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Record-Breaking Frequency of 44 GHz Based on the Higher Order Mode of Surface Acoustic Waves with LiNbO_(3)/SiO_(2)/SiC Heterostructures 被引量:1
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作者 Jian Zhou Dinghong Zhang +5 位作者 Yanghui Liu Fengling Zhuo Lirong Qian Honglang Li yong-qing fu Huigao Duan 《Engineering》 SCIE EI CAS CSCD 2023年第1期112-119,共8页
Surface acoustic wave (SAW) technology has been extensively explored for wireless communication, sensors, microfluidics, photonics, and quantum information processing. However, due to fabrication issues, the frequenci... Surface acoustic wave (SAW) technology has been extensively explored for wireless communication, sensors, microfluidics, photonics, and quantum information processing. However, due to fabrication issues, the frequencies of SAW devices are typically limited to within a few gigahertz, which severely restricts their applications in 5G communication, precision sensing, photonics, and quantum control. To solve this critical problem, we propose a hybrid strategy that integrates a nanomanufacturing process (i.e., nanolithography) with a LiNbO_(3)/SiO_(2)/SiC heterostructure and successfully achieve a record-breaking frequency of about 44 GHz for SAW devices, in addition to large electromechanical coupling coefficients of up to 15.7%. We perform a theoretical analysis and identify the guided higher order wave modes generated on these slow-on-fast SAW platforms. To demonstrate the superior sensing performance of the proposed ultra-high-frequency SAW platforms, we perform micro-mass sensing and obtain an extremely high sensitivity of approximately 33151.9 MHz·mm2·μg−1, which is about 1011 times higher than that of a conventional quartz crystal microbalance (QCM) and about 4000 times higher than that of a conventional SAW device with a frequency of 978 MHz. 展开更多
关键词 Ultra-high frequency SAW Higher order mode Hyper sensitive detection
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右侧喉不返神经2例 被引量:1
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作者 胡英男 万勇 +2 位作者 傅永清 黄捷 周剑 《中国现代医学杂志》 CAS 2019年第8期123-124,共2页
目的探讨喉不返神经(NRLN)的解剖特点及变异分型。方法回顾性分析本院收治2例NRLN的临床资料,并复习相关文献。结果本组2例均发生于右侧,术中证实例1为Ⅰ型,直接起源颈部迷走神经主干,与甲状腺上极血管相伴下行入喉;例2为ⅡA型,发自甲... 目的探讨喉不返神经(NRLN)的解剖特点及变异分型。方法回顾性分析本院收治2例NRLN的临床资料,并复习相关文献。结果本组2例均发生于右侧,术中证实例1为Ⅰ型,直接起源颈部迷走神经主干,与甲状腺上极血管相伴下行入喉;例2为ⅡA型,发自甲状腺下动脉水平迷走神经总干,平行甲状腺下动脉横行入喉。术后均未无NRLN并发症。结论 NRLN临床罕见,以右侧居多,术前难以诊断。术者应熟悉喉不返神经解剖特点及变异分型,避免损伤喉不返神经。 展开更多
关键词 甲状腺结节 喉返神经 遗传变异 解剖
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Breath monitoring,sleep disorder detection,and tracking using thin-film acoustic waves and open-source electronics
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作者 Jethro Vernon Pep Canyelles-Pericas +4 位作者 Hamdi Torun Richard Binns Wai Pang Ng Qiang Wu yong-qing fu 《Nanotechnology and Precision Engineering》 CAS CSCD 2022年第3期9-17,共9页
Apnoea,a major sleep disorder,affects many adults and causes several issues,such as fatigue,high blood pressure,liver conditions,increased risk of type II diabetes,and heart problems.Therefore,advanced monitoring and ... Apnoea,a major sleep disorder,affects many adults and causes several issues,such as fatigue,high blood pressure,liver conditions,increased risk of type II diabetes,and heart problems.Therefore,advanced monitoring and diagnosing tools of apnoea disorders are needed to facilitate better treatment,with advantages such as accuracy,comfort of use,cost effectiveness,and embedded computation capabilities to recognise,store,process,and transmit time series data.In this work we present an adaptation of our apnoea-Pi open-source surface acoustic wave(SAW)platform(Apnoea-Pi)to monitor and recognise apnoea in patients.The platform is based on a thin-film SAW device using bimorph ZnO and Al structures,including those fabricated as Al foils or plates,to achieve breath tracking based on humidity and temperature changes.We applied open-source electronics and provided embedded computing characteristics for signal processing,data recognition,storage,and transmission of breath signals.We show that the thin-film SAW device out-performed standard and off-the-shelf capacitive electronic sensors in terms of their response and accuracy for human breath-tracking purposes.This in combination with embedded electronics makes a suitable platform for human breath monitoring and sleep disorder recognition. 展开更多
关键词 Surface acoustic waves Sleep disorder APNOEA Open-source electronics Pattern recognition Piezoelectric thin film
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