Youn Sang Kim

Ionovoltaics is a breakthrough concept in energy conversion that harnesses water motion with ion dynamics to generate electrical energy. This phenomenon is based on the interaction between the nanoscopic ionic behavior at the solid–liquid interface and the flow of electrons in a semiconductor electrode. Ionovoltaic research aims to present the most rational and convincing mechanism for the much‐debated principle of energy conversion by water motion through a deeper understanding of solid–liquid interfacial phenomena and to discuss the potential to transform related fields through the development of enabling technologies such as novel energy harvesters, interfacial analysis tools, and bio/chemical sensors. Furthermore, efforts to develop high‐efficiency ionovoltaic device powered by small water droplets indicate a potential contribution to the advancement of green energy systems that complement solar and wind power generation and address environmental pollution and energy shortages. This review paper explores the evolution of energy harvesting technologies using water motion, with a particular focus on ionovoltaics as an emerging field. By establishing the fundamentals, this study investigates solid–liquid interfaces, semiconductor properties, and natural water motion‐driven ionovoltaic phenomena and also highlights that extensive research on complex ion/interface phenomena can have practical applications in diverse industrial fields. image

Synaptic devices that mimic biological neurons have attracted much attention for brain-inspired neuromorphic computing. Especially, synaptic thin-film transistors (TFTs) have emerged with simultaneous signal processing and information storage advantages. However, the analysis of excitatory postsynaptic current (EPSC) relies on an empirical model such as a serial RC circuit, which limits a systematic and in-depth study of synaptic devices in terms of material and electrical properties. Herein, the single-pulse-driven synaptic EPSC (SPSE) model, including capacitive effect and information of the synaptic window, is analytically proposed. The SPSE model can simulate EPSC of synaptic devices at given TFT-operating conditions. EPSC with the SPSE model can be characterized with quantified parameters for the capacitive effects and the synaptic windows, which also depend on the electrical condition applied to TFTs. Various kinds of synaptic-TFTs with different gate insulators (e.g., SiO2 and ion-gel) are used to confirm the performance of the SPSE model. For example, the SPSE model can capture the long-term robustness of ion-gel-based TFTs with specific quantified parameters. In addition, the SPSE model enables the estimation of energy consumption, which can potentially be leveraged to compare the energy cost of EPSC fairly. The SPSE model can provide a guideline to understand the physical properties of synaptic TFTs.