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Production of iron and steel releases seven percent of the global greenhouse gas (GHG) emissions. Incremental changes in present primary steel production technologies would not be sufficient to meet the emission reduction targets. Replacing coke, used in the blast furnaces as a reducing agent, with hydrogen produced from water electrolysis has the potential to reduce emissions from iron and steel production substantially. Mass and energy flow model based on an open-source software (Python) has been developed in this work to explore the feasibility of using hydrogen direct reduction of iron ore (HDRI) coupled with electric arc furnace (EAF) for carbon-free steel production. Modeling results show that HDRI-EAF technology could reduce specific emissions from steel production in the EU by more than 35 % , at present grid emission levels (295 kgCO2/MWh). The energy consumption for 1 ton of liquid steel (tls) production through the HDRI-EAF route was found to be 3.72 MWh, which is slightly more than the 3.48 MWh required for steel production through the blast furnace (BF) basic oxygen furnace route (BOF). Pellet making and steel finishing processes have not been considered. Sensitivity analysis revealed that electrolyzer efficiency is the most important factor affecting the system energy consumption, while the grid emission factor is strongly correlated with the overall system emissions.

The traditional ironmaking technologies (including coking, sintering, pelletizing, and BF ironmaking process) are carbon-intensive, which makes the industry a significant contributor to global CO 2 emissions. Hydrogen replacement of carbon in steelmaking processes is a sustainable way to reduce CO 2 emissions. First, the reduction thermodynamics and kinetics of iron oxide by carbon and hydrogen are compared. Then, the latest researches on different hydrogen reduction technologies in ironmaking industry are compared and analyzed. Based on this, the advantages and problems faced by hydrogen-based reduction over carbon-based reduction are presented. And finally, the possible pathways for the future development of hydrogen metallurgy are proposed, hoping to provide guidance for the hydrogen metallurgy in the steel industry. The reduction product of hydrogen metallurgy is H 2 O, and has a faster reduction rate than CO reduction. Therefore, hydrogen metallurgy is considered to be an effective way to achieve low-carbon green transformation in the metallurgical industry. Graphical Abstract

Continuous casting is a key process in steel production, and optimizing the cutting process to minimize material waste while meeting customer demands is one of the core challenges in improving production efficiency. This paper proposes an online optimization algorithm to address the cutting optimization problem in steel continuous casting. Through an optimization model constructed by combining nested models, analytical modeling, and computer traversal algorithms, cutting schemes can be adjusted in real-time when production abnormalities occur, ensuring production continuity and efficiency. The proposed method demonstrates excellent performance in reducing cutting losses, meeting production requirements, and minimizing secondary cutting operations, with broad practical application potential.

Promoting energy efficiency in iron and steel production provides opportunities for mitigating environmental impacts from this energy-intensive industry. Energy efficiency technologies differ in investment costs, fuel-saving potentials, and environmental performance. Hence the decision-making of the adoption strategy needs to prioritize technological combinations concerning these multi-dimensional objectives. To address this problem, this study proposes a hybrid multi-criteria decision-support model for adopting energy efficiency technologies in the iron and steel industry. The modeling framework integrates a linear programming model that determines the optimal technology adoption rates based on the techno-economic, energy, and environmental performance details and an interactive multi-criteria model analysis tool for diverse modeling environments. A real case study was performed in which a total number of 56 energy efficiency technologies were investigated against various criteria concerning economics, energy, and environmental performances. The results examine the tradeoffs and synergies were examined with regard to seven criteria. A balanced solution shows that a total investment of 13.4 billion USD could save 2.51 Exajoule fuel consumption, cut 67.4 million tons (Mton) CO2 emissions, and reduce air pollution of 1.5 Mton SO2, 1.41 Mton NOx, and 0.86 Mton PM, respectively. The case study demonstrates the effectiveness and applicability of the proposed multi-criteria decision-making support framework.

Chromium is a critical material for stainless steel production. With economic growth and the optimization and upgrading of industrial structure, China’s demand for chromium has been increasing year by year. Conducting research on chromium demand forecasting holds significant practical implications for the sustainable development of China’s chromium industrial chain. China’s chromium consumption accounts for one-third of the global, over 95% of which has long-term depended on imports, and 90% of which is used in stainless steel production. In this paper, a linear correlation model between chromium consumption and stainless steel production is constructed by using the department demand forecasting method. The importance of influencing factors on chromium demand is analyzed using the gray correlation degree, and a PSO-BP neural network algorithm is constructed to predict China’s chromium demand from 2025 to 2040. The results indicate that the predictions of the two methods are relatively consistent, with demand for chromium expected to peak in 2035 and then decline gradually thereafter. This provides an important reference basis for the security and sustainable development of China’s chromium supply chain.

