Vision system utilizing large-area organic single crystals for sensory applications

Abstract

The development of brain-inspired neural network computing synaptic devices based on organic field-effect transistors (OFETs) represents a pivotal research frontier in neuromorphic computing and flexible electronics. These devices elucidate fundamental mechanistic parallels between biological neural networks and artificial systems, facilitating the paradigm shift in organic electronics from passive “sensing” to active “cognition”. This technological evolution enables loop perception-computation-decision architectures while unlocking transformative opportunities in intelligent hardware and medical technologies. Such pioneering advancements are poised to redefine the global semiconductor industry landscape by bridging neuromorphic engineering with next-generation bioelectronic applications, ultimately driving the convergence of adaptive learning systems and human-machine symbiotic interfaces. A low-voltage (1 V) C₈-BTBT optoelectronic synaptic array (coefficient of variation in synaptic weight modulation: 8%) emulated human visual information processing under distinct cognitive states: dispersed-attention mode achieved rapid response and short-term plasticity, while focused-attention mode enabled noise suppression and long-term potentiation via carrier trapping modulation. This platform advances hardware-level perception-computation integration for biomimetic vision chips.