增加转换线性度的连续波NQR温度传感器的结构和功能合成

IF 1.8 3区 化学 Q4 CHEMISTRY, PHYSICAL Solid state nuclear magnetic resonance Pub Date : 2020-12-01 DOI:10.1016/j.ssnmr.2020.101700
A. Samila , I. Safronov , O. Hotra
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引用次数: 3

摘要

本文介绍了提高转换线性度的连续波NQR温度传感器的详细结构和电路图的研制。实验证明,在调幅为40%、输入电压变化在20 ~ 1000 mV范围内时,采用线性有源解调器的对称边缘振荡器电路比采用JFET或二极管检波器的非对称边缘振荡器电路具有更好的传递特性线性度。所提出的NQR传感器的测温物质是氧化铜Cu2O,其特点是63Cu NQR的共振频率对温度有很强的依赖性。与KClO3中的35Cl NQR相反,对于氧化亚铜,63Сu NQR频率在26.621-25.658 MHz频率范围内的温度依赖性在100-390 K温度范围内呈线性关系。实验证实,使用低质量样品(小于200 mg)作为所提出的NQR传感器的测温物质,足以在信噪比为9.1 dB的情况下成功地观察到共振线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Structural and functional synthesis of the continuous wave NQR temperature sensor with increased conversion linearity

The paper describes development of the detailed structure and circuit diagrams of the continuous wave NQR temperature sensor with increased conversion linearity. It is experimentally established that at amplitude modulation of 40% and change of input voltage in the range of 20–1000 ​mV, the circuit of a symmetric marginal oscillator with a linear active demodulator provides better linearity of transfer characteristic than the circuits of asymmetric marginal oscillators with JFET or diode detectors. As a thermometric substance of the proposed NQR sensor, copper oxide Cu2O was used, which is characterized by a strong temperature dependence of the resonance frequency of 63Cu NQR. In contrast to 35Cl NQR in KClO3, for cuprous oxide the temperature dependence of 63Сu NQR frequency in the frequency range 26.621–25.658 ​MHz is linear in the temperature range 100–390 ​K. It is experimentally confirmed that the use of a low mass sample (less than 200 ​mg) as a thermometric substance of the proposed NQR sensor is quite sufficient for successfully observation of the resonance line at the SNR equal to 9.1 ​dB.

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来源期刊
CiteScore
5.30
自引率
9.40%
发文量
42
审稿时长
72 days
期刊介绍: The journal Solid State Nuclear Magnetic Resonance publishes original manuscripts of high scientific quality dealing with all experimental and theoretical aspects of solid state NMR. This includes advances in instrumentation, development of new experimental techniques and methodology, new theoretical insights, new data processing and simulation methods, and original applications of established or novel methods to scientific problems.
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