HfO<sub>2</sub> Memristor-Based Flexible Radio Frequency Switches
Flexible and wearable electronics are experiencing rapid growth due to the increasing demand for multifunctional, lightweight, and portable devices. However, the growing demands of interactive applications driven by the rise of AI reveal the inadequate connectivity of current connection technologies. In this work, we successfully leverage memristive technology to develop a flexible radio frequency (RF) switch, optimized for 6G-compatible communication systems and adaptable to flexible applications. The flexible RF switch demonstrates a low insertion loss (2 dB) and a cutoff frequency exceeding 840 GHz, and performance metrics are maintained after 10<sup>6</sup> switching cycles and 2500 mechanical bending cycles, showing excellent reliability and robustness. Furthermore, the RF switch is fully integrable with a photolithography-processable polyimide (PSPI) substrate, enabling efficient 2.5D integration with other RF components, such as RF antennas and interconnects. This technology holds significant promise to advance 6G communications in flexible electronics, offering a scalable solution for high-speed data transmission in next-generation wearable devices.
Authors
- Shih-Chieh Chen
- Yun-Chien Tseng
- Chao-Hsin Chien
- Eng Keong Ho
- Yu-Tao Yang (ORCID: https://orcid.org/0000-0003-2313-7790)
- Der‐Hsien Lien (ORCID: https://orcid.org/0000-0001-6774-2074)
- Jyun-Sian Chih
- Hsien-Yang Liu (ORCID: https://orcid.org/0009-0003-3237-5237)
- Chun-Hsiao Kuan
- Tsung-Te Chou (ORCID: https://orcid.org/0009-0001-2953-7974)
- Kun-Dong Chiou
- Po‐Wei Huang (ORCID: https://orcid.org/0000-0002-3130-1354)
- Chien‐Nan Kuo (ORCID: https://orcid.org/0000-0001-7479-717X)
- Yu‐Ting Cheng (ORCID: https://orcid.org/0000-0003-1191-8979)
- Chien‐Wei Chen
- Yao-Wun Jhang
Institutions
- National Yang Ming Chiao Tung University (TW)
- National Institutes of Applied Research (TW)
Publication Details
- Journal
- ACS Nano
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1021/acsnano.4c11846
- Citations
- 14
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.92
Funders
- Semiconductor Research Corporation
- Ministry of Education of the People's Republic of China
- Taiwan Semiconductor Manufacturing Company
- Ministry of Education, India
- National Science and Technology Council