Jin Yeong Song
Papers
2
Total Citations
64
H-Index
2
About
Jin Yeong Song is a leading researcher in the fields of self-powered sensors, triboelectric nanogenerators, and advanced electrode patterning for wearable electronics. His work is distinguished by a focus on creating environmentally robust, intelligent systems that bridge the gap between energy harvesting and practical AIoT applications. Song’s major contributions include the development of a highly efficient patterning technique for silver nanowire electrodes using electrospray deposition, a method that dramatically reduces material waste and enables the creation of high-performance transparent electrodes for self-powered triboelectric tactile sensors. This foundational work, cited 35 times, has been pivotal for next-generation wearable devices. More recently, Song has pioneered an environmentally robust triboelectric tire monitoring system that integrates hybrid deep learning for self-powered driving information recognition, a breakthrough that addresses the critical challenge of environmental fluctuations in triboelectric signals. This 2024 study, with 29 citations, showcases his ability to merge materials science with advanced AI. Song’s research is not only highly cited but also directly applicable to the development of durable, intelligent, and sustainable electronic systems, marking him as a key innovator in the field of self-powered smart technologies.
Research Focus
Key Achievements
Top Papers
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