7‐Methylquinolinium Iodobismuthate Memristor: Exploring Plasticity and Memristive Properties for Digit Classification in Physical Reservoir Computing

This study explores 7‐methylquinolinium halobismuthates (I, Br, and Cl) with a focus on: (1) the impact of halide composition on their structural and semiconducting properties, and (2) their memristive behavior and plasticity for neuromorphic and reservoir computing. Crystallographic analysis reveals that halide substitution leads to the formation of low‐dimensional bismuth‐based frameworks. Optical bandgaps, measured via diffuse reflectance spectroscopy, correlate well with density functional theory calculations. Due to solubility constraints, only bismuth iodide complexes are integrated into electronic devices. Current–voltage measurements reveal pinched hysteresis loops, indicative of memristive behavior. Conductivity versus temperature analysis suggests both ionic and electronic conduction pathways. Given their ability to function as synaptic analogs, further tests on transient conductance (potentiation–depression) and spike‐time‐dependent plasticity are performed. The observed nonlinearity and fading memory characteristics highlight their potential for physical reservoir computing. To evaluate system‐level behavior, a device with 16 gold electrodes (1 input, 15 outputs) is fabricated on a silicon substrate coated with the target compound. The device is assessed through benchmark tasks including waveform generation, NARMA‐2, memory capacity, and noise response under DC/AC signals. Finally, the system demonstrates 82.26% accuracy in MNIST digit classification and 82% accuracy in spoken digit “2” recognition across six different speakers.