This review highlights recent progress in organic phototransistor technology for neuromorphic computing and its implications.
The von Neumann architecture faces significant limitations, including low transmission efficiency and high energy consumption, when handling large-scale data and unstructured problems. Benefiting from the inherent merits of optical signals including high bandwidth, near-zero Joule heating, fast transmission speed, and immunity to electromagnetic interference, photonics provides a powerful pathway for high-speed neuromorphic computing. Together with the mechanical flexibility and largearea manufacturability of organic semiconductors, organic phototransistor (OPT)-based photonic synapses have therefore attracted extensive attention in recent years. This review provides a comprehensive overview of recent advances in OPT-based photonic synapses, covering operational principles, active materials, advances in bidirectional photoresponse process, as well as cutting-edge applications. Finally, the current challenges and opportunities in this field are highlighted. Distinct from previous reviews, this review emphasizes an in-depth exploration of bidirectional photoresponse mechanisms, a systematic dissection of material–structure–function correlations enabling integrated sensing-memory technology, and emerging.
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Ding et al. (2026) studied this question.
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