Organic neuromorphic electronics powering intelligent sensory and edge computing systems

Abstract

Neuromorphic sensing technology is rapidly evolving from laboratory demonstrations to application-driven prototypes such as multimodal wearables that integrate touch, vision, and chemistry, synaptic devices operating under aqueous, low-voltage conditions, and skin-like arrays capable of on-site learning. Organic materials have emerged as promising candidates for these technologies owing to their softness, biocompatibility, and intrinsic ionic–electronic coupling that emulates synaptic signaling. Despite accelerating progress in wearables and human–machine interfaces, this field still lacks an integrated, application-oriented overview of organic neuromorphic systems. This review addresses that gap by clarifying when to employ different device platforms and how electric signals are translated into chemical, physical, and visual sensing. We first discuss the characteristics of bioneural signals and how the devices can mimic them. We then compare device platforms, including two-terminal devices and three-terminal transistors, outlining their structures and operation mechanisms. Building on these foundations, we introduce various sensory applications across chemical detection, physical stimuli, and visual photoreception, including multimodal architectures that integrate heterogeneous inputs within a single adaptive system. The review concludes by summarizing the defining characteristics of organic neuromorphic devices and outlining the remaining challenges for future research.

Keywords

artificial neural networks / artificial synaptic devices / bioelectronics / neuromorphic electronics / wearable electronics

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