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<p>Memristor technology offers a promising route toward energy-efficient computing but faces challenges including resistance drift, variability, and the need for electroforming. Filamentary resistive random-access memory, one of the most studied memristive platforms, typically requires a high-voltage electroforming step to initiate conductive filaments, leading to increased power overhead and reduced endurance. Here we report HfO<sub>2</sub>-based forming-free memristive devices (PdNeuRAM) that operate at low voltages, support multi-bit functionality, and exhibit reduced variability. Through combined electrical and materials characterization, we identify a Pd-O-Hf interfacial configuration that lowers oxygen-vacancy formation and migration barriers, creating a dense network of shallow defect states. Together with a Ti top electrode acting as an oxygen reservoir and an ultrathin (5 nm) HfO<sub>2</sub> layer, this interfacial engineering enables charge redistribution at room temperature and eliminates the need for electroforming. The fabricated devices provide tunable resistance states and reduce programming and read energy by 43% and 38%, respectively, in spiking neural network inference tasks. These results provide mechanistic insight into forming-free resistive switching and demonstrate the potential of Pd/HfO<sub>2</sub> devices for energy-efficient neuromorphic computing.</p>

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PdNeuRAM: forming-free, multi-bit Pd/HfO2 ReRAM for energy-efficient neuromorphic computing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月30日

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  • Erbing Hua,
  • Theofilos Spyrou,
  • Majid Ahmadi,
  • Abdul Momin Syed,
  • Hanzhi Xun,
  • Laurentiu Braic,
  • Nimer Wehbe,
  • Ewout van der Veer,
  • Nazek Elatab,
  • Anteneh Gebregiorgis,
  • Georgi Gaydadjiev,
  • Beatriz Noheda,
  • Said Hamdioui,
  • Ryoichi Ishihara,
  • Heba Abunahla

摘要

Memristor technology offers a promising route toward energy-efficient computing but faces challenges including resistance drift, variability, and the need for electroforming. Filamentary resistive random-access memory, one of the most studied memristive platforms, typically requires a high-voltage electroforming step to initiate conductive filaments, leading to increased power overhead and reduced endurance. Here we report HfO2-based forming-free memristive devices (PdNeuRAM) that operate at low voltages, support multi-bit functionality, and exhibit reduced variability. Through combined electrical and materials characterization, we identify a Pd-O-Hf interfacial configuration that lowers oxygen-vacancy formation and migration barriers, creating a dense network of shallow defect states. Together with a Ti top electrode acting as an oxygen reservoir and an ultrathin (5 nm) HfO2 layer, this interfacial engineering enables charge redistribution at room temperature and eliminates the need for electroforming. The fabricated devices provide tunable resistance states and reduce programming and read energy by 43% and 38%, respectively, in spiking neural network inference tasks. These results provide mechanistic insight into forming-free resistive switching and demonstrate the potential of Pd/HfO2 devices for energy-efficient neuromorphic computing.