journal article·2026

Statistical variability analysis of resistive switching in lead-free double perovskite flexible memristors

Susmita Das, Prabir Kumar Haldar, Pranab Kumar Sarkar

Nanoscale· Volume 18· Issue 11
Publisher page

Abstract

Inorganic double halide perovskites are considered as promising materials for resistive switching (RS) applications due to their superior functional stability. In this work, an inorganic cesium tin(IV) iodide (Cs2SnI6) perovskite has been incorporated as an active layer in an Ag/Cs2SnI6/ITO-PET flexible device, which exhibits excellent bipolar RS characteristics at room temperature. The RS mechanism was investigated through current versus voltage measurements for 100 consecutive cycles, during which no severe degradation was observed, attributed to the device's uniformity and reproducibility. The device also exhibits a remarkably high on/off ratio (∼103), significant endurance (>106 times), a long retention time (∼104 s), and uniform switching features. We investigated variability in resistive random access memory (RRAM) devices using advanced numerical techniques to process the experimental data. Variability depends on the adopted numerical technique to achieve the set and reset voltages. We used cumulative distribution functions (CDFs) to analyze the cycle-to-cycle (C/C) variability of set and reset voltages. Furthermore, the current-voltage (I-V) characteristics are investigated under various bending conditions to assess the device's mechanical robustness and electrical reliability. No such significant difference is observed between low resistance state (LRS) and high resistance state (HRS) currents under without bending (W/O), compressive bending (C/B), and tensile bending (T/B) conditions. The conductive filament (CF) model explains the mechanism behind resistive switching, which is based on the migration of halide ions and their corresponding vacancies inside perovskite layers. These overall findings of the Ag/Cs2SnI6/ITO-PET device will pave the way for exploring double perovskite materials in next-generation low-power consumption NVM devices.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Perovskite Materials and Applications · Conducting polymers and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Physics, Cooch Behar Panchanan Barma University, Cooch Behar 736101, India

Department of Applied Science and Humanities, Assam University, Silchar 788011, Assam, India

Funding

Science and Engineering Research Board

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