Ag/Ti/GeS/Ag Bidirectional Conductive-Bridge Selector with Low Turn-Off Latency, High Endurance, and Enhanced Switching Uniformity
To fulfill the demands of three-dimensional (3D) cross-point array architectures in embedded memories, selectors with low voltage and low off current with high selectivity are imperative. Selector devices with reliable pulsed switching performance at a logic-compatible voltage are crucial for achieving the ultimate goal of embedded 3D universal cross-point memory. While resistive ReRAM systems offer high density and ultralow power consumption, the 3D cross-point array introduces challenges such as sneak path currents during read and write operations. To overcome these problems, the selectors must be integrated into each cross-point cell. Although selector devices have been extensively studied, no singular material system has currently fulfilled all the vital needs for integration with nonvolatile memory. Here, we demonstrate an Ag-gated GeS-based bidirectional threshold switching selector device (Ag/Ti/GeS/Ag) with a highly uniform cycle-to-cycle and device-to-device switching performance. The device demonstrates highly uniform bidirectional threshold switching with promising attributes, including low threshold voltages (∼±0.22 V), low off current (∼pA), large selectivity window (∼3 × 108), an endurance of more than 109 cycles, and an on/off switching latency of 50 ns at 1 V pulsed operations. The simple material configuration of the selector device (Ag/Ti/GeS/Ag) facilitates easy fabrication, and its uniform switching performance makes it suitable for 3D cross-point integration with nonvolatile memory cells in a one-selector–one-resistor array configuration.
Authors
- Diing Shenp Ang (ORCID: https://orcid.org/0000-0002-8139-1984)
- Jongwan Jung (ORCID: https://orcid.org/0000-0002-1397-212X)
- Jiayi Li (ORCID: https://orcid.org/0000-0001-5016-4239)
- Haider Abbas (ORCID: https://orcid.org/0000-0003-4372-2639)
- Asif Ali (ORCID: https://orcid.org/0000-0002-7998-6962)
Institutions
- Nanyang Technological University (SG)
- Sejong University (KR)
Publication Details
- Journal
- ACS Applied Electronic Materials
- Published
- 2024-11-18
- DOI
- https://doi.org/10.1021/acsaelm.4c01392
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.21