Hysteresis in Perovskite Devices: Understanding the Abrupt Resistive Switching Mechanism

Halide perovskite devices exhibit diverse current-voltage hysteresis behaviors, driven by distinct mechanisms that can enhance or hinder performance, making their understanding crucial. Among these, abrupt switching is particularly relevant for memristive operation and reverse-bias breakdown in solar cells. In this work, we identify four distinct hysteresis responses: capacitive, inductive, hysteresis-free, and abrupt switching. All four behaviors are clearly observed via cyclic voltammetry in a simple perovskite device with silver contacts. Real-time photoluminescence microscopy shows that continuous bias and illumination progressively modify the perovskite-electrode interface, transforming inductive into hysteresis-free behavior and supporting its interfacial origin. Further stress leads to filament formation, with abrupt switching occurring only when a filament bridges the electrodes, forming a reversible short circuit. This switching arises from dynamic contact at the filament-electrode interface. Conductive AFM and electron microscopy reveal that the filaments are highly conductive and composed of metallic silver. Transient and impedance measurements effectively differentiate the hysteresis modes. Similar responses are found in gold-contacted devices, though abrupt switching is restricted to nanometer-scale gaps between the electrodes, suggesting the formation of smaller, less stable filaments due to the lower reactivity of gold. These findings provide valuable insights for advancing switching and understanding hysteresis in perovskite-based devices.

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Publication Details

Journal
ACS Energy Letters
Published
2025-07-24
DOI
https://doi.org/10.1021/acsenergylett.5c01556
Citations
5
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
3.65

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article

Hysteresis in Perovskite Devices: Understanding the Abrupt Resistive Switching Mechanism

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5 citations
ACS Energy Letters
Advanced Memory and Neural Computing
3.65
article

Hysteresis in Perovskite Devices: Understanding the Abrupt Resistive Switching Mechanism

Esther Alarcón‐Lladó, Bruno Ehrler, Yorick Bleiji, Jeroen J. de Boer, Agustín O. Alvarez, Lars Sonneveld
article en
5 citations

Abstract

Halide perovskite devices exhibit diverse current-voltage hysteresis behaviors, driven by distinct mechanisms that can enhance or hinder performance, making their understanding crucial. Among these, abrupt switching is particularly relevant for memristive operation and reverse-bias breakdown in solar cells. In this work, we identify four distinct hysteresis responses: capacitive, inductive, hysteresis-free, and abrupt switching. All four behaviors are clearly observed via cyclic voltammetry in a simple perovskite device with silver contacts. Real-time photoluminescence microscopy shows that continuous bias and illumination progressively modify the perovskite-electrode interface, transforming inductive into hysteresis-free behavior and supporting its interfacial origin. Further stress leads to filament formation, with abrupt switching occurring only when a filament bridges the electrodes, forming a reversible short circuit. This switching arises from dynamic contact at the filament-electrode interface. Conductive AFM and electron microscopy reveal that the filaments are highly conductive and composed of metallic silver. Transient and impedance measurements effectively differentiate the hysteresis modes. Similar responses are found in gold-contacted devices, though abrupt switching is restricted to nanometer-scale gaps between the electrodes, suggesting the formation of smaller, less stable filaments due to the lower reactivity of gold. These findings provide valuable insights for advancing switching and understanding hysteresis in perovskite-based devices.

ACS Energy LettersVol. 10(8)
Institute for Atomic and Molecular Physics (NL), Institute for Molecular Science (JP), Vrije Universiteit Amsterdam (NL), University of Amsterdam (NL)
H2020 European Research Council
Openalex Percentile: Top 7%
Advanced Memory and Neural Computing
3.65
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