Bibliographic Details
| Title: |
Phase-Transition-Induced Self-Pulverization and Selective Metal Recovery of Electric Furnace Slag Processed by Vacuum Carbothermal Reduction. |
| Authors: |
Jiang, Kangning, Xu, Anxun, Lv, Xiaodong, Qin, Bingke, Li, Miao, Long, Xianze, Chen, Zhaohai, Huang, Qingqing, Huang, Run |
| Source: |
JOM: The Journal of The Minerals, Metals & Materials Society (TMS); Oct2026, Vol. 78 Issue 10, p9370-9386, 17p |
| Subject Terms: |
Phase transitions, Basicity, Metallurgical analysis, Waste recycling, Volatization, Calcium silicates, Fracture mechanics, Slag |
| Abstract: |
The output of electric furnace steel slag continues to increase, and its low utilization causes serious environmental and economic problems. This study proposes a novel vacuum carbothermal reduction process to simultaneously enhance the slag's self-pulverization and recover valuable metals. This study elucidates the synergistic regulation of vacuum carbothermal reduction for electric furnace steel slag by carbon addition, holding time, and basicity. Under optimized conditions (1450°C, 16%C, 60 min, R = 1.0), basicity is identified as the critical parameter dictating the selective recovery of valuable elements and the value-added conversion of the tailing slag: lowered basicity promoted slag self-pulverization, which was primarily attributed to the β → γ crystalline transformation of Ca2SiO4 during cooling. However, deviations from the optimum basicity (either too high or too low) inhibited this phase transition or caused iron aggregation, thereby reducing pulverization efficiency. Under the optimized parameters, the self-pulverization rate reached 93.8%, significantly surpassing the 49.97% achieved by conventional atmospheric processes at a higher temperature (1600°C), while also achieving high metal volatilization rates (Mg: 49.9%, Mn: 67.7%). [ABSTRACT FROM AUTHOR] |
|
Copyright of JOM: The Journal of The Minerals, Metals & Materials Society (TMS) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |