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This paper presents a novel silicon-based piezoresistive pressure sensor composed of a silicon layer with sensing elements and a glass cover for hermetic packaging. Unlike conventional designs, this study employs numerical simulation to analyze the influence of varying roughness levels of the sensitive membrane on the sensor's output response. Simulation results demonstrate that pressure sensors with smoother sensitive membranes exhibit superior performance in terms of sensitivity (5.07 mV/V/MPa), linearity (0.67% FS), hysteresis (0.88% FS), and repeatability (0.75% FS). Furthermore, an optimized process for controlling membrane roughness was achieved by adjusting the concentration of the etchant solution. Experimental results reveal that a membrane roughness of 35.37 nm was attained under conditions of 80 °C and 25 wt% TMAH. Additionally, the fabrication process of this piezoresistive pressure sensor was significantly simplified and cost-effective due to the adoption of a backside wet etching technique. The fabricated sensor demonstrates excellent performance metrics, including a sensitivity of 5.07 mV/V/MPa, a full-scale (FS) output of 101.42 mV, a hysteresis of 0.88% FS, a repeatability of 0.75% FS, and a nonlinearity of 0.67% FS. These results indicate that the proposed sensor is a promising tool for precise pressure measurement applications, offering both high performance and cost efficiency. This study not only advances the understanding of the impact of membrane roughness on sensor performance but also provides a practical and scalable fabrication approach for piezoresistive pressure sensors.
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http://dx.doi.org/10.3390/mi16050516 | DOI Listing |
Phys Chem Chem Phys
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Shock Wave Research Laboratory, Department of Physics, Abdul Kalam Research Center, Sacred Heart College (Autonomous), affiliated to Thiruvalluvar University, Tirupattur, Tamil Nadu, 635 601, India.
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Department of Maxillofacial Orthognathics, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan.
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View Article and Find Full Text PDFJ Colloid Interface Sci
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State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China; Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.. Electronic address:
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View Article and Find Full Text PDFNanomicro Lett
September 2025
Nanomaterials & System Lab, Major of Mechatronics Engineering, Faculty of Applied Energy System, Jeju National University, Jeju, 63243, Republic of Korea.
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring, clinical diagnosis, and robotic applications. Nevertheless, it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility, adhesion, self-healing, and environmental robustness with excellent sensing metrics. Herein, we report a multifunctional, anti-freezing, self-adhesive, and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes (CoN CNT) embedded in a polyvinyl alcohol-gelatin (PVA/GLE) matrix.
View Article and Find Full Text PDFNMR Biomed
October 2025
High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
The human kidneys play a pivotal role in regulating blood pressure, water, and salt homeostasis, but assessment of renal function typically requires invasive methods. Deuterium metabolic imaging (DMI) is a novel, noninvasive technique for mapping tissue-specific uptake and metabolism of deuterium-labeled tracers. This study evaluates the feasibility of renal DMI at 7-Tesla (7T) to track deuterium-labeled tracers with high spatial and temporal resolution, aiming to establish a foundation for potential clinical applications in the noninvasive investigation of renal physiology and pathophysiology.
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