Analysis of soluble components in coals and interpretations for the complex mass spectra

Fan, Xing; Yu, Yaru; Xia, Jun‐Liu; Cao, Jing‐Pei; Lu, Yao; Yue, Xiaoming; Zhu, Tenggao; Wei, Xian‐Yong; Lu, Jinren

doi:10.1002/rcm.7816

Cited by 15 publications

(8 citation statements)

References 21 publications

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“…Improved analytical methods were emerged to take advantage on the characterization of species in biooil. HRMSs were extensively used to identify individual component according to the monoisotopic mass in complex mixtures [ 17 , 44 , 47 , 74 , 76 , 83 , 84 ].…”

Section: Introductionmentioning

confidence: 99%

Analytical Strategies Involved in the Detailed Componential Characterization of Biooil Produced from Lignocellulosic Biomass

et al. 2017

International Journal of Analytical Chemistry

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Elucidation of chemical composition of biooil is essentially important to evaluate the process of lignocellulosic biomass (LCBM) conversion and its upgrading and suggest proper value-added utilization like producing fuel and feedstock for fine chemicals. Although the main components of LCBM are cellulose, hemicelluloses, and lignin, the chemicals derived from LCBM differ significantly due to the various feedstock and methods used for the decomposition. Biooil, produced from pyrolysis of LCBM, contains hundreds of organic chemicals with various classes. This review covers the methodologies used for the componential analysis of biooil, including pretreatments and instrumental analysis techniques. The use of chromatographic and spectrometric methods was highlighted, covering the conventional techniques such as gas chromatography, high performance liquid chromatography, Fourier transform infrared spectroscopy, nuclear magnetic resonance, and mass spectrometry. The combination of preseparation methods and instrumental technologies is a robust pathway for the detailed componential characterization of biooil. The organic species in biooils can be classified into alkanes, alkenes, alkynes, benzene-ring containing hydrocarbons, ethers, alcohols, phenols, aldehydes, ketones, esters, carboxylic acids, and other heteroatomic organic compounds. The recent development of high resolution mass spectrometry and multidimensional hyphenated chromatographic and spectrometric techniques has considerably elucidated the composition of biooils.

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Section: Introductionmentioning

confidence: 99%

Analytical Strategies Involved in the Detailed Componential Characterization of Biooil Produced from Lignocellulosic Biomass

et al. 2017

International Journal of Analytical Chemistry

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“…2,3 Moreover, carbon emission and acid rain mostly induced by coal burning led us to reconsider the utilization of coal in clean and highly efficient ways. 4,5 Lignite is unsuitable for direct burning, but suitable for developing as a feedstock for value-added chemicals due to the high content of organic oxygen. [6][7][8] It is reasonable to utilize lignite for non-fuel purposes and important to understand the molecular composition of the organic species present in lignite.…”

Section: Introductionmentioning

confidence: 99%

Characterization of humic acids extracted from a lignite and interpretation for the mass spectra

et al. 2017

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Humic acids obtained from a Chinese lignite via alkali treatment were analyzed using Fourier transform infrared spectroscopy and Orbitrap mass spectrometry coupled with an electrospray ion source (ESIOrbitrap-MS). Raw coal and the corresponding residue were characterized via scanning electron microscopy and energy dispersive spectrometry. Over 4700 heteroatom-containing compounds with wide distributions of molecular mass and unsaturation degree were detected via the ESI-Orbitrap-MS, and around 60 percent of the detected species were found to be oxygen-containing compounds. In addition, van Krevelen diagram and double-bond equivalent (DBE) plot were introduced to provide more structural details of the compounds. For the species only containing C, H, and O (HA CHO ), condensed aromatic compounds with a DBE value over 20 only contained 1 or 2 oxygen atoms. Carboxyl-and hydroxylcontaining aliphatic compounds (CHCACs) were predominant in HA CHO with 5 or 6 oxygen atoms. Both the CHCACs and aromatic carboxylic acids or phenols were grouped into clusters in the van Krevelen diagram to be recognized. The introduction of a nitrogen atom to the HA CHO species was based on the structures of the HA CHO species, which is also indicated by the van Krevelen diagram.

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“…Data 13–15 (obtained by ESI−) contain relatively higher contents of compounds from the O 4 –O 6 classes. Previous research has shown that a high number of oxygen atoms per molecule causes an increased polarity and the molecule is more facile to be ionized by ESI compared with APPI . Compounds in the ON class are widely detected by ESI‐MS.…”

Section: Resultsmentioning

confidence: 99%

“…However, there are large amounts of compounds from the N and ON classes in group 1 because ESI+ is more suitable to detect alkaline compounds . Combining the loading plot with the score plot, groups 2 and 3 mainly contain the compounds from the ON, OS, N and NS classes, while no compound from the CH class was detected in all of the extracts because hydrocarbons are difficult to protonate in the positive mode of ESI …”

Section: Resultsmentioning

confidence: 99%

Insight into molecular information of Huolinguole lignite obtained by Fourier transform ion cyclotron resonance mass spectrometry and statistical methods

Fan

et al. 2019

Rapid Comm Mass Spectrometry

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Rationale: Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was applied to the characterization of organic compounds in coal extracts at the molecular level. Large volumes of data obtained by FT-ICR MS were processed via statistical methods to extract valuable information on the molecular structures and compositions of organic compounds in coal. Methods:A low-rank coal was subjected to ultrasonic extraction sequentially with six solvents to separate and enrich species with different molecular characteristics.Complex mass spectra of the six extracts were obtained by a FT-ICR MS system equipped with two ionization sources. Two multivariate statistical methods, hierarchical clustering analysis (HCA) and principle component analysis (PCA), were introduced to mine useful information from the complex MS data and visually exhibit comprehensive molecular details in coal extracts.Results: Similarities and differences between the 17 MS data sets from six coal extracts ionized by different ion sources were visually exhibited in plots via data processing using HCA and PCA. For HCA, all of the identified compounds were divided into seven classes (CH, O, N, S, ON, OS, and NS), and detailed differences in the relative abundance were revealed. In addition, PCA discriminated the differences in molecular composition for organic compounds from the six extracts. Conclusions:Multivariate statistical analysis is a promising methodology which can interpret the chemical composition of coals and coal derivatives at the molecular level, especially for the analysis of multiple complex samples presenting in a single plot.

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Analysis of soluble components in coals and interpretations for the complex mass spectra

Cited by 15 publications

References 21 publications

Analytical Strategies Involved in the Detailed Componential Characterization of Biooil Produced from Lignocellulosic Biomass

Analytical Strategies Involved in the Detailed Componential Characterization of Biooil Produced from Lignocellulosic Biomass

Characterization of humic acids extracted from a lignite and interpretation for the mass spectra

Insight into molecular information of Huolinguole lignite obtained by Fourier transform ion cyclotron resonance mass spectrometry and statistical methods

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