Memristor technology shows great promise for energy-efficient computing, yet it grapples with challenges like resistance drift and inherent variability. For filamentary Resistive RAM (ReRAM), one of the most investigated types of memristive devices, the expensive electroforming step required to create conductive pathways results in increased power and area overheads and reduced endurance. In this study, we present novel HfO2-based forming-free ReRAM devices, PdNeuRAM, that operate at low voltages, support multi-bit functionality, and display reduced variability. Through a deep understanding and comprehensive material characterization, we discover the key process that allows this unique behavior: a Pd-O-Hf configuration that capitalizes on Pd innate affinity for integrating into HfO2. This structure actively facilitates charge redistribution at room temperature, effectively eliminating the need for electroforming. Moreover, the fabricated ReRAM device provides tunable resistance states for dense memory and reduces programming and reading energy by 43% and 73%, respectively, using spiking neural networks (SNN). This study reveals novel mechanistic insights and delineates a strategic roadmap for the realization of power-efficient and cost-effective ReRAM devices.
@article{arxiv.2505.22789,
title = {PdNeuRAM: forming-free, multi-bit Pd/HfO2 ReRAM for energy-efficient neuromorphic computing},
author = {Erbing Hua and Theofilos Spyrou and Majid Ahmadi and Abdul Momin Syed and Hanzhi Xun and Laurentiu Braic and Ewout van der Veer and Nazek Elatab and Anteneh Gebregiorgis and Georgi Gaydadjiev and Beatriz Noheda and Said Hamdioui and Ryoichi Ishihara and Heba Abunahla},
journal= {arXiv preprint arXiv:2505.22789},
year = {2026}
}
Comments
32 pages, 6 figures in main text and 7 figures in supporting information