Advances in Organic In‐Sensor Neuromorphic Computing: from Material Mechanisms to Applications
Dong Hyun Lee, Woojo Kim, Eun Kwang Lee, Hocheon Yoo
Abstract
In‐sensor neuromorphic computing integrates sensing and processing within a single material system, enabling real‐time, ultralow‐power computation for biomedical signal analysis, artificial skin, and brain‐machine interfaces. Organic sensors, organic electrochemical transistors, and memory‐based synaptic devices serve as key components, utilizing ion–electron coupling and nonvolatile synaptic weight modulation for energy‐efficient neuromorphic functions. Reflecting the potential of the aforementioned in‐sensor computing, this review provides a comprehensive analysis of organic‐based in‐sensor computing for wearable and bioelectronic applications. It explores the design and mechanisms of organic synaptic devices, with a focus on memory‐based and organic electrochemical transistor‐based architectures. The fundamental principles of neuromorphic computing are examined, highlighting various organic neuromorphic computing devices and their operational characteristics. Through an in‐depth discussion of recent advancements, challenges, and future perspectives, this review aims to offer valuable insights into the potential of organic electronics in advancing intelligent systems.