4.7 Article

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

期刊

FUEL
卷 236, 期 -, 页码 1037-1042

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2018.09.063

关键词

Coal; Expectation maximum algorithm; Extraction; Hierarchical cluster analysis; R language; Thermal dissolution

资金

  1. National Natural Science Foundation of China [21676293]
  2. Key Project of Joint Fund from National Natural Science Foundation of China [U1503293]
  3. Government of Xinjiang Uygur Autonomous Region [U1503293]
  4. Qing Lan Project of Jiangsu Province
  5. Priority Academic Program Development of Jiangsu Higher Education Institutions

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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.

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