Publication date: 15th December 2025
Neuromorphic computing implemented with spiking neural networks (SNNs) using volatile threshold switching devices is a promising computing paradigm that may overcome future limitations of the von Neumann architecture. For the computation by dynamics and time new technologies for devices with high dynamics are required, for which volatile electrochemical memory (v-ECM), also known as diffusive memristor, is very promising [1,2]. v-ECM devices switch from the high-resistance to the low-resistance state when the voltage rises above the threshold voltage and automatically restores the high-resistance state after a relaxation time when the voltage falls below the holding voltage [3]. The advantage of v-ECMs compared to insulator-to-metal-based threshold switches is their extremely low leakage current and the low threshold voltages, while a drawback is the higher switching variability. We have investigated in detail the set kinetics and relaxation dynamics of v-ECM threshold switches based on analysis of the transient current in pulsed voltage measurements for Ag/HfO2/Pt crossbar devices made of 3 nm amorphous HfO2 by atomic layer deposition. The results show a clear correlation between the relaxation time and the operating parameters with reference to the set kinetics [4,5]. This is crucial for the application of v-ECM cells in neuromorphic circuits. There are several approaches to understand the physical origin of the relaxation behaviour, ranging from surface energy minimization [6] to the effect of electromotive force [7]. The presentation will summarize different approaches of device fabrication, physical understanding, and applications of v-ECM devices, also known as diffusive memristors. In addition, actual results based on integrate-and-fire circuits will be discussed.
This work was in part funded by the Federal Ministry of Research, Technology and Space (BMFTR, Germany) in the projects NEUROTEC II (Project No. 16ME0398K) and NeuroSys (Project No. 03ZU1106AB) and is based on the Juelich Aachen Research Alliance (JARA-FIT).
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