion extends to the emulation of biological perception via artificial synapses and concludes with future perspectives and challenges in neuromorphic system development, emphasizing the need for a deeper understanding of neural network processing to innovate and refine these complex systems.

The development of advanced materials capable of autonomous self-healing and mechanical stimulus sensing in aquatic environments holds great promise for applications in underwater soft electronics, underwater robotics, and water-resistant human-machine interfaces. However, achieving superior autonomous self-healing properties and effective sensing simultaneously in an aquatic environment is rarely feasible. Here, we present an ultrafast underwater molecularly engineered self-healing piezo-ionic elastomer inspired by the cephalopod’s suckers, which possess self-healing properties and mechanosensitive ion channels. Through strategic engineering of hydrophobic C–F groups, hydrolytic boronate ester bonds, and ions, the material achieves outstanding self-healing efficiencies, with speeds of 94.5% (9.1 µm/min) in air and 89.6% (13.3 µm/min) underwater, coupled with remarkable pressure sensitivity (18.1 kPa^–1) for sensing performance. Furthermore, integration of this mechanosensitive device into an underwater submarine for signal transmission and light emitting diode modulation demonstrates its potential for underwater robotics and smarter human-machine interactions.