Optimization of the thermophysical properties of cast iron for aluminum electrolysis

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Authors: zixiang zhao, Junhao Wu, Liping Wang, Qian Zhang, Hui Fang, Wenyuan Hou
Cited by: 0
References: 18

Abstract

Abstract In the anode assembly of an aluminum electrolysis cell, cast iron connects the carbon anode and anode stub, providing thermal, electrical, and structural connections. As a major energy-consuming component in aluminum electrolysis, the properties of cast iron directly impact electrolysis energy consumption. The four primary elemental compositions of cast iron (C, Si, Mn, and P) have a significant impact on its thermophysical properties. While previous studies have primarily focused on the individual or pairwise effects of elements on cast iron properties, this work systematically investigates the interactive effects of four key elements using response surface methodology and multi-objective optimization. This approach enables the simultaneous optimization of resistivity and thermal expansion coefficient, providing a balanced elemental composition that has not been previously reported for aluminum electrolysis applications. The mass fractions of C, Si, Mn, and P were selected as the designing parameters, with the resistivity and thermal expansion coefficient serving as responses. The interactive effects of cast iron components on the responses ​​are plotted through 3D response surface plots. The results show that C, Si, Mn, and P have a statistically significant effect on resistivity of cast iron, with C having the most significant effect. Si, Mn, and P have a significant effect on the thermal expansion coefficient, with P having the most significant effect. The optimal element ratio of cast iron for aluminum electrolysis is: C content 3.28 wt%, Si content 2.22 wt%, Mn content 0.49 wt%, P content 1.01 wt%.

Fields of Study & Subjects

Metallurgical Processes and Thermodynamics Thermodynamic and Structural Properties of Metals and Alloys Machine Learning in Materials Science

Publication details

Journal / source
Materials Research Express
Volume
13
Issue
4
Pages
046504–046504
Publication date
12 February 2026
Language
EN