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.

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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

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article

Characterization of Nonvolatile Switches Based on 2-D Multilayered hBN Memristors for High-Frequency Applications

Pedro de Paco, Yaqing Shen, Mario Lanza, Jordi Verdú et al.
IEEE Microwave and Wireless Technology Letters
Advanced Memory and Neural Computing
article

Characterization of Nonvolatile Switches Based on 2-D Multilayered hBN Memristors for High-Frequency Applications

Pedro de Paco, Yaqing Shen, Mario Lanza, Jordi Verdú, Sebastián Pazos, Tobías Amarilla
article en

Abstract

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.

IEEE Microwave and Wireless Technology LettersVol. 35(9)
National University of Singapore (SG), King Abdullah University of Science and Technology (SA)
Secretaría de Estado de Investigación, Desarrollo e Innovación
Affordable and clean energy
Openalex Percentile: Top 88%
Advanced Memory and Neural Computing
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