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Application of Fourier transform ion cyclotron resonance mass spectrometry to characterize natural organic matter.
Chemosphere ( IF 8.8 ) Pub Date : 2020-06-28 , DOI: 10.1016/j.chemosphere.2020.127458
Xiaoxiao Zhang 1 , Jiarui Han 2 , Xiangru Zhang 2 , Jimin Shen 3 , Zhonglin Chen 3 , Wei Chu 4 , Jing Kang 3 , Shengxin Zhao 3 , Yaoyu Zhou 5
Affiliation  

Advances in the ultra-high-resolution mass spectroscopy lead to a deep insight into the molecular characterization of natural organic matter (NOM). Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) has been used as one of the most powerful tools to decipher NOM molecules. In FTICR-MS analysis, the matrix effects caused by the co-occurring inorganic substances in water samples greatly affect the ionization of NOM molecules. The inherent complexity of NOM may hinder its component classification and formula assignment. In this study, basic principles and recent advances for sample separation and purification approaches, ionization methods, and the evolutions in formula assignment and data exploitation of the FTICR-MS analysis were reviewed. The complementary characterization methods for FTICR-MS were also reviewed. By coupling with other developed/developing characterization methods, the statistical confidence for inferring the NOM compositions by FTICR-MS was greatly improved. Despite that the refined separation procedures and advanced data processing methods for NOM molecules have been exploited, the big challenge for interpreting NOM molecules is to give the basic structures of them. Online share of the FTICR-MS data, further optimizing the FTICR-MS technique, and coupling this technique with more characterization methods would be beneficial to improving the understanding of the composition and property of NOM.



中文翻译:

傅里叶变换离子回旋共振质谱在表征天然有机物中的应用。

超高分辨率质谱技术的进步导致人们对天然有机物(NOM)分子表征的深入了解。傅里叶变换离子回旋共振质谱(FTICR-MS)已被用作解密NOM分子的最强大工具之一。在FTICR-MS分析中,水样品中同时存在的无机物引起的基质效应极大地影响了NOM分子的电离。NOM固有的复杂性可能会阻碍其组分分类和公式分配。在这项研究中,概述了样品分离和纯化方法,电离方法的基本原理和最新进展,以及FTICR-MS分析的配方分配和数据开发方面的发展。还综述了FTICR-MS的互补表征方法。通过与其他已开发/正在开发的表征方法相结合,通过FTICR-MS推断NOM组成的统计可信度大大提高。尽管已经开发出了完善的NOM分子分离程序和先进的数据处理方法,但要解释NOM分子的最大挑战是提供其基本结构。在线共享FTICR-MS数据,进一步优化FTICR-MS技术,以及将该技术与更多表征方法结合使用,将有助于增进对NOM组成和性质的了解。尽管已经开发出了完善的NOM分子分离程序和先进的数据处理方法,但要解释NOM分子的最大挑战是提供其基本结构。在线共享FTICR-MS数据,进一步优化FTICR-MS技术,以及将该技术与更多表征方法结合使用,将有助于增进对NOM组成和性质的了解。尽管已经开发出了完善的NOM分子分离程序和先进的数据处理方法,但要解释NOM分子的最大挑战是提供其基本结构。在线共享FTICR-MS数据,进一步优化FTICR-MS技术,以及将该技术与更多表征方法结合使用,将有助于增进对NOM组成和性质的了解。

更新日期:2020-07-20
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