Artificial synapses with photoelectric plasticity and memory behaviors based on charge trapping memristive system

Imitation of memory and learning behaviors of nervous system by nanoscale photoelectric devices is highly desirable for building neuromorphic systems or even artificial neural networks. In this work, artificial synapses with photoelectric plasticity and memory behaviors based on a charge trapping memristive system was fabricated. Versatile synaptic functions, such as photoelectric excitatory postsynaptic current behavior, short-term memory, long-term memory, short - to long-term memory transition, and photonic learning and forgetting behaviors, were all mimicked by applied pulses of light and electricity. Moreover, the device also has the potential to be used in flexible applications. The photoelectric plasticity and memory phenomenon can be attributed to charge trapping and detrapping, since the used CdSe/ZnS quantum dots with a quantum well structure that act as trapping centers. This work provides a cost-effective method to develop artificial synapse devices, neural networks, and computers with photoelectric operations. (C) 2019 The Authors. Published by Elsevier Ltd.