Evolutionary 2D organic crystals for optoelectronic transistors and neuromorphic computing. Issue 1 (7th February 2022)

• Record Type: Journal Article
• Authors: Qian, Fangsheng; Bu, Xiaobo; Wang, Junjie; Lv, Ziyu; Han, Su-Ting; Zhou, Ye
• Is Part Of: Neuromorphic computing and engineering. Volume 2:Issue 1(2022)
• Publication Date: 2022-02-07
• Subjects: 2D organic crystals -- transistors -- optoelectronic synapses -- neuromorphic computing; Neural networks (Computer science) -- Periodicals; Neural computers -- Periodicals; Neuromorphics -- Periodicals; 006.3
• DOI: 10.1088/2634-4386/ac4a84
• Languages: English
• ISSNs: 2634-4386

Abstract

Abstract: Brain-inspired neuromorphic computing has been extensively researched, taking advantage of increased computer power, the acquisition of massive data, and algorithm optimization. Neuromorphic computing requires mimicking synaptic plasticity and enables near-in-sensor computing. In synaptic transistors, how to elaborate and examine the link between microstructure and characteristics is a major difficulty. Due to the absence of interlayer shielding effects, defect-free interfaces, and wide spectrum responses, reducing the thickness of organic crystals to the 2D limit has a lot of application possibilities in this computing paradigm. This paper presents an update on the progress of 2D organic crystal-based transistors for data storage and neuromorphic computing. The promises and synthesis methodologies of 2D organic crystals (2D OCs) are summarized. Following that, applications of 2D OCs for ferroelectric non-volatile memory, circuit-type optoelectronic synapses, and neuromorphic computing are addressed. Finally, new insights and challenges for the field's future prospects are presented, pushing the boundaries of neuromorphic computing even farther.