Hydrogen direct reduction and reoxidation behaviour of high-grade pellets

Cavaliere, Pasquale; Dijon, Leandro; Laska, Aleksandra; Koszelow, Damian

doi:10.1016/j.ijhydene.2023.08.254

Cited by 12 publications

(2 citation statements)

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“…It is influenced by the pellet's porosity in terms of size, distribution, and tortuosity of pores, which affect the volume of hydrogen reacting with the internal surface of the pellet. When porosity is low and pores on the surface are small, hydrogen diffusion into the pellet becomes hindered, making solid-state diffusion from the surface more critical, and much slower [96]. Higher porosity facilitates better gas diffusion, leading to more efficient reduction.…”

Section: Results Of Research Studies Focused On the Reduction In Iron...mentioning

confidence: 99%

“…Changes in pellet diameter affect how density influences the reduction; higher density diminishes the impact of diameter, whereas in larger, less dense pellets, the effect of density is less pronounced. Reduction time also correlates with both the absolute porosity and the dimensions of surface pores-larger pores facilitate faster reduction [96].…”

Section: Results Of Research Studies Focused On the Reduction In Iron...mentioning

confidence: 99%

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An Overview Analysis of Current Research Status in Iron Oxides Reduction by Hydrogen

Miškovičová,

Legemza,

Demeter

et al. 2024

Metals

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This paper focuses on the study of current knowledge regarding the use of hydrogen as a reducing agent in the metallurgical processes of iron and steel production. This focus is driven by the need to introduce environmentally suitable energy sources and reducing agents in this sector. This theoretical study primarily examines laboratory research on the reduction of Fe-based, metal-bearing materials. The article presents a critical analysis of the reduction in iron oxides using hydrogen, highlighting the advantages and disadvantages of this method. Most experimental facilities worldwide employ their unique original methodologies, with techniques based on Thermogravimetric analysis (TGA) devices, fluidized beds, and reduction retorts being the most common. The analysis indicates that the mineralogical composition of the Fe ores used plays a crucial role in hydrogen reduction. Temperatures during hydrogen reduction typically range from 500 to 900 °C. The reaction rate and degree of reduction increase with higher temperatures, with the transformation of wüstite to iron being the slowest step. Furthermore, the analysis demonstrates that reduction of iron ore with hydrogen occurs more intensively and quickly than with carbon monoxide (CO) or a hydrogen/carbon monoxide (H2/CO) mixture in the temperature range of 500 °C to 900 °C. The study establishes that hydrogen is a superior reducing agent for iron oxides, offering rapid reduction kinetics and a higher degree of reduction compared to traditional carbon-based methods across a broad temperature range. These findings underscore hydrogen’s potential to significantly reduce greenhouse gas emissions in the steel production industry, supporting a shift towards more sustainable manufacturing practices. However, the implementation of hydrogen as a primary reducing agent in industrial settings is constrained by current technological limitations and the need for substantial infrastructural developments to support large-scale hydrogen production and utilization.

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Section: Results Of Research Studies Focused On the Reduction In Iron...mentioning

confidence: 99%

Section: Results Of Research Studies Focused On the Reduction In Iron...mentioning

confidence: 99%

An Overview Analysis of Current Research Status in Iron Oxides Reduction by Hydrogen

Miškovičová,

Legemza,

Demeter

et al. 2024

Metals

View full text Add to dashboard Cite

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Modeling of Gaseous Reduction of Iron Oxide Pellets Using Machine Learning Algorithms, Explainable Artificial Intelligence, and Hyperparameter Optimization Techniques

Hosseinzadeh,

Kasiri,

Rezaei

2024

steel research int.

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In this study, a novel application of machine learning (ML) is introduced to pellet modeling in the intricate non‐catalytic gas–solid reaction of direct reduction of iron oxide in the steel industry. Twenty ML models are developed using four algorithms: multilayer perceptron neural networks (MLPNN), radial basis function neural network (RBFNN), support vector regression, and random forest (RF). Hyperparameter optimization is conducted using Bayesian algorithms, random search, and grid search. The optimum model achieves a mean squared error test of 0.0052 with random RF for the larger dataset (872 samples), while smaller datasets (132, 225, and 242 samples) produce optimum models with MLPNN and RBFNN. Hyperparameters vary between the larger datasets and the smaller datasets. The models offer insight into the complex interactions among variables, including time, temperature, gas composition, hematite composition, pellet radius, and initial pellet porosity, influencing the metallization degree. In this study, the significant role of time and temperature is emphasized, as revealed by explainable artificial intelligence using Shapley additive explanation analysis that utilizes the game theory, and the effects of pellet modeling parameters are elucidated through 3D plots, particularly highlighting the impact of changing H2/CO proportion on metallization degree and carbon deposit.

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TiO2 and Reducing Gas: Intricate Relationships to Direct Reduction of Iron Oxide Pellets

Cavaliere,

Sadeghi,

Laska

et al. 2024

Metall Mater Trans B

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In response to the imperative for sustainable iron production with reduced CO2 emissions, this study delves into the intricate role of TiO2 in the direct reduction of iron oxide pellets. The TiO2-dependent reducibility of iron oxide pellets utilizing H2 and CO gas across varied temperatures and gas compositions is thoroughly investigated. Our findings unveil the nuanced nature of the TiO2 effect, underscored by its concentration-dependent behavior, revealing an optimal range between 1 and 1.5 pct TiO2, where a neutral or positive impact on reduction kinetics and diffusion coefficient is observed. Notably, the synergistic interplay of CO and H2 at 1000 °C emerges as particularly efficacious, suggesting complementary effects on the reduction process. The introduction of H2 into the reducing atmosphere regulated by CO not only extends the transition range but also markedly expedites the rate of reduction. Furthermore, our study highlights the temperature sensitivity of the TiO2 effect, with higher TiO2 content correlating with prolonged reduction time in a 100 pct H2 atmosphere at 900 °C. In a 100 pct H2 atmosphere, the non-contributory role of TiO2 stems from the water-gas shift reaction. Conversely, introducing H2 into a CO-controlled reducing atmosphere with TiO2 enhances the transition range and expedites the reduction rate. Additionally, our findings underscore the role of total iron content, revealing a direct correlation with the reduction process.

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Hydrogen direct reduction and reoxidation behaviour of high-grade pellets

Cited by 12 publications

References 43 publications

An Overview Analysis of Current Research Status in Iron Oxides Reduction by Hydrogen

An Overview Analysis of Current Research Status in Iron Oxides Reduction by Hydrogen

Modeling of Gaseous Reduction of Iron Oxide Pellets Using Machine Learning Algorithms, Explainable Artificial Intelligence, and Hyperparameter Optimization Techniques

TiO2 and Reducing Gas: Intricate Relationships to Direct Reduction of Iron Oxide Pellets

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