Fully interface-controlled memristive devices for artificial synapse and neuromorphic computing

Sundar Kunwar; Aiping Chen

doi:10.1117/12.2682857

5 October 2023 Fully interface-controlled memristive devices for artificial synapse and neuromorphic computing

Sundar Kunwar, Aiping Chen

Proceedings Volume PC12651, Low-Dimensional Materials and Devices 2023; PC1265106 (2023) https://doi.org/10.1117/12.2682857
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States

Abstract

Resistive switching (RS) devices are key elements for future neuromorphic computing systems as they can emulate biological synaptic functions as well as short/long term memory effects. However, there are various challenges at the device level because of their operational stability, uniformity, and device-to-device variability, which are often originated by the switching mechanisms. Here, I will discuss on how fully interface controlled memristive devices can solve these issues. I will also discuss an example of Au/Nb:STO model system, which works based on interface charge trapping/detrapping and Schottky barrier modulation mechanism. Such device also shows analog RS switching characteristics with high stability, uniformity, and programmability, making it suitable for artificial synapse and neuromorphic computing.

Conference Presentation

Citation Download Citation

Sundar Kunwar and Aiping Chen "Fully interface-controlled memristive devices for artificial synapse and neuromorphic computing", Proc. SPIE PC12651, Low-Dimensional Materials and Devices 2023, PC1265106 (5 October 2023); https://doi.org/10.1117/12.2682857

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