Ultralow-Power Circuit and Sensing Applications Based on Subthermionic Threshold Switching Transistors
The most recent breakthrough in state-of-the-art electronics and optoelectronics involves the adoption of steep-slope field-effect transistors (FETs), promoting sub-60 mV/dec subthreshold swing (SS) at ambient temperature, effectively overcoming "Boltzmann limit" to minimize power consumption. Here, a series integration of nanoscale copper-based resistive-filamentary threshold switch (TS) with the IGZO channel-based FET is used to develop a TS-FET, in which the turn-on characteristics exhibit an abrupt transition over five decades, with an extremely low SS of 7 mV/dec, a high on/off ratio (>10<sup>9</sup>), and ultralow leakage current (40-fold decrease), ensuring excellent repeatability and device yield. Unlike previous device-centric studies, this work highlights potential circuit applications (logic-inverter, pulse-sensor amplification, and photodetector) based on TS-FET. The sharp transition behavior of TS-FET enables the establishment of logic inverters with a high voltage gain of ≈800, with a circuit-level demonstration achieving a bias-independent record-high intrinsic gain (>1000). A wearable pulse sensor integrated with an amplifier circuit ensured the precise amplification of electrophysical signals by 450 times. In addition, the application of a TS-FET-based photodetector features high responsivity (1.08 × 10<sup>4</sup> mA/W) and detectivity (1.03 × 10<sup>20</sup> Jones). The low-power strategy of TS-FETs is promising for the development of energy-efficient integrated circuits alongside sensor-interconnected biomedical applications in wearable technology.
Authors
- Arman Kadyrov (ORCID: https://orcid.org/0009-0008-9777-8770)
- Junseong Bae (ORCID: https://orcid.org/0000-0002-9735-4504)
- Gisung Lee
- Batyrbek Alimkhanuly
- Shubham Patil (ORCID: https://orcid.org/0000-0001-6535-5919)
- Anupom Devnath
- Seunghyun Lee (ORCID: https://orcid.org/0000-0002-4701-2856)
Institutions
- Kyung Hee University (KR)
- Convergence (US)
Publication Details
- Journal
- ACS Nano
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1021/acsnano.4c08650
- Citations
- 5
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.04
Funders
- Ministry of Trade, Industry and Energy
- National Research Foundation of Korea