Neuromorphic Perovskite Based Device with Fast Relearning Functionality
Shahzada Ahmad a f, Dani S. Assi b c, M. P.U. Haris a e, Vaithinathan Karthikeyan b c, Samrana Kazim a d f, Vellaisamy A. L. Roy b c
a 1BCMaterials, Basque Center for Materials, Applications, and Nanostructures, UPV/EHU Science Park
b Electronics and Nanoscale Engineering, James Watt School of Engineering, University of Glasgow
c School of Science and Technology, Hong Kong Metropolitan University
d 4Materials Physics Center, CSIC-UPV/EHU
e King Fahd University of Petroleum and Minerals
f IKERBASQUE, Basque Foundation for Science, 48013 Bilbao, Vizcaya, España, Bilbao, Spain
Proceedings of MATSUS Fall 2024 Conference (MATSUSFall24)
#NeuroMorph - Engineering of Semiconductors for Neuromorphic Devices
Lausanne, Switzerland, 2024 November 12th - 15th
Organizers: Shahzada Ahmad and Samrana Kazim
Oral, Shahzada Ahmad, presentation 410
Publication date: 28th August 2024

In order to reduce energy consumption, we aim to explore electronic materials beyond silicon for memristor and neuromorphic devices. Halide perovskites have emerged as a choice semiconductor due to their defect tolerance, low defect formation energies, compositional and optical bandgap tunability, and light/electric pulse-induced stimulation possibilities. [1,2] The resistance depends on the applied electrical signals, and this makes them potential candidates for future data storage and neuromorphic computing. The optoelectronic and carrier transport merits allow mimicking the characteristics of neurons and synaptic functions in the human brain. Methylammonium lead triiodide showed synaptic behaviors of photonic and electronic stimulations, and due to the intrinsic phase transition, limited efforts are made to study neuromorphic properties. We developed CsFAPbI3 microcrystals in grams quantity and studied CsFAPbI3-based memristive neuromorphic devices that can switch at low power and show larger endurance. [1] The fabricated memristors also showed an ultra-high paired-pulse facilitation index with applied electric stimuli pulse, and the short-term to long-term memory transition consumes ultra-low energy with long relaxation times. Our results suggest low-power neuromorphic devices that are synchronic to the human brain's performance with faster learning and memorization processes.

Keywords: Perovskite, Passivation, Surface modification, defect density.

Work produced with the support of a 2023 Leonardo Grant for Scientific Research and Cultural Creation, BBVA Foundation. SA thank INTERACTION (PID2021-129085OB-I00) from the Spanish Ministry of Science and Innovation.

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