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Nonvolatile Memory and Artificial Synaptic Characteristics in Thin‐Film Transistors with Atomic Layer Deposited HfOx Gate Insulator and ZnO Channel Layer
Author(s) -
Lee Hyerin,
Beom Keonwon,
Kim Minju,
Kang Chi Jung,
Yoon TaeSik
Publication year - 2020
Publication title -
advanced electronic materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.25
H-Index - 56
ISSN - 2199-160X
DOI - 10.1002/aelm.202000412
Subject(s) - materials science , non volatile memory , optoelectronics , atomic layer deposition , transistor , neuromorphic engineering , thin film transistor , layer (electronics) , stack (abstract data type) , nanotechnology , voltage , electrical engineering , computer science , artificial neural network , engineering , machine learning , programming language
Nonvolatile memory and synaptic characteristics in thin‐film transistors (TFTs) with HfOx gate insulator and ZnO channel are investigated for the application to nonvolatile memory and artificial synapse in neuromorphic systems. Nonvolatile change of drain current induced by modulated gate stack properties is demonstrated to be applicable to nonvolatile memory operation. It also emulates synaptic weight change for learning and memory functions in artificial synapses. The TFTs with HfOx and ZnO layers deposited by sputtering or atomic layer deposition (ALD) at low temperatures exhibit tunable drain current upon applying gate pulses, featuring analog, reversible, nonvolatile changes with respect to pulse amplitude, width, interval, and repetition number. However, the TFTs with HfOx and ZnO by ALD at high temperatures show negligible change. The structural and chemical analyses reveal similarities in defective nature of sputter‐deposited and low‐temperature ALD HfOx and ZnO layers, leading to analogous drain current modulation. Also, the results of temperature‐ and voltage polarity‐dependent drain current changes and capacitance changes verify that the drain current modulation is driven by oxygen ion migration associated with defective states of HfOx and ZnO layers. It demonstrates feasibility of application of ALD‐HfOx/ZnO TFTs to nonvolatile memory and artificial synapses using modulated gate stack properties.