Characterization of Nonvolatile Switches Based on 2-D Multilayered hBN Memristors for High-Frequency Applications
RF/microwave systems with large number of elements usually require switching elements with very small footprint, but providing very good electrical performance, low switching times, and good power-handling capabilities. In this sense, nonvolatile switches based on 2-D materials are emerging as a very suitable alternative to CMOS or MEMS-based technologies, mainly due to the capability of keeping a certain state with no energy consumption. In this article, different switches have been designed and fabricated using a multilayered structure based on 18 2-D hexagonal boron nitride (hBN) layers on three different substrates, high-resistivity silicon, quartz, and polycrystaline CVD diamond. The proposed device has been characterized in a frequency range up to 26.5GHz for these three substrates. The ON-state resistance and <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small>-state capacitance have been extracted from experimental data using an equivalent electric model being <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$28~\Omega $</tex-math> </inline-formula> and 22 fF, leading to insertion losses (ILs) better than 2.5 dB in case of CVD diamond, and isolation better than 10 dB in case of quartz, for the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small>- and <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small>-states, respectively.
Authors
- Pedro de Paco (ORCID: https://orcid.org/0000-0002-7628-7189)
- Yaqing Shen (ORCID: https://orcid.org/0000-0002-2325-5618)
- Mario Lanza (ORCID: https://orcid.org/0000-0003-4756-8632)
- Jordi Verdú (ORCID: https://orcid.org/0000-0002-2434-7012)
- Sebastián Pazos (ORCID: https://orcid.org/0000-0002-7354-4530)
- Tobías Amarilla (ORCID: https://orcid.org/0009-0002-4208-9237)
Institutions
- National University of Singapore (SG)
- King Abdullah University of Science and Technology (SA)
Publication Details
- Journal
- IEEE Microwave and Wireless Technology Letters
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1109/lmwt.2025.3576996
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Secretaría de Estado de Investigación, Desarrollo e Innovación