Electronic threshold switching of As-embedded SiO2 selectors: charged oxygen vacancy model
Sneak current issues in crossbar arrays of non-volatile memories can be effectively alleviated using threshold switching (TS)-based selectors. However, 1-selector-1-resistor integration requires coherence between the constituent materials and operational parameters of the two components. Here, we propose a highly coherent selector via in-depth investigation of the operation process of a fab-friendly As-SiO<sub>2</sub> selector unit. The structural and electrical characteristics of an As-embedded SiO<sub>2</sub> selector are analyzed, and the TS-on and -off operational mechanism is presented. Further, the critical control elements governing the selector operation are identified, including the electron charging into the oxygen vacancies in the SiO<sub>2</sub> matrix and energy band alignment between the As cluster and charged oxygen vacancies in SiO<sub>2</sub>. Consequently, practical control strategies for the TS behavior are proposed with a pulse scheme applicable to actual device operation. The proposed TS operational mechanism and analytical methodology can contribute to interpreting and integrating various memory/selector components, thereby advancing their operational and integrative research.
Authors
- S Park
- Jeong Hwan Song (ORCID: https://orcid.org/0000-0001-9284-2632)
- Soo Gil Kim
- Sang Gil Lee (ORCID: https://orcid.org/0000-0001-8127-8132)
- Jae Hyuck Jang (ORCID: https://orcid.org/0000-0002-9133-3286)
- Tae Jun Seok
- Hyun Seung Choi
- Byung Joon Choi (ORCID: https://orcid.org/0000-0003-1920-8162)
- Kyun Seong Dae (ORCID: https://orcid.org/0000-0001-5928-9855)
- Hye Rim Kim (ORCID: https://orcid.org/0000-0002-6857-8496)
- Tae Joo Park (ORCID: https://orcid.org/0000-0003-4641-2425)
- Tae Jung Ha
Institutions
- SK Group (United States) (US)
- Seoul National University of Science and Technology (KR)
- SK Group (South Korea) (KR)
- Korea Basic Science Institute (KR)
- Hanyang University (KR)
Publication Details
- Journal
- Nano Convergence
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1186/s40580-025-00480-7
- Citations
- 2
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.46