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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

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SnO₂-Based Memory Device with Filamentary Switching Mechanism for Advanced Data Storage and Computing.

Muhammad Ismail¹, Chandreswar Mahata¹, Myounggon Kang²

¹Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea.

Nanomaterials (Basel, Switzerland)

|September 28, 2023

Summary

This study introduces a novel tin oxide (SnO_x) memory device for neuromorphic computing. The device demonstrates excellent endurance, retention, and multilevel resistance states, mimicking synaptic functions for advanced AI applications.

Keywords:

Schottky emission multilevel resistance states neuromorphic system resistive switching tin oxide

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Gradient Echo Quantum Memory in Warm Atomic Vapor

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Published on: November 11, 2013

Area of Science:

Materials Science
Neuroscience
Computer Engineering

Background:

Neuromorphic computing aims to mimic the human brain's structure and function.
Developing efficient and reliable memory devices is crucial for neuromorphic systems.
Tin oxide (SnO_x) is a promising material for resistive switching memory applications.

Purpose of the Study:

To fabricate and characterize a Pt/TiN/SnO_x/Pt memory device for neuromorphic computing.
To investigate the role of the TiON interface layer in device operation.
To evaluate the device's performance in terms of endurance, retention, and synaptic behavior emulation.

Main Methods:

Fabrication of Pt/TiN/SnO_x/Pt memory devices using reactive sputtering.
Characterization of electrical properties, including endurance, retention, and resistance states.
Analysis of the filamentary switching mechanism based on oxygen vacancy concentration gradients.

Main Results:

The SnO_x-based device showed over 200 DC cycles, an ON/OFF ratio (>20), and 10⁴ s retention.
Low set (9.89%) and reset (3.2%) voltage variabilities were achieved.
The device successfully emulated synaptic behaviors, including long-term potentiation (LTP) and long-term depression (LTD).

Conclusions:

The Pt/TiN/SnO_x/Pt device exhibits excellent performance for neuromorphic computing applications.
The TiON interface layer facilitates oxygen vacancy migration, enabling reliable switching.
SnO_x-based devices hold significant potential for high-density data storage and advanced AI.