Grainy Cr <sub> <i>x</i> </sub> O <sub> <i>y</i> </sub> RRAM with Thermal Stability for Enabling Emerging Computing Applications

With the increasing demand for high-performance data processing, traditional silicon-based integrated circuits and emerging memory technologies are in urgent need as device miniaturization approached physical scaling limits. Resistive random-access memory (RRAM) is a promising candidate for neuromorphic computing and nonvolatile memory applications for its high scalability and low cost. With the rapid growth of AI workloads, ensuring device-level thermal robustness in non-volatile memory technologies has become increasingly critical. In this work, CrxOy-based RRAM devices were fabricated by localized prepatterned metal sources by chemical vapor deposition at 650 °C, as redistributed localized oxide deposition. The grainy oxide RRAM devices exhibit reliable bipolar switching with high uniformity and an ON/OFF ratio exceeding 104, while operated under 25 to 70 °C with an increased memory window attributed to the grainy structures with a thermal treatment process, which stabilized the filamentary-based resistive switching under high temperature. Linear conductance modulation with long-term potentiation (LTP), long-term depression (LTD), and training accuracy on the MNIST data set has resulted in 92.4% of pattern recognition accuracy. This study provides a unique technique in fabricating the active switching layer as CrxOy with improved operating temperature robustness, good memory window, and analog behaviors for future in-memory computing applications.

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Publication Details

Journal
ACS Applied Electronic Materials
Published
2025-12-12
DOI
https://doi.org/10.1021/acsaelm.5c02188
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46
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article

Grainy Cr x O y RRAM with Thermal Stability for Enabling Emerging Computing Applications

Ying‐Chen Chen, Zhipeng Lu, Sandhya Susarla, Mahir Manna et al.
2 citations
ACS Applied Electronic Materials
Advanced Memory and Neural Computing
1.46
article

Grainy Cr x O y RRAM with Thermal Stability for Enabling Emerging Computing Applications

Ying‐Chen Chen, Zhipeng Lu, Sandhya Susarla, Mahir Manna, Yujian Huang, Sai Prakash Maddineni, David J. Niedzwieck
article en
2 citations

Abstract

With the increasing demand for high-performance data processing, traditional silicon-based integrated circuits and emerging memory technologies are in urgent need as device miniaturization approached physical scaling limits. Resistive random-access memory (RRAM) is a promising candidate for neuromorphic computing and nonvolatile memory applications for its high scalability and low cost. With the rapid growth of AI workloads, ensuring device-level thermal robustness in non-volatile memory technologies has become increasingly critical. In this work, CrxOy-based RRAM devices were fabricated by localized prepatterned metal sources by chemical vapor deposition at 650 °C, as redistributed localized oxide deposition. The grainy oxide RRAM devices exhibit reliable bipolar switching with high uniformity and an ON/OFF ratio exceeding 104, while operated under 25 to 70 °C with an increased memory window attributed to the grainy structures with a thermal treatment process, which stabilized the filamentary-based resistive switching under high temperature. Linear conductance modulation with long-term potentiation (LTP), long-term depression (LTD), and training accuracy on the MNIST data set has resulted in 92.4% of pattern recognition accuracy. This study provides a unique technique in fabricating the active switching layer as CrxOy with improved operating temperature robustness, good memory window, and analog behaviors for future in-memory computing applications.

ACS Applied Electronic MaterialsVol. 7(24)
Newton Public Schools (US), Energy Concepts (United States) (US), Good Shepherd Rehabilitation (US), Arizona State University (US)
Openalex Percentile: Top 14%
Advanced Memory and Neural Computing
1.46
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