This paper presented a novel droplet-based pressure sensor using elastic and capacitive electrode–electrolyte interfaces to achieve ultrahigh mechanical-to-electrical sensitivity (1.58 μF kPa⁻¹) and resolution (1.8 Pa) with a simple device architecture. The miniature transparent droplet sensors, fabricated by one-step laser micromachining, consisted of two flexible polymer membranes with conductive coating and a separation layer hosting a sensing chamber for an electrolyte droplet. The sensing principle primarily relied on high elasticity of the sensing droplet and large capacitance presented at the electrode–electrolyte interface. A simple surface modification scheme was introduced to the conductive coating, which reduced hysteresis of the droplet deformation without substantially compromising the interfacial capacitance. Moreover, the major concern of liquid evaporation was addressed by a mixture of glycerol and electrolyte with long-term stability in a laboratory environment. Theoretical analyses and experimental investigations on several design parameters (i.e., the dimensions of the sensing chamber and the droplet size) were thoroughly conducted to characterize and optimize the overall sensitivity of the device. Moreover, the environmental influences (e.g., temperature and humidity) on the capacitive measurement were further investigated. Finally, the simply constructed and mechanically flexible droplet sensor was successfully applied to detect minute blood pressure variations on the skin surface (with the maximum value less than 100 Pa) throughout cardiovascular cycles.

An iontronic microdroplet array (IMA) device, using an ultra-large interfacial capacitance at the highly elastic droplet–electrode contact, has been proposed for flexible tactile sensing applications. The transparent IMA sensors consist of an array of nanoliter droplets sandwiched between two polymeric membranes with patterned transparent electrodes, forming the electrical double layers with remarkable unit-area capacitance. Under external loading, the membrane deformation results in the circumferential expansion at the highly elastic droplet–electrode contact, which offers a completely new capacitive sensing scheme with a dramatic increase in sensitivity. Under the simple device architecture, the IMA has achieved device sensitivity of 0.43 nF kPa⁻¹ and a minimal detectable pressure of 33 Pa, the highest reported values for its dimension. In addition, the hysteresis of the droplet deformation has been reduced by introducing a layer of hydrophobic coating to the conductive electrode surface, ensuring a fast mechanical response (on the order of several milliseconds). To demonstrate the utility of the transparent flexible IMA sensor, it has been successfully mounted onto a fingertip setting to map different surface topologies and embedded into a wristband to resolve dynamic pressure waves throughout cardiovascular cycles.

The booming of wearable electronics has nourished the progress on developing multifunctional energy storage systems with versatile flexibility, which enable the continuous and steady power supply even under various deformed states. In this sense, the synergy of flexible energy and electronic devices to construct integrative wearable microsystems is meaningful but remains quite challenging by far. Herein, we devise an innovative supercapacitor/sensor integrative wearable device that is based upon our designed vanadium nitride-graphene (VN-G) architectures. Flexible quasi-solid-state VN-G supercapacitor with ultralight and binder-free features deliver a specific capacitance of ~ 53 F·g⁻¹ with good cycle stability. On the other hand, VN-G derived pressure sensors fabricated throughout a spray-printing process also manifest favorably high sensitivity (40 kPa⁻¹ at the range of 2–10 kPa), fast response time (~ 130 ms), perfect skin conformability, and outstanding stability under static and dynamic pressure conditions. In turn, their complementary unity into a self-powered wearable sensor enables the precise detection of physiological motions ranging from pulse rate to phonetic recognition, holding promise for in-practical health monitoring applications. Open image in new window