TY - JOUR
T1 - Recent Progress in Organic Optoelectronic Synaptic Devices
AU - He, Min
AU - Tang, Xin
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/5
Y1 - 2025/5
N2 - Organic semiconductors hold immense promise in the field of optoelectronic synapses due to their tunable optoelectronic properties, mechanical flexibility, and biocompatibility. This review article provides a comprehensive overview of recent advancements in organic optoelectronic synaptic devices. We delve into the fundamental concepts and classifications of these devices, examine their roles and operational mechanisms, and explore their diverse application scenarios. Additionally, we highlight the current challenges and emerging opportunities in this field, outlining a forward-looking path for the future development and application of these materials and devices in next-generation artificial intelligence (AI). We emphasize the potential of further optimizing organic materials and devices, which could significantly enhance the integration of organic synapses into biointegrated electronics and human–computer interfaces. By addressing key challenges such as material stability, device performance, and scalability, we aim to accelerate the transition from laboratory research to practical applications, paving the way for innovative AI systems that mimic biological neural networks.
AB - Organic semiconductors hold immense promise in the field of optoelectronic synapses due to their tunable optoelectronic properties, mechanical flexibility, and biocompatibility. This review article provides a comprehensive overview of recent advancements in organic optoelectronic synaptic devices. We delve into the fundamental concepts and classifications of these devices, examine their roles and operational mechanisms, and explore their diverse application scenarios. Additionally, we highlight the current challenges and emerging opportunities in this field, outlining a forward-looking path for the future development and application of these materials and devices in next-generation artificial intelligence (AI). We emphasize the potential of further optimizing organic materials and devices, which could significantly enhance the integration of organic synapses into biointegrated electronics and human–computer interfaces. By addressing key challenges such as material stability, device performance, and scalability, we aim to accelerate the transition from laboratory research to practical applications, paving the way for innovative AI systems that mimic biological neural networks.
KW - memristor
KW - organic semiconductor
KW - photoelectric synapse
KW - transistor
UR - http://www.scopus.com/inward/record.url?scp=105006700156&partnerID=8YFLogxK
U2 - 10.3390/photonics12050435
DO - 10.3390/photonics12050435
M3 - Review article
AN - SCOPUS:105006700156
SN - 2304-6732
VL - 12
JO - Photonics
JF - Photonics
IS - 5
M1 - 435
ER -