Novel Insights into Low-Carbon Metallurgical Process Simulation and Optimization

Dear Colleagues,

The metallurgical industry stands at a critical juncture in its transition toward carbon neutrality. Responsible for a significant share of global industrial CO₂ emissions, the sector is actively exploring breakthrough technologies including hydrogen-based direct reduction, renewable energy-powered electrolysis, and novel smelting routes . However, the complexity of high-temperature multiphase reactions, coupled with the high cost and technical risk of physical trials, makes process optimization particularly challenging. Computational modeling and simulation have emerged as indispensable tools to accelerate this low-carbon transition. From particle-scale discrete element method (DEM) and computational fluid dynamics (CFD) to system-level process integration, numerical approaches enable researchers to visualize internal furnace phenomena, optimize operating parameters, and quantify energy efficiency and emissions reduction potential before industrial implementation. Recent advances in multi-physics coupling, digital twin technologies, and AI-accelerated surrogate models are opening new frontiers for process intensification.

This Special Issue aims to showcase novel insights into the simulation and optimization of low-carbon metallurgical processes. We invite contributions on hydrogen-based ironmaking, electric smelting furnaces, renewable energy integration, process-scale life cycle assessment, and innovative numerical methods. By bringing together cutting-edge research from academia and industry, this issue seeks to advance the scientific understanding and practical deployment of sustainable metallurgical technologies.

Dr. Fuhai Liu
Dr. Kai Feng
Dr. Hang Hu
Guest Editors

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