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

• Published in: Materials advances Vol. 5; no. 5; pp. 188 - 1886
• Main Authors: Ganaie, Mubashir M, Bravetti, Gianluca, Sahu, Satyajit, Kumar, Mahesh, Mili, Jovana V
• Format: Journal Article
• Language: English
• Published: England RSC 04.03.2024
• Subjects: Chemistry
• ISSN: 2633-5409; 2633-5409
• DOI: 10.1039/d3ma00618b

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) 2 PbX 4 composition (X = Br, I), showing a transformation of the resistive switching from digital to analog with the change of the halide anion. While (BzA) 2 PbI 4 devices demonstrate gradual set and reset processes with reduced power consumption, the (BzA) 2 PbBr 4 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) 2 PbX 4 perovskites as promising candidates for non-volatile memory and neuromorphic computing. Resistive switching with synaptic behaviour in layered benzylammonium-based Ruddlesden-Popper perovskites is demonstrated, with a transformation from digital to analog upon change of the halide anion, of potential interest to neuromorphic computing.