Optoelectronic synaptic transistors based on upconverting nanoparticles. Issue 2 (16th December 2020)

• Record Type: Journal Article
• Authors: Lian, Haixia; Liao, Qiufan; Yang, Baidong; Zhai, Yongbiao; Han, Su-Ting; Zhou, Ye
• Is Part Of: Journal of materials chemistry. Volume 9:Issue 2(2021)
• Page Start: 640
• Page End: 648
• Publication Date: 2020-12-16
• Subjects: Materials -- Periodicals; Chemistry, Analytic -- Periodicals; Optical materials -- Research -- Periodicals; Electronics -- Materials -- Research -- Periodicals; 543.0284
• DOI: 10.1039/d0tc04115g
• Languages: English
• ISSNs: 2050-7526

Abstract

Abstract : Transistors based on upconverting nanoparticles enable the simulation of artificial synaptic functions. Abstract : Neuromorphic computing inspired by the functions of human brain has attracted much attention in the research area of artificial intelligence. Herein, we report an optoelectronic synapse based on a polyvinylpyrrolidone (PVPy)-upconverting nanoparticle (UCNP) hybrid floating gate transistor. The UCNP-based synaptic transistor exhibits a remarkable near-infrared (NIR)-induced de-trapping behaviour as well as a long retention time. Furthermore, our device is employed to successfully emulate various synaptic functions including postsynaptic current with different duration times and pulse amplitudes, paired-pulse facilitation/depression, transition from short-term plasticity to long-term plasticity and learning-forgetting-relearning processes. Overall, this work may open up a new opportunity for NIR optoelectronic synapses.