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New Approach to Study Iron Sulfide Precipitation Kinetics, Solubility, and Phase Transformation

A reliable anoxic plug flow reactor has been developed to study iron sulfide (FeS) precipitation kinetics, solubility, and phase transformation simultaneously. The effects of temperature (23–125 °C), ionic strength (0.00886–5.03 mol/kg), and ferrous iron [Fe­(II)] to sulfide [S­(-II)] concentration...

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Bibliographic Details
Published in:Industrial & engineering chemistry research 2017-08, Vol.56 (31), p.9016-9027
Main Authors: Liu, Ya, Zhang, Zhang, Bhandari, Narayan, Dai, Zhaoyi, Yan, Fei, Ruan, Gedeng, Lu, Alex Y, Deng, Guannan, Zhang, Fangfu, Al-Saiari, Hamad, Kan, Amy T, Tomson, Mason B
Format: Article
Language:English
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Summary:A reliable anoxic plug flow reactor has been developed to study iron sulfide (FeS) precipitation kinetics, solubility, and phase transformation simultaneously. The effects of temperature (23–125 °C), ionic strength (0.00886–5.03 mol/kg), and ferrous iron [Fe­(II)] to sulfide [S­(-II)] concentration ratio (1:20 to 1:5) were studied. The kinetics of FeS precipitation was found to be a pseudo-first-order reaction with respect to Fe­(II) concentration, when Fe­(II) concentration is significantly lower than the S­(-II) concentration. FeS precipitation kinetics can be accelerated by high temperature and high ionic strength but not be affected by the Fe­(II) to S­(-II) concentration ratio at the tested ratio range. A model for predicting FeS solubility and precipitation was developed by using FeS solubility data measured in this study and data from literature. At a temperature ≤100 °C, freshly precipitated FeS was found to be mackinawite. Mackinawite can transform to troilite at a temperature ≥50 °C, and low ionic strength favors the phase transformation. Also, mackinawite formed from steel corrosion seems to be easier to transform to troilite than the mackinawite formed from precipitation. This study presented a new approach for iron sulfide study and contributed valuable FeS thermodynamics and kinetics data for FeS prediction and control in industry.
ISSN:0888-5885
1520-5045
DOI:10.1021/acs.iecr.7b01615