Electromagnetic Radiation Stimulated Learning in Perovskite Nickelates

Biological plasticity refers to the ability of synapses to strengthen or weaken over time. These adaptive properties play a fundamental role in learning and memory, spanning many orders of magnitude in timescales. Short-term plasticity (STP) arises from rapid correlative activity, while long-term plasticity (LTP) is governed by slower biochemical processes. Here, we investigate electromagnetically driven relaxation dynamics in perovskite nickelate thin films as an analogue of biological learning behaviors. By comparing radio frequency (RF), infrared (IR), visible, and ultraviolet (UV) radiation as stimuli, we find that RF excitation primarily induces STP, while visible and IR illumination lead to reversible relaxation on behavioral timescales. In contrast, UV illumination results in persistent, non-thermal changes in conductivity over extended timescales. Notably, UV-exposed nickelate films exhibit glass-like dynamics, characterized by stretched exponential relaxation and aging phenomena. The films display habituation to repeated stimuli, along with sensitization and spontaneous recovery under controlled environments. A minimal dynamical systems model captures key qualitative features of the UV-induced resistance changes. Our results demonstrate that electromagnetic frequency enables multi-timescale relaxation spanning nearly nine orders of magnitude, suggesting perovskite nickelates as promising platforms for adaptive optoelectronic hardware and for linking computational neuroscience with emerging quantum technologies.

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Publication Details

Journal
Advanced Science
Published
2026-06-12
DOI
https://doi.org/10.1002/advs.75984
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Electromagnetic Radiation Stimulated Learning in Perovskite Nickelates

Shriram Ramanathan, Ivan Seskar, Martin Mönnigmann, Ranjan Kumar Patel et al.
Advanced Science
Advanced Memory and Neural Computing
article

Electromagnetic Radiation Stimulated Learning in Perovskite Nickelates

Shriram Ramanathan, Ivan Seskar, Martin Mönnigmann, Ranjan Kumar Patel, Guangxin Ni, Kabir Zama, Matthew Smart, Ramya Eathirajan, Narayan Mandayam
article en

Abstract

Biological plasticity refers to the ability of synapses to strengthen or weaken over time. These adaptive properties play a fundamental role in learning and memory, spanning many orders of magnitude in timescales. Short-term plasticity (STP) arises from rapid correlative activity, while long-term plasticity (LTP) is governed by slower biochemical processes. Here, we investigate electromagnetically driven relaxation dynamics in perovskite nickelate thin films as an analogue of biological learning behaviors. By comparing radio frequency (RF), infrared (IR), visible, and ultraviolet (UV) radiation as stimuli, we find that RF excitation primarily induces STP, while visible and IR illumination lead to reversible relaxation on behavioral timescales. In contrast, UV illumination results in persistent, non-thermal changes in conductivity over extended timescales. Notably, UV-exposed nickelate films exhibit glass-like dynamics, characterized by stretched exponential relaxation and aging phenomena. The films display habituation to repeated stimuli, along with sensitization and spontaneous recovery under controlled environments. A minimal dynamical systems model captures key qualitative features of the UV-induced resistance changes. Our results demonstrate that electromagnetic frequency enables multi-timescale relaxation spanning nearly nine orders of magnitude, suggesting perovskite nickelates as promising platforms for adaptive optoelectronic hardware and for linking computational neuroscience with emerging quantum technologies.

Advanced Science
Rutgers, The State University of New Jersey (US), Florida State University (US), Princeton University (US), Environmental and Occupational Health Sciences Institute (US), National High Magnetic Field Laboratory (US), Ruhr University Bochum (DE)
National Science Foundation, U.S. Department of Energy, Air Force Office of Scientific Research
Openalex Percentile: Top 10%
Advanced Memory and Neural Computing
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