Dual-Modal Optoelectronic Synaptic Devices with Versatile Synaptic Plasticity

Optoelectronic synaptic devices that mimic biological synapses are critical building blocks of artificial neural networks (ANN) based on optoelectronic integration. Here it is shown that an optoelectronic synaptic device based on the hybrid structure of silicon nanocrystals (Si NCs) and poly(3-hexylthiophene) (P3HT) can work with dual modes, exhibiting versatile synaptic plasticity. In the three-terminal mode, the device is a synaptic transistor, which has wavelength-selective synaptic plasticity due to potential wells enabled by the Si NCs/P3HT hybrid structure. In the two-terminal mode, it is a synaptic metal-oxide-semiconductor (MOS) device, which is capable of mimicking spike-rate-dependent plasticity (SRDP) and metaplasticity with optical stimulation. Based on the wavelength-selective synaptic plasticity a light-stimulated ANN is proposed to recognize handwritten digits with an accuracy of around 90.4%. In addition, the SRDP and metaplasticity may be well used for the simulation of edge detection of images, facilitating real-time image processing.