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Flexible pressure sensors have been widely applied in wearable devices, e-skin, and the new generation of robots. However, most of the current sensors use connecting wires for energy supply and signal transmission, which presents an obstacle for application scenarios requiring long endurance and large movement, especially. Flexible sensors combined with wireless technology is a promising research field for realizing efficient state sensing in an active state. Here, we designed and fabricated a soft wireless passive pressure sensor, with a fully flexible Ecoflex substrate and a multi-walled carbon nanotube/polydimethylsiloxane (MWCNT/PDMS) bilayer pyramid dielectric structure. Based on the principle of the radio-frequency resonator, the device achieved pressure sensing with a changeable capacitance. Subsequently, the effect of the pyramid density was simulated by the finite element method to improve the sensitivity. With one-step embossing and spin-coating methods, the fabricated sensor had an optimized sensitivity of 14.25 MHz/kPa in the low-pressure range. The sensor exhibited the potential for application in limb bending monitoring, thus demonstrating its value for long-term wireless clinical monitoring. Moreover, the radio frequency coupling field can be affected by approaching objects, which provides a possible route for realizing non-contact sensing in applications such as pre-collision warning.
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http://dx.doi.org/10.3390/mi13030404 | DOI Listing |
Radiother Oncol
September 2025
Canadian Cancer Trials Group, Queen's University, Kingston, ON, Canada.
Purpose/objectives: Low Dose-Rate Brachytherapy (LDR) and High Dose-Rate Brachytherapy (HDR) are options for favorable risk prostate cancer. We hypothesized that HDR provides comparable disease control with less urinary toxicity. Primary objective was to determine prostate cancer control at 48 months, defined as a PSA < 0.
View Article and Find Full Text PDFPhys Rev Lett
August 2025
RIKEN Center for Quantum Computing, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
We present a method for probing the quantum capacitance associated with the Rydberg transition of surface electrons on liquid helium using radio-frequency (rf) reflectometry. Resonant microwave excitation of the Rydberg transition induces a redistribution of image charges on capacitively coupled electrodes, giving rise to a quantum capacitance originating from adiabatic state transitions and the finite curvature of the energy bands. By applying frequency-modulated resonant microwaves to drive the Rydberg transition, we systematically measured a capacitance sensitivity of 0.
View Article and Find Full Text PDFRev Sci Instrum
September 2025
International Center for Quantum Materials, School of Physics, Peking University, Beijing 100871, China.
Radio frequency (RF) control is a key technique in cold atom experiments. We present a compact and efficient RF circuit based on a capacitive transformer network, where a low-frequency coil operating up to 30 MHz serves as both an intrinsic inductor and a power-sharing element. The design enables high current delivery and flexible impedance matching across a wide frequency range.
View Article and Find Full Text PDFSmall
September 2025
Institute of Thin Film Physics and Applications, Shenzhen Key Laboratory of Advanced Thin Films and Applications, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, State Key Laboratory of Radio Frequency Heterogeneous Integration, College of Physic
Antimony selenide (SbSe), a narrow-bandgap semiconductor with strong light absorption, exhibits photoresponse up to ≈1050 nm due to its intrinsic 1.15 eV bandgap. To extend detection into the near-infrared (NIR, 700-1350 nm), Bi-alloyed (BiSb)Se is developed via vacuum sputtering and postselenization.
View Article and Find Full Text PDFComput Methods Biomech Biomed Engin
September 2025
Institute of Radio Physics and Electronics, University of Calcutta, Kolkata, India.
Parkinson's disease (PD) is a neurodegenerative condition that impairs motor functions. Accurate and early diagnosis is essential for enhancing well-being and ensuring effective treatment. This study proposes a deep learning-based approach for PD detection using EEG signals.
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