The evolution of the steel industry has been characterized by the dual pursuit of quantitative output and qualitative excellence. However, existing studies and media have predominantly emphasized crude steel production as the primary indicator of a steel company’s competitiveness. However, this metric does not adequately reflect the quality competitiveness in this industry. This study introduces the integrated production ratio (IPR), defined as the proportion of cold-rolled steel sheet―a representative high-grade product―within a company’s total steel output, as a complementary metric. A higher IPR reflects a greater focus on high-grade steel production and thus serves as an indicator of quality competitiveness. The utility of IPR is demonstrated through an analysis of production trends from POSCO, a leading Korean steel manufacturer.

Steelmaking-refining-Continuous Casting (SCC) is a bottleneck in the iron and steel production operation. In order to enhance production efficiency, SCC scheduling is employed to find an optimal schedule. Unfortunately, dynamic events such as charge start-time delay may occur in a real-world SCC process, which will invalidate the optimal SCC schedule, i.e., making the schedule not optimal or inexecutable. To cope with such a situation, SCC rescheduling is significant for generating a new optimal schedule. This paper proposes a mathematical model of the SCC rescheduling problem considering charge start-time delay, and further presents an Elite solutions and Tabu assisted Variable Neighbourhood Descent (ETVND) method to tackle the problem. The main framework of the ETVND method is Variable Neighbourhood Descent (VND). In the ETVND method, three Tabu based neighbourhood structures are elaborately designed. Moreover, three distinguished features are incorporated, i.e., an elite solutions based exploration strategy, two-layer local search based on the Fruit fly Optimization Algorithm, and multi-type perturbation. The first two features are devised to enhance the intensification abilities while the third is devised to improve the diversification abilities. Experimental results have demonstrated the effectiveness of the ETVND method by comparing with several algorithms in the literature. Further comparison experiments have validated the efficiency of the Tabu based neighbourhood structures and specially devised strategies.

Hydrogen-based direct reduction (HyDR) of iron ores has attracted immense attention and is considered a forerunner technology for sustainable ironmaking. It has a high potential to mitigate CO 2 emissions in the steel industry, which accounts today for ~ 8–10% of all global CO 2 emissions. Direct reduction produces highly porous sponge iron via natural-gas-based or gasified-coal-based reducing agents that contain hydrogen and organic molecules. Commercial technologies usually operate at elevated pressure, e.g., the MIDREX process at 2 bar and the HyL/Energiron process at 6–8 bar. However, the impact of H 2 pressure on reduction kinetics and microstructure evolution of hematite pellets during hydrogen-based direct reduction has not been well understood. Here, we present a study about the influence of H 2 pressure on the reduction kinetics of hematite pellets with pure H 2 at 700 °C at various pressures, i.e., 1, 10, and 100 bar under static gas exposure, and 1.3 and 50 bar under dynamic gas exposure. The microstructure of the reduced pellets was characterized by combining X-ray diffraction and scanning electron microscopy equipped with electron backscatter diffraction. The results provide new insights into the critical role of H 2 pressure in the hydrogen-based direct reduction process and establish a direction for future furnace design and process optimization. Graphical Abstract

Conventional (anthracite, calcined petroleum coke, and coke) and non-conventional (biochar, and biocokes (3 wt.% torrefied wood, and 3 wt.% petroleum coke + 3 wt.% charcoal)) carbon-bearing sources have been studied for their use in electric arc furnace (EAF)-based steel production. Commonly, for the use of carbon sources in EAFs, one of the important properties is the content of fixed carbon, the release of volatiles as well as the elemental composition of inorganics. The properties of six carbon sources were analyzed by determining the proximate analysis, X-ray fluorescence analysis (XRF), coke reactivity index (CRI), and strength after reaction with CO2 (CSR), Brunauer–Emmett–Teller (BET) specific surface area and Barrett–Joyner–Halenda (BJH) pore size and volume analysis, ash chemical analysis, optical and scanning microscopy, Raman spectroscopy and X-ray diffraction (XRD) analysis. The results indicate biocoke as a promising option to replace conventional carbon-bearing sources. In the sample set, the fixed carbon, volatiles, and ash content of the biocokes were similar despite the total difference in additives. Additionally, the use of additives did not significantly affect the biocoke reactivity indices, but slightly decreased the strength after the reaction