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Mass spectrometric evaluation of the soluble species of Shengli lignite using cluster analysis methods

机译:聚类分析方法对胜利褐煤中的可溶性物质进行质谱分析

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摘要

A coal was extracted and thermally dissolved with cyclohexane, acetone and methanol sequentially. The ultrasonic extracts and thermal dissolution (TD) products were analyzed using an Orbitrap mass spectrometer (MS) with an atmospheric pressure chemical ionization source in positive ion mode. Large amounts of MS data were obtained but there were challenges in obtaining meaningful information from the data. The purpose of cluster analysis is to reduce complex multivariate data into meaningful groups. Two cluster analysis methods, hierarchical cluster analysis and expectation maximum algorithm based on Gaussian mixture model (EMGM), run by R language were introduced to obtain in-depth statistical results for compounds in both extracts and TD products. Seven types of heteroatomic compounds (O-1, O-2, N-1, S-1, O1N1, O1S1 and N1S1) in the extracts under the condition of ultrasonic extraction with cyclohexane were clustered with EMGM and possible structures of the related models can be inferred by analyzing the relationship between carbon number and double bond equivalent. The application of cluster analysis will provide methodological guidance in studying the structure of coal molecules.
机译:提取煤并依次与环己烷,丙酮和甲醇热溶解。超声提取物和热溶解(TD)产物使用Orbitrap质谱仪(MS)和大气压化学电离源以正离子模式进行分析。获得了大量的MS数据,但是从数据中获取有意义的信息仍然存在挑战。聚类分析的目的是将复杂的多元数据减少为有意义的组。介绍了两种由R语言运行的聚类分析方法,即层次聚类分析和基于高斯混合模型(EMGM)的期望最大值算法,以获取提取物和TD产品中化合物的深入统计结果。用环己烷超声提取条件下提取物中的七种杂原子化合物(O-1,O-2,N-1,S-1,O1N1,O1S1和N1S1)与EMGM聚类,并建立了相关模型的可能结构通过分析碳数和双键当量之间的关系可以推断出。聚类分析的应用将为研究煤分子的结构提供方法学指导。

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