Issue 5, 2024

Resistive switching in benzylammonium-based Ruddlesden–Popper layered hybrid perovskites for non-volatile memory and neuromorphic computing

Abstract

Artificial synapses based on resistive switching have emerged as a promising avenue for brain-inspired computing. Hybrid metal halide perovskites have provided the opportunity to simplify resistive switching device architectures due to their mixed electronic–ionic conduction, yet the instabilities under operating conditions compromise their reliability. We demonstrate reliable resistive switching and synaptic behaviour in layered benzylammonium (BzA) based halide perovskites of (BzA)2PbX4 composition (X = Br, I), showing a transformation of the resistive switching from digital to analog with the change of the halide anion. While (BzA)2PbI4 devices demonstrate gradual set and reset processes with reduced power consumption, the (BzA)2PbBr4 system features a more abrupt switching behaviour. Moreover, the iodide-based system displays excellent retention and endurance, whereas bromide-based devices achieve a superior on/off ratio. The underlying mechanism is attributed to the migration of halide ions and the formation of halide vacancy conductive filaments. As a result, the corresponding devices emulate synaptic characteristics, demonstrating the potential for neuromorphic computing. Such resistive switching and synaptic behaviour highlight (BzA)2PbX4 perovskites as promising candidates for non-volatile memory and neuromorphic computing.

Graphical abstract: Resistive switching in benzylammonium-based Ruddlesden–Popper layered hybrid perovskites for non-volatile memory and neuromorphic computing

Supplementary files

Article information

Article type
Communication
Submitted
29 Aug. 2023
Accepted
11 Dec. 2023
First published
03 Janv. 2024
This article is Open Access
Creative Commons BY-NC license

Mater. Adv., 2024,5, 1880-1886

Resistive switching in benzylammonium-based Ruddlesden–Popper layered hybrid perovskites for non-volatile memory and neuromorphic computing

M. M. Ganaie, G. Bravetti, S. Sahu, M. Kumar and J. V. Milić, Mater. Adv., 2024, 5, 1880 DOI: 10.1039/D3MA00618B

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