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Updated: May 22, 2025

Two-way Valorization of Blast Furnace Slag: Synthesis of Precipitated Calcium Carbonate and Zeolitic Heavy Metal Adsorbent
Published on: February 21, 2017
Key Factors and Evaluation Model of Valuable Metal Separation in Low-Concentration Smelting Slag
Zhuandi Shao1,2, Tiantian Wei1,2, Xiujuan Zhang1,2
1School of Environment and Energy, The Key Laboratory of Pollution Control and Ecosystem Restoration in Industry Clusters (Ministry of Education), South China University of Technology, Guangzhou 510006, China.
Abstract:
The low concentration of valuable metals in smelting slags poses a significant challenge for separation. Despite the effective separation achieved by current pyrometallurgical or hydrometallurgical methods, the intricate mineralogy of slag and numerous leaching factors present considerable challenges in selecting the appropriate separation techniques and parameters for efficient and rapid extraction. In this study, copper slag flotation tailings (CSFT) were taken as an example, and the microexistence forms of valuable metals were analyzed through XRD and SEM-EDS. By integrating theoretical calculations and TGA analysis, a method involving concentrated sulfuric acid roasting and subsequent water leaching was employed to sufficiently extract valuable metals Mg, Cu, and Ni, concurrently achieving depth separation from Fe in the slag. Concurrently, a dynamic evaluation model correlating metal leaching efficiency (X ) with key factors has been established, enabling the quantification of valuable metal leaching performance under various conditions. Based on the kinetics equation and Arrhenius formula, with roasting temperature (T), roasting time (t), acid-to-solid ratio (r), and particle size (d) as key parameters, using experimental data, a dynamic evaluation model with kinetic characteristics was established as follows: 1/3ln(1- X ) - [1 - (1 - X )-1/3] = 9.36r 1.55 d -1.40 e -21957.8/RT t. The influence order was determined as roasting temperature > acid-to-solid ratio > particle size. The simulated values closely matched the experimental values, allowing the model to accurately predict the metal leaching rates. This provides an essential method for the design of metal recovery reaction parameters and optimization of engineering outcomes in the treatment of smelting slag.
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