Utilising ionic effects in halide perovskites
Nripan Mathews a
a School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798
Proceedings of MATSUS Fall 2026 Conference (MATSUSFall26)
A6 Halide Perovskites Beyond the Ideal Crystal: Chemistry, Interfaces, and Functional Heterostructures
Palma, Spain, 2026 October 26th - 30th
Organizers: Ahmed Abdelhady and Anna Moliterni
Invited Speaker, Nripan Mathews, presentation 261
Publication date: 22nd July 2026

Halide perovskites have significantly transformed the field of optoelectronics, enabling substantial advances in established technologies such as solar cells and light-emitting diodes (LEDs), as well as in emerging devices including memristors. A defining characteristic of these materials is their propensity for ionic migration. Although ion transport is typically regarded as a detrimental effect that contributes to the performance degradation of solar cells and LEDs, it is fundamentally the mechanism that facilitates resistive switching in memristive devices. Consequently, a comprehensive understanding of ionic transport and strategies for its precise control are critical for the rational design of high-performance devices.

This presentation will examine in detail the mechanisms of ionic migration in halide perovskites and outline approaches for modulating this behavior. To expedite progress in this area, high-throughput characterization methodologies have been developed to systematically evaluate ionic transport, thereby enabling precise control over ion dynamics and the realization of functional memristors across diverse applications. A range of device architectures and operational mechanisms—including switchable photovoltaics, photovoltaics exhibiting persistent photovoltage, bipolar photoconductor switching, color-tunable LEDs, and self-rectifying memristors—will be discussed as platforms for achieving novel functionalities. These advances further enable the development of sophisticated hardware security technologies, such as Physical Unclonable Functions (PUFs), as well as advanced neuromorphic systems, including in-sensor and reservoir computing.

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