Iontronic Dynamic Sensor with Broad Bandwidth and Flat Frequency Response Using Controlled Preloading Strategy.

Rapid advancements in human-machine interaction and voice biometrics impose desirability on soft mechanical sensors for sensing complex dynamic signals. However, existing soft mechanical sensors mainly concern quasi-static signals such as pressure and pulsation for health monitoring, limiting their applications in emerging wearable electronics. Here, we propose a hydrogel-based soft mechanical sensor that enables recording a wide range of dynamic signals relevant to humans by combining a preloading design strategy and iontronic sensing mechanism. The proposed sensor offers a two-orders-of-magnitude larger working bandwidth (up to 1000 Hz) than most of the reported soft mechanical sensors and meanwhile provides a high sensitivity (-23 dB) that surpasses the common commercial microphone. The amplitude-frequency characteristic of the proposed sensor can be precisely tuned to meet the desired requirement by adjusting the preloads and the parameters of the microstructured hydrogel. The sensor is capable of recording instrumental sounds with high fidelity from simple pure tones to melodic songs. Demonstration of a skin-mountable sensor used for human-voice-based remote control of a toy car shows great potential for applications in the voice user interface of human-machine interactions.

Digitized Construction of Iontronic Pressure Sensor with Self-Defined Configuration and Widely Regulated Performance.

Flexible pressure sensors are essential components for wearable smart devices and intelligent systems. Significant progress has been made in this area, reporting on excellent sensor performance and fascinating sensor functionalities. Nevertheless, geometrical and morphological engineering of pressure sensors is usually neglected, which, however, is significant for practical application. Here, we present a digitized manufacturing methodology to construct a new class of iontronic pressure sensors with optionally defined configurations and widely modulated performance. These pressure sensors are composed of self-defined electrode patterns prepared by a screen printing method and highly tunable pressure-sensitive microstructures fabricated using 3D printed templates. Importantly, the iontronic pressure sensors employ an iontronic capacitive sensing mechanism based on mechanically regulating the electrical double layer at the electrolyte/electrode interfaces. The resultant pressure sensors exhibit high sensitivity (58 kPa-1), fast response/recovery time (45 ms/75 ms), low detectability (6.64 Pa), and good repeatability (2000 cycles). Moreover, our pressure sensors show remarkable tunability and adaptability in device configuration and performance, which is challenging to achieve via conventional manufacturing processes. The promising applications of these iontronic pressure sensors in monitoring various human physiological activities, fabricating flexible electronic skin, and resolving the force variation during manipulation of an object with a robotic hand are successfully demonstrated.

Structural Engineering of the Barrier Oxide Layer of Nanoporous Anodic Alumina for Iontronic Sensing.

The hemispherical barrier oxide layer (BOL) closing the bottom tips of hexagonally distributed arrays of cylindrical nanochannels in nanoporous anodic alumina (NAA) membranes is structurally engineered by anodizing aluminum substrates in three distinct acid electrolytes at their corresponding self-ordering anodizing potentials. These nanochannels display a characteristic ionic current rectification (ICR) signal between high and low ionic conduction states, which is determined by the thickness and chemical composition of the BOL and the pH of the ionic electrolyte solution. The rectification efficiency of the ionic current associated with the flow of ions across the anodic BOL increases with its thickness, under optimal pH conditions. The inner surface of the nanopores in NAA membranes was chemically modified with thiol-terminated functional molecules. The resultant NAA-based iontronic system provides a model platform to selectively detect gold metal ions (Au3+) by harnessing dynamic ICR signal shifts as the core sensing principle. The sensitivity of the system is proportional to the thickness of the barrier oxide layer, where NAA membranes produced in phosphoric acid at 195 V with a BOL thickness of 232 ± 6 nm achieve the highest sensitivity and low limit of detection in the sub-picomolar range. This study provides exciting opportunities to engineer NAA structures with tailorable ICR signals for specific applications across iontronic sensing and other nanofluidic disciplines.

Imperceptible Epidermal-Iontronic Interface for Wearable Sensing.

Recent development of epidermal electronics provides an enabling means to continuous monitoring of physiological signals and close tracking of physical activities without affecting quality of life. Such devices require high sensitivity for low-magnitude signal detection, noise reduction for motion artifacts, imperceptible wearability with long-term comfortableness, and low-cost production for scalable manufacturing. However, the existing epidermal pressure sensing devices, usually involving complex multilayer structures, have not fully addressed the aforementioned challenges. Here, the first epidermal-iontronic interface (EII) is successfully introduced incorporating both single-sided iontronic devices and the skin itself as the pressure sensing architectures, allowing an ultrathin, flexible, and imperceptible packaging with conformal epidermal contact. Notably, utilizing skin as part of the EII sensor, high pressure sensitivity and high signal-to-noise ratios are achieved, along with ultralow motion artifacts for both internal (body) and external (environmental) mechanical stimuli. Monitoring of various vital signals, such as blood pressure waveforms, respiration waveforms, muscle activities and artificial tactile sensation, is successfully demonstrated, implicating a broad applicability of the EII devices for emerging wearable applications.