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◆ Small (Weinheim an der Bergstrasse, Germany)2026-09-10

Interface-Engineered Quaternary Halide Memristor for Synergistic Heterostructure-Driven Neuromorphic Functionality and Robust Artificial Learning.

Suvankar Poddar, Souvik Bhattacharjee, Pulok Das, Pranab Kumar Sarkar, Abhrajit Roy, Kalyan Kumar Chattopadhyay

原始摘要(英文原文)· Original abstract
Solution-processed memristors offer a scalable, cost-effective pathway for next-generation computing. The Rb4Ag2BiBr9 (RABB) based resistive random-access memory exhibits stable non-volatile memristive behavior with low operating voltage (∼1.7 V), robust endurance over ∼900 cycles, and extended data retention up to ∼ 5 × 10 3 s. Although, the pristine (Al/Rb4Ag2BiBr9/ITO/glass) device exhibits non-volatile switching with a high ON/OFF ratio but fail to produce gradual conductance modulation even after low bias application. Introducing the PEDOT:PSS layer through the modification of the interface (Al/Rb4Ag2BiBr9/PEDOT: PSS/ITO/glass), which can be switched among non-volatile switching and stable analog switching by adjusting voltage bias. In both cases, lattice incorporated Ag species and bromine vacancies govern resistive switching through an intrinsic mechanism rather than electrode driven metal injection. The PEDOT:PSS modified device effectively emulates a typical synaptic function, encompassing short- and long-term plasticity. The SNDP and SRDP decay characteristics are consistent with the Ebbinghaus and Wickelgren forgetting models. In addition, the device successfully demonstrates classical Pavlovian associative learning. The PEDOT:PSS modified device achieves moderate energy consumption highlighting a foundational proof-of-concept for PEDOT:PSS modified memristors. The PEDOT:PSS modified device-based ANN achieved ∼92% test accuracy for handwritten digit recognition utilising LTP/LTD data, accounting for cycle-to-cycle and device-to-device variations.
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Interface-Engineered Quaternary Halide Memristor for Synergistic Heterostructure-Driven Neuromorphic Functionality and Robust Artificial Learning. — 科研速览 Science Skim