Memristive Properties and Synaptic Plasticity of Iodobismuthates: Handwritten Character Recognition and Detection of Vocalizations of Trichosurus Vulpecula in a Physical Reservoir Computer
Year: 2025
Type: conference-paper
Abstract: This work explores the structure-property-function relationship in low-dimensional halobismuthates incorporating various organic cations and halides ($\mathrm{I}^{-}, \text{Br}^{-},\ \text{Cl}^{-}$), with a focus on their application in the physical reservoir computing. Structural variation driven by anionic composition was correlated with semiconducting behaviour through experimental and Density Functional Theory (DFT) analyses. Memristive devices based on bismuth iodide complexes exhibited analog plasticity and nonlinear dynamics essential for neuromorphic function. Integrated into multiterminal architectures, these materials performed benchmark tasks-including MNIST classification and raw signal recognition—without preprocessing or trainable layers. The results demonstrate the feasibility of sustainable hardware-level reservoir computing using bismuth-based memristors).
Source: CAS proceedings
Authors: Ewelina Cechosz, Gisya Abdi, Marlena Gryl, Ahmet Karacali, Alif Syafiq Kamarol Zaman, Andrzej Sławek, Hirofumi Tanaka, Konrad Szaciłowski
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Award: G1105811034
OpenAlex ID: W4415969227
