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.

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.