Indexed by:
Journal Papers
First Author:
Zhou, Yang
Correspondence Author:
Hu, HQ (reprint author), Dalian Univ Technol, Sch Chem Engn, Inst Coal Chem Engn, State Key Lab Fine Chem, Dalian 116024, Peoples R China.; Fan, HJ (reprint author), Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Mol React Dynam, Dalian 116023, Peoples R China.
Co-author:
Li, Lu,Jin, Lijun,Zhu, Jialong,Li, Jiangang,Li, Yang,Fan, Hongjun,Hu, Haoquan
Date of Publication:
2020-01-15
Journal:
FUEL
Included Journals:
EI、SCIE
Document Type:
J
Volume:
260
ISSN No.:
0016-2361
Key Words:
Coal pyrolysis; Functional groups; In-situ analysis; Volatile evolution;
Py-PI-TOF MS
Abstract:
To investigate the effect of functional groups in coal on volatiles evolution, eight coal samples with different ranks were pyrolyzed in a novel in-situ pyrolysis photoionization time-of-flight mass spectrometer (Py-PI-TOF MS). Soft ionization were adopted to enable the fragment-free detection of volatiles generated from initial pyrolysis products. Temperature-evolved profiles of main products are visible via scanning of the ion current of individual compound measured during the pyrolysis processes. The obtained mass spectra of volatiles from pyrolysis of eight coal samples reveal predominantly molecular ions with four categories: alkenes, benzenes, phenols and diphenols. Furthermore, the analysis of different coal samples demonstrates that both alkyl and oxygen-containing groups attached on the benzene rings can reduce the peak temperatures of main products' evolution, and the effect of oxygen-containing group is stronger than that of alkyl group. The difference of peak temperature with maximum evolution, which is used as an indicator to measure the effect of the functional groups, were correlated with carbon content and volatile content of coal samples. The influence degree of functional groups on evolution temperature was found to be negative correlated with the carbon content and positive correlated with the volatile content, respectively. Based on the experimental observations and theoretical calculations, the overall results allowed to reveal the influence of the functional groups on the volatile organic compounds during coal pyrolysis. Analogous to reported setups with online studies of coal pyrolysis, PyPI-TOF MS may be a good option for monitoring the evolution characteristics and reaction pathways of coal pyrolysis process.
Translation or Not:
no
