研究目的
Investigating the structural differences of spontaneous combustion prone inertinite-rich Chinese lignite coals to understand their impact on coal fire propensity and behavior.
研究成果
The study concludes that the more spontaneous combustion-prone lignite had a significantly higher total pore volume and surface area, with both coals having similar micro- and mesopore size distributions. The inertinite contribution shifts some structural properties to be similar to vitrinite-rich, high-volatile bituminous rank coals. These findings provide insights into the structural variations affecting spontaneous combustion propensity in inertinite-rich lignites.
研究不足
The study focuses on two specific lignite coals from Xinjiang province, which may not represent all inertinite-rich coals. The experimental conditions, such as drying the coals, may not fully replicate natural conditions affecting spontaneous combustion.
1:Experimental Design and Method Selection:
The study involved the examination of two raw Xinjiang lignites from the Shaerhu (SEH) and Piliqing (PLQ) Collieries using XRD, solid-state 13C NMR, LDIMS, and HRTEM techniques to analyze their chemical and physical structures.
2:Sample Selection and Data Sources:
Two Chinese coals were collected from Shaerhu (SEH) and Piliqing (PLQ) Collieries, differing in spontaneous combustion susceptibility.
3:List of Experimental Equipment and Materials:
Equipment used includes a Rigaku D/max 2500 PC X-ray diffractometer, a Bruker ADVANVE III 600 MHz Wide Bore spectrometer, a JEOL JEM 2010 transmission electron microscope, and a Micromeritics ASAP-2020 for gas adsorption measurements.
4:Experimental Procedures and Operational Workflow:
The coal samples were crushed, vacuum-dried, and analyzed using the aforementioned techniques to determine their structural properties and spontaneous combustion tendencies.
5:Data Analysis Methods:
Data from XRD, NMR, HRTEM, and gas adsorption were analyzed to determine crystallite parameters, aromaticity, pore size distributions, and molecular weight distributions.
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