journal article·2023-12-02

Synaptic Characteristics of Atomic Layer-Deposited Ferroelectric Lanthanum-Doped HfO2 (La:HfO2) and TaN-Based Artificial Synapses

Yu-Rim Jeon, Duho Kim, Boncheol Ku, Chulwon Chung, Changhwan Choi

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Abstract

Analog synaptic devices have made significant advances based on various electronic materials that can realize the biological synapse properties of neuromorphic computing. Ferroelectric (FE) HfO 2 -based materials with nonvolatile and low power consumption characteristics are being studied as promising materials for application to analog synaptic devices. The gradual reversal of FE multilevel polarization results in precise changes in the channel conductance and allows analogue synaptic weight updates. However, there have been few studies of FE synaptic devices doped with La, Y, and Gd. Furthermore, an investigation of interface quality is also crucial to enhance the remnant polarization ( P r ), synaptic conductance linearity, and reliability characteristics. In this study, we demonstrate improved FE and artificial synaptic characteristics using an atomic layer-deposited (ALD) lanthanum-doped HfO 2 (La:HfO 2 ) and TaN electrode in the structure of an FE thin-film transistor (ITO/IGZO/La:HfO 2 /TaN), where indium–tin oxide (ITO) and indium–gallium–zinc oxide (IGZO) were used as source/drain and channel materials, respectively. Improved P r and lower surface roughness were achieved by doped HfO 2 and ALD TaN thin films. This synaptic transistor shows long-term potentiation and long-term depression with 200 levels of conductance states, high linearity ( A p, 0.97; A d, 0.86), high G max / G min (∼6.1), and low cycle-to-cycle variability. In addition, a pattern recognition accuracy higher than 90% was achieved in an artificial neural network simulation.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Semiconductor materials and devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States

Division of Materials Science & Engineering, Hanyang University, Seoul 04763, Korea

Department of Energy Engineering, Hanyang University, Seoul 04763, Korea

Funding

National Research Foundation of Korea

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