首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Sensitivity Enhancement of NMR Spectroscopy Receiving Chain Used in Condensed Matter Physics
【2h】

Sensitivity Enhancement of NMR Spectroscopy Receiving Chain Used in Condensed Matter Physics

机译:凝聚态物理中NMR光谱接收链的灵敏度增强

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Assurance of high measuring sensitivity is one of the most challenging issues for any nuclear magnetic resonance (NMR) spectroscopy system. To this end, we propose an accurate noise model of the entire probe-to-spectrometer receiving chain for condensed matter physics, based on the concept of noise figure. The model predicts the propagation of both the signal and noise levels in every component of the NMR spectroscopy receiving chain. Furthermore, it enables identification of the "weakest" component and, therefore, the optimization of the whole system. The most important property of the proposed model is the possibility to find system parameters that reduce the measurement time by an a priori calculation, rather than an a posteriori approach. The model was tested experimentally on several different samples. It was found that the measurement time can still be significantly shortened, down to at least one half of the measurement time, starting from optimized conditions with commercially available components. Thus, the proposed model can be used as a tool for both quantitative analysis of the noise properties and a sensitivity prediction of practical NMR systems in physics and material science.
机译:确保高测量灵敏度是任何核磁共振(NMR)光谱系统中最具挑战性的问题之一。为此,我们基于噪声系数的概念,为凝结物物理学提出了一个完整的探头到光谱仪接收链的精确噪声模型。该模型预测NMR光谱接收链的每个组件中信号和噪声水平的传播。此外,它还可以识别“最弱”的组件,因此可以优化整个系统。所提出模型的最重要属性是可以通过先验计算而不是后验方法来找到减少测量时间的系统参数。该模型在几个不同的样本上进行了实验测试。已经发现,从使用市售组件获得的最佳条件开始,测量时间仍可以显着缩短,至少可缩短至测量时间的一半。因此,所提出的模型可以用作在物理和材料科学中对噪声特性进行定量分析以及对实际NMR系统进行灵敏度预测的工具。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号