Evolutionary 2D organic crystals for optoelectronic transistors and neuromorphic computing

Fangsheng Qian, Xiaobo Bu, Junjie Wang, Ziyu Lv, Su‐Ting Han, Ye Zhou
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引用次数: 8

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 are summarized. Following that, applications of 2D organic crystals for ferroelectric nonvolatile 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.
用于光电晶体管和神经形态计算的进化二维有机晶体
大脑启发的神经形态计算已经得到了广泛的研究,利用了不断增强的计算机能力、大量数据的获取和算法优化。神经形态计算需要模拟突触可塑性,并实现近传感器计算。在突触晶体管中,如何阐述和检验微观结构与特性之间的联系是一个主要的难点。由于没有层间屏蔽效应、无缺陷界面和宽谱响应,将有机晶体的厚度减小到二维极限在该计算范式中具有许多应用可能性。本文介绍了用于数据存储和神经形态计算的二维有机晶体晶体管的最新进展。综述了二维有机晶体的发展前景和合成方法。随后,讨论了二维有机晶体在铁电非易失性存储器、电路型光电突触和神经形态计算方面的应用。最后,提出了该领域未来前景的新见解和挑战,进一步推动了神经形态计算的边界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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