The fusion mechanism of complex minerals mixture and prediction model for flow temperature of coal ash for gasification. (1st December 2021)

• Record Type: Journal Article
• Authors: Shi, Wenju; Laabs, Marcel; Reinmöller, Markus; Kong, Lingxue; Vassilev, Stanislav V.; Guhl, Stefan; Bai, Jin; Meyer, Bernd; Li, Wen
• Is Part Of: Fuel. Volume 305(2021)
• Publication Date: 2021-12-01
• Subjects: Fusion mechanisms -- Density -- Dissolution rate -- Flow temperature prediction; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2021.121448
• Languages: English
• ISSNs: 0016-2361

Abstract

Graphical abstract: Highlights: The fusion mechanism of ash in mullite phase area is "melting-sinking-dissolving". The fusion mechanism of ash in anorthite phase area is "soften-melting" mechanism. FT prediction model based on fusion mechanisms can improve the predicting accuracy. Tmullite for ashes in mullite phase area can be estimated by IFe-Ca . Abstract: Management of slag behavior for safe slag-tapping requires the well understanding of slag flow behavior and reliable prediction model for flow ash fusion temperature (FT) of coal ash. With the support of thermomechanical analysis, high-temperature scanning electron microscope, density and dissolution rate of main minerals, the fusion mechanism of ashes in mullite phase area is concluded as "melting-sinking-dissolving", and as "softening-melting" for ashes in anorthite phase area. The first mechanism refers to formation of large number of low temperature eutectics and narrow melting temperature range, while the "softening-melting" mechanism shows wide fusion temperature range. It is indicated that, small amount of remained mullite has little influence on FT for samples in mullite phase area and vast formed anorthite has huge effect on FT. Subsequently, combining our previous discovery, the construction of sub-mineral grouping parameter and the correlation between Tmullite and chemical composition provides an alternative to predict FT when FactSage software is unavailable. This work enables the prediction of FT from chemical composition according to the classification of fusion mechanism.