Artificial optoelectronic synaptic characteristics of Bi2FeMnO6 ferroelectric memristor for neuromorphic computing

Tin Doping Induced High‐Performance Solution‐Processed Ga2O3 Photosensor toward Neuromorphic Visual System

“…To benchmark the performance of these Ga 2 O 3 :Sn devices, the recognition accuracy under weak light intensity stimulations was compared with various photonic synapses made of photoelectronic phototransistors, [ 7,27‐29,33,40‐42 ] photosensors, [ 6,30‐32,43 ] and optoelectronic memristors. [ 4,34‐39,44 ,45] As shown in Figure 5h, our device had comparable high recognition accuracy to the highest value of accuracy and ultra‐low light intensity response to the lowest value of intensity. This result demonstrates the outstanding performance of our devices toward high‐efficient NVS, which could broaden the application potential of the NVS from bright to dim scenes.…”

Photoelectric Memristor-Based Machine Vision for Artificial Intelligence Applications

“…At the device structure level, on the one hand, further understanding of the working mechanism of photoelectric memristors is needed. New optoelectronic device structures with continuous plasticity and high integration density should be explored to broaden the application scenarios of optoelectronic memristors and expand their applications in the field of artificial intelligence. , On the other hand, it is necessary not only to further apply photoelectric modulation to devices to obtain more conductive states but also to develop visual perception systems and more deeply simulate the complex functions of the brain, providing new opportunities for advanced machine vision systems. , The future development diagram of photoelectric memristor-based machine vision is shown in Figure . It is believed that with the efforts of researchers, photoelectric memristor-based machine vision will achieve significant breakthroughs in the application of artificial intelligence in the near future. Research regarding machine vision systems based on photoelectric memristors is a multidisciplinary research field closely related to artificial intelligence and has become an important strategic research topic in recent years.…”

“…117,118 On the other hand, it is necessary not only to further apply photoelectric modulation to devices to obtain more conductive states but also to develop visual perception systems and more deeply simulate the complex functions of the brain, providing new opportunities for advanced machine vision systems. 119,120 The future development diagram of photoelectric memristor-based machine vision is shown in Figure 16. It is believed that with the efforts of researchers, photoelectric memristor-based machine vision will achieve significant breakthroughs in the application of artificial intelligence in the near future.…”

Memristor-based neural networks: a bridge from device to artificial intelligence

“…In particular, the photoelectric synapse is also a novel type of artificial synapse combining optical pulse excitation and electrical pulse excitation, forming an important part of neuromorphic hardware development. Zhong et al reported a double-stranded ferroelectric artificial synapse based on a photoelectric co-excited state, 130 which used ultraviolet irradiation to generate excitatory postsynaptic currents and photoelectric dual controlled synapses. The memristor employed a training method based on ultraviolet excitation and ferroelectric enhancement, which greatly reduced the number of training pulses and increased synaptic plasticity.…”