Metal free all oxide SnOx/HfOx bilayer transristor synapse for neuromorphic computing

Developing flexible and transparent memristors for emulating biological activities aligns with the growing demand for sustainable technologies in electronics. This paper presents the development and characterization of transparent memristors (transristors) on a flexible substrate, utilizing a structure of ITO/SnOx/HfOx/ITO/PEN. Hafnium oxide (HfOx) and tin oxide (SnOx) films are sequentially RF sputtered onto an indium doped tin oxide (ITO) bottom electrode, with polyethylene naphthalate serving as the flexible substrate. Then, an ITO top electrode is sputtered onto the SnOx layer using a shadow mask. Samples with varying thicknesses of HfOx and SnOx were prepared to optimize the device configuration. Electrical switching and synaptic characteristics of these samples were measured at room temperature, with a positive voltage applied to the top electrode and a negative voltage to the bottom electrode. This study identifies a configuration with 35 nm SnOx and 6 nm HfOx as the most effective, exhibiting excellent bipolar switching properties. Notably, it demonstrates low set/reset voltages of 1.3 and −1.6 V, with a compliance current of 100 μA. X-ray photoelectron spectroscopy was employed to assess the concentration of oxygen vacancies in the films. The device also shows the highest endurance up to 104 cycles, long-term potentiation/depression characteristics over 350 cycles, a good nonlinearity value of 1.53 (potentiation)/1.46 (depression), and 100% pattern recognition accuracy at just 14 iterations. Multi-state resistive switching characteristics were also explored. Obtained characteristics reveal that the optimized device could serve as a flexible component in making artificial synapses.

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Publication Details

Journal
Journal of Applied Physics
Published
2025-03-17
DOI
https://doi.org/10.1063/5.0231295
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73

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Metal free all oxide SnOx/HfOx bilayer transristor synapse for neuromorphic computing

Asutosh Patnaik, Debashis Panda, Tseung‐Yuen Tseng, N. K. Sahoo et al.
1 citations
Journal of Applied Physics
Advanced Memory and Neural Computing
0.73
article

Metal free all oxide SnOx/HfOx bilayer transristor synapse for neuromorphic computing

Asutosh Patnaik, Debashis Panda, Tseung‐Yuen Tseng, N. K. Sahoo, Ping‐Xing Chen
article en
1 citations

Abstract

Developing flexible and transparent memristors for emulating biological activities aligns with the growing demand for sustainable technologies in electronics. This paper presents the development and characterization of transparent memristors (transristors) on a flexible substrate, utilizing a structure of ITO/SnOx/HfOx/ITO/PEN. Hafnium oxide (HfOx) and tin oxide (SnOx) films are sequentially RF sputtered onto an indium doped tin oxide (ITO) bottom electrode, with polyethylene naphthalate serving as the flexible substrate. Then, an ITO top electrode is sputtered onto the SnOx layer using a shadow mask. Samples with varying thicknesses of HfOx and SnOx were prepared to optimize the device configuration. Electrical switching and synaptic characteristics of these samples were measured at room temperature, with a positive voltage applied to the top electrode and a negative voltage to the bottom electrode. This study identifies a configuration with 35 nm SnOx and 6 nm HfOx as the most effective, exhibiting excellent bipolar switching properties. Notably, it demonstrates low set/reset voltages of 1.3 and −1.6 V, with a compliance current of 100 μA. X-ray photoelectron spectroscopy was employed to assess the concentration of oxygen vacancies in the films. The device also shows the highest endurance up to 104 cycles, long-term potentiation/depression characteristics over 350 cycles, a good nonlinearity value of 1.53 (potentiation)/1.46 (depression), and 100% pattern recognition accuracy at just 14 iterations. Multi-state resistive switching characteristics were also explored. Obtained characteristics reveal that the optimized device could serve as a flexible component in making artificial synapses.

Journal of Applied PhysicsVol. 137(11)
National Yang Ming Chiao Tung University (TW), Global University (LB), Berhampur University (IN)
Science and Engineering Research Board, Board of Research in Nuclear Sciences
Openalex Percentile: Top 30%
Advanced Memory and Neural Computing
0.73
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