1. Optimization of the position of TaOx:N-based barrier layer in TaOx RRAM devices
- Author
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Pramod Ravindra, Maximilian Liehr, Rajas Mathkari, Karsten Beckmann, Natalya Tokranova, and Nathaniel Cady
- Subjects
neuromorphic computing ,resistive memories ,non-volatile memories ,tantalum oxide ,reliability ,Technology - Abstract
Resistive Random-Access Memory (RRAM) presents a transformative technology for diverse computing and artificial intelligence applications. However, variability in the high resistance state (HRS) has proved to be a challenge, impeding its widespread adoption. This study focuses on optimizing TaOx-based RRAMs by strategically placing a nitrogen-doped TaOx barrier-layer (BL) to mitigate variability in the HRS. Through comprehensive electrical characterization and measurements, we uncover the critical influence of BL positioning on HRS variability and identify the optimal location of the BL to achieve a 2x lowering of HRS variability as well as an expanded range of operating voltages. Incremental reset pulse amplitude measurements show that the TaOx:N maintains a low HRS variability even at higher operating voltages when the position of the BL is optimized. Our findings offer insights into stable and reliable RRAM operation, highlighting the potential of the proposed BL to enhance the functionality of TaOx-based RRAMs and elevate overall device performance.
- Published
- 2024
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