Investigation of Electron Transport Layer Influence on Asymmetric Bipolar Switching in Transparent BST-Based RRAM Devices
Ba<sub>0.6</sub>Sr<sub>0.4</sub>TiO<sub>3</sub> (BST) thin films were deposited on ITO substrates via rf magnetron sputtering, followed by structural and morphological characterization using XRD and FE-SEM. Metal-insulator-metal (MIM) RRAM devices were fabricated by depositing Al top electrodes, and their electrical properties were examined through <i>I-V</i> measurements. The optimized BST films deposited at 40% oxygen concentration exhibited stable resistive switching, with an operating voltage of 3 V, an on/off ratio of 1, and a leakage current of 10<sup>-8</sup> A. After rapid thermal annealing at 500 °C, the on/off ratio improved to 2 but leakage increased to 10<sup>-3</sup> A. Incorporating an electron transport layer (ETL) effectively suppressed the leakage current to 10<sup>-5</sup> A while maintaining the on/off ratio at 2. Moreover, a transition from bipolar to unipolar switching was observed at higher oxygen concentration (60%). These results highlight the role of ETLs in reducing leakage and stabilizing switching characteristics, providing guidance for the development of transparent, low-power, and high-reliability BST-based RRAM devices. This study aims to investigate the role of Ba<sub>0.6</sub>Sr<sub>0.4</sub>TiO<sub>3</sub> (BST) ferroelectric oxide as a functional switching layer in resistive random-access memory (RRAM) and to evaluate how interface engineering using an electron transport layer (ETL) can improve resistive switching stability, leakage suppression, and device reliability.
Authors
- Chien-Min Cheng
- Kai-Huang Chen (ORCID: https://orcid.org/0000-0003-2367-5900)
- Yao‐Chin Wang (ORCID: https://orcid.org/0000-0002-0094-8016)
- Ming‐Cheng Kao (ORCID: https://orcid.org/0000-0001-6795-5774)
- Hsin-Chin Chen
- Weimin Xu (ORCID: https://orcid.org/0000-0001-9815-2528)
Institutions
- Chaoyang University of Technology (TW)
- Cheng Shiu University (TW)
- Southern Taiwan University of Science and Technology (TW)
Publication Details
- Journal
- Micromachines
- Published
- 2025-11-20
- DOI
- https://doi.org/10.3390/mi16111302
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.73
Funders
- National Science Council
- National Science and Technology Council