Synaptic and neuristor functionality in nickelate-based devices
Beatriz Noheda a b, Foelke Janssen a b, Ruben Hamming-Green a b, Laura Begón-Lours c
a Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 3, Groningen, 9747AG, The Netherlands.
b CogniGron - Groningen Cognitive Systems and Materials Center, University of Groningen, Netherlands
c 3D-ITET Integrated Systems Laboratory, ETH Zürich, Zürich, Switzerland
Proceedings of MATSUS Fall 2025 Conference (MATSUSFall25)
D.12 Materials and Methods for Neuromorphic Devices - #NeuroMorph
València, Spain, 2025 October 20th - 24th
Organizers: Shahzada Ahmad and Samrana Kazim
Invited Speaker, Beatriz Noheda, presentation 245
Publication date: 17th July 2025

Materials that undergo a metal-to-insulator phase transition are interesting as threshold, or volatile, memristors, and they are a crucial component in self-oscillating circuits that emulate the emission of action potentials by neurons. Rare-earth (RE) nickelates (RENiO3) show a metal-to-insulator transition at temperatures that can be tuned by different parameters, such as changing the RE cations, the strain state, film thickness or the oxygen vacancy content. Compared to other transition metal oxides, nickelates are especially interesting as memristive devices because of their endurance due to the robustness of the perovskite structure to high local temperatures and electric fields. In addition, it is known that the transport properties in transition metal (TM) oxides are largely dependent on the oxygen vacancy concentration. Thus, next to using the metal-insulator transition for artificial neurons, nickelates could also be used as synaptic devices driven by redox-reactions. However, this functionality is much less understood in the nickelates. Here we show that nickelates can behave as neuristors and as synapses and we discuss the mechanisms behind the different behaviours. In addition, we show that by interfacing nickelate thin films with ferroelectrics, it is possible to combine volatile and non-volatile memristive behaviour in one device and that such combination allows to select either the neuron or the synapse functionality by switching the ferroelectric polarization with the external bias[1]. Such devices could be used in reconfigurable networks, in which the devices can be dynamically reprogrammed to operate as memristors or spiking elements [2], for the implementation of sparse firing models in SNNs [3], or in oscillating neural networks that use memristive weights to couple the oscillations of individual elements [4]. These devices can also allow oscillators to be dynamically added or removed from a population.

.References

[1] R. Hamming Green. et al. Frontiers in Materials 11, 1356610, 2024
[2] R. John et al. Nat. Commun. 13, 2074, 2022
[3] G. Belec et al. Nat. Commun. 11, 3625, 2020
[4] P. Feketa et al. EEE Trans. Automatic Control 66, 3084, 2021

 

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