Taste Bud-Inspired Single-Drop Multitaste Sensing for Comprehensive Flavor Analysis with Deep Learning Algorithms.

The electronic tongue (E-tongue) system has emerged as a significant innovation, aiming to replicate the complexity of human taste perception. In spite of the advancements in E-tongue technologies, two primary challenges remain to be addressed. First, evaluating the actual taste is complex due to interactions between taste and substances, such as synergistic and suppressive effects. Second, ensuring reliable outcomes in dynamic conditions, particularly when faced with high deviation error data, presents a significant challenge. The present study introduces a bioinspired artificial E-tongue system that mimics the gustatory system by integrating multiple arrays of taste sensors to emulate taste buds in the human tongue and incorporating a customized deep-learning algorithm for taste interpretation. The developed E-tongue system is capable of detecting four distinct tastes in a single drop of dietary compounds, such as saltiness, sourness, astringency, and sweetness, demonstrating notable reversibility and selectivity. The taste profiles of six different wines are obtained by the E-tongue system and demonstrated similarities in taste trends between the E-tongue system and user reviews from online, although some disparities still exist. To mitigate these disparities, a prototype-based classifier with soft voting is devised and implemented for the artificial E-tongue system. The artificial E-tongue system achieved a high classification accuracy of ∼95% in distinguishing among six different wines and ∼90% accuracy even in an environment where more than 1/3 of the data contained errors. Moreover, by harnessing the capabilities of deep learning technology, a recommendation system was demonstrated to enhance the user experience.

Strain-Insensitive Stretchable Fiber Conductors Based on Highly Conductive Buckled Shells for Wearable Electronics.

Based on their high applicability to wearable electronics, fiber-based stretchable electronics have been developed via different strategies. However, the electrical conductivity of a fiber electrode is severely degraded, following deformation upon stretching. Despite the introduction of conductive buckled structures to resolve this issue, there still exist limitations regarding the simultaneous realizations of high conductivity and stretchability. Here, we exploit the dense distribution of the Ag nanoparticle (AgNP) network in polyurethane (PU) to fabricate a strain-insensitive stretchable fiber conductor comprising highly conductive buckled shells via a facile chemical process. These buckled AgNPs/PU fibers exhibit stable and reliable electrical responses across a wide range (tensile strain = ∼200%), in addition to their high electrical conductivity (26,128 S/m) and quality factor (Q = 2.29). Particularly, the negligible electrical hysteresis and excellent durability (>10,000 stretching-releasing cycles) of the fibers demonstrate their high applicability to wearable electronics. Furthermore, we develop buckled fiber-based pH sensors exhibiting stable, repeatable, and highly distinguishable responses (changing pH is from 4 to 8, response time is 5-6 s) even under 100% tensile strain. The buckled AgNPs/PU fibers represent a facile strategy for maintaining the stable electrical performances of fiber electrodes across the strain range of human motion for wearable applications.

Instant, multiscale dry transfer printing by atomic diffusion control at heterogeneous interfaces.

Transfer printing is a technique that integrates heterogeneous materials by readily retrieving functional elements from a grown substrate and subsequently printing them onto a specific target site. These strategies are broadly exploited to construct heterogeneously integrated electronic devices. A typical wet transfer printing method exhibits limitations related to unwanted displacement and shape distortion of the device due to uncontrollable fluid movement and slow chemical diffusion. In this study, a dry transfer printing technique that allows reliable and instant release of devices by exploiting the thermal expansion mismatch between adjacent materials is demonstrated, and computational studies are conducted to investigate the fundamental mechanisms of the dry transfer printing process. Extensive exemplary demonstrations of multiscale, sequential wet-dry, circuit-level, and biological topography-based transfer printing demonstrate the potential of this technique for many other emerging applications in modern electronics that have not been achieved through conventional wet transfer printing over the past few decades.

Ultrasensitive and Stretchable Conductive Fibers Using Percolated Pd Nanoparticle Networks for Multisensing Wearable Electronics: Crack-Based Strain and H2 Sensors.

The need for wearable electronic devices continues to grow, and the research is under way for stretchable fiber-type sensors that are sensitive to the surrounding atmosphere and will provide proficient measurement capabilities. Currently, one-dimensional fiber sensors have several limitations for their extensive use because of the complex structures of the sensing mechanisms. Thus, it is essential to miniaturize these materials with durability while integrating multiple sensing capabilities. Herein, we present an ultrasensitive and stretchable conductive fiber sensor using PdNP networks embedded in elastomeric polymers for crack-based strain and H2 sensing. The fiber multimodal sensors show a gauge factor of ∼2040 under 70% strain and reliable mechanical deformation tolerance (10,000 stretching cycles) in the strain-sensor mode. For H2 sensing, the fiber multimodal sensors exhibit a wide sensing range of high sensitivity: -0.43% response at 5 ppm (0.0005%) H2 gas and -27.3% response at 10% H2 gas. For the first time, we demonstrate highly stretchable H2 sensors that can detect H2 gas under 110% strain with mechanical durability. As demonstrated, their stable performance allows them to be used in wearable applications that integrate fiber multimodal sensors into industrial safety clothing along with a microinorganic light-emitting diode for visual indication, which exhibits proper activation upon H2 gas exposure.

Self-assembled three dimensional network designs for soft electronics.

Low modulus, compliant systems of sensors, circuits and radios designed to intimately interface with the soft tissues of the human body are of growing interest, due to their emerging applications in continuous, clinical-quality health monitors and advanced, bioelectronic therapeutics. Although recent research establishes various materials and mechanics concepts for such technologies, all existing approaches involve simple, two-dimensional (2D) layouts in the constituent micro-components and interconnects. Here we introduce concepts in three-dimensional (3D) architectures that bypass important engineering constraints and performance limitations set by traditional, 2D designs. Specifically, open-mesh, 3D interconnect networks of helical microcoils formed by deterministic compressive buckling establish the basis for systems that can offer exceptional low modulus, elastic mechanics, in compact geometries, with active components and sophisticated levels of functionality. Coupled mechanical and electrical design approaches enable layout optimization, assembly processes and encapsulation schemes to yield 3D configurations that satisfy requirements in demanding, complex systems, such as wireless, skin-compatible electronic sensors.