Physics-Constrained Constitutive Learning of Rate-Limiting Timescales for Efficient Hydrogen-Based Direct Reduction...

Area of Science:

• Materials Science
• Chemical Engineering
• Metallurgy

Background:

• Hydrogen-based direct-reduction is key for carbon-neutral ironmaking.
• Industrial adoption is limited by slow late-stage reduction kinetics, impacting efficiency and resource use.

Purpose of the Study:

• To develop a framework for analyzing reduction kinetics in ironmaking.
• To identify rate-limiting factors and their dependence on operating conditions and pellet properties.

Main Methods:

• Developed a conversion-resolved constitutive framework (SCAM) to infer reaction and transport timescales from reduction trajectories.
• Mapped timescale dependencies on operating conditions, pellet architecture, and composition.
• Generated constitutive maps, symbolic laws, and regime boundaries.

Main Results:

• Internal diffusion significantly slows down reduction at intermediate to high conversion stages.
• The shift from reaction to diffusion control depends on conversion and evolving microstructure.
• Temperature and hydrogen pressure affect early stages; pellet structure (porosity, tortuosity) governs late-stage kinetics.
• Pellet composition influences diffusion-controlled regimes via pore morphology.

Conclusions:

• The framework provides experimentally anchored, pellet-scale constitutive relations.
• Identified reduction-stage-specific rate limitations.
• Offers guidelines for designing industrial pellets to enhance green steelmaking efficiency.