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Analytical Modeling of Organic–Inorganic CH 3 NH 3 PbI 3 Perovskite Resistive Switching and its Application for Neuromorphic Recognition (Adv. Theory Simul. 4/2018)
Author(s) -
Ren Yanyun,
Milo Valerio,
Wang Zhongqiang,
Xu Haiyang,
Ielmini Daniele,
Zhao Xiaoning,
Liu Yichun
Publication year - 2018
Publication title -
advanced theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.068
H-Index - 17
ISSN - 2513-0390
DOI - 10.1002/adts.201870009
Subject(s) - neuromorphic engineering , resistive random access memory , perovskite (structure) , materials science , resistive touchscreen , resistor , computer science , scheme (mathematics) , optoelectronics , layer (electronics) , electronic engineering , artificial neural network , computer architecture , nanotechnology , physics , artificial intelligence , electrical engineering , engineering , mathematics , electrode , quantum mechanics , mathematical analysis , voltage , chemical engineering , computer vision
Analytical models are crucial for building a theoretical basis for optimizing RRAM scheme and implementing its application in neuromorphic computing. In article number 1700035 , Zhongqiang Wang, Haiyang Xu, Daniele Ielmini, and co‐workers present an analytical model demonstrating the evolution of resistive switching dynamics for CH 3 NH 3 PbI 3 perovskite‐based RRAM. Furthermore, a 2‐layer neuromorphic network with 2‐transistor/1‐resistor synapses is demonstrated. This study paves the way for the use of perovskite‐based RRAM devices for neuromorphic systems.