Electrochemical Ag-based memristive devices as dynamical elements for neuromorphic computing
Stefano Brivio a, Mrinmoy Dutta a, Sabina Spiga a
a CNR-IMM Unit of Agrate Brianza, Via Camillo Olivetti, 2, Agrate Brianza, Italy
Proceedings of Neuronics Conference (Neuronics)
València, Spain, 2024 February 21st - 23rd
Organizers: Sabina Spiga and Juan Bisquert
Oral, Stefano Brivio, presentation 011
Publication date: 18th December 2023

The emulation of brain functionalities through solid state electronic systems requires billions of dynamical components reproducing the time varying properties of neurons, synapses, dendrites, etc. (as exemplified in TOC figure on the left). Memristor devices that rely their electrical operation on ion movement, interestingly akin to the chemistry of neural processes, hold the potential to make it possible thanks to their nanoscale dimension and short- and long- term memory of past electrical signals. Indeed, voltage pulses modify the inner layer of their metal/oxide/metal structure through formation of ionic conductive filaments (CFs) which short the electrodes and modify the device overall conductance. The fine understanding of conductance dynamics of memristive devices is therefore crucial for the final goal of an electronic brain.

In this framework, we characterized prototypical Pt/SiOx/Ag devices belonging to the class of electrochemical metallization memristors (the top right part of the TOC figure sketches the device structure and switching mechanism). Upon voltage application, Ag+ are injected from the electrode, migrate and deposit into a growing Ag CF that eventually shorts the two electrodes. As a result of these sequence of processes, the device reacts to a voltage pulse (grey area of the bottom right panel of the top figure) with an abrupt current upward jump (blue plot in the bottom right part of the TOC figure). The current jump is delayed by the moment of the voltage application by a certain time (called delay time), which is characteristic of the filament growth process. As soon as the voltage is released, the current gradually decreases, within a relaxation time, until a final drop to the pristine value occurs because of the atomic surface diffusion that disconnects the CF.

In the present work, we show that these timescales are at the base of the use of electrochemical devices for the emulation of neural functions. In particular, we identify prototypical dynamical features which can be useful for emulation of brain functions, as stimulated in response to sequence of pulses. We analyze such features as a function of the pulse sequence parameters (voltage, pulse width and inter-pulse intervals) so to draw a comprehensive picture of the device programming possibilities. We also describe the results with reference to the basic physical mechanism responsible for the CF growth and self-dissolution.

The work is partially supported by H2020 EU project MeM-Scales (grant agreement No. 871371).

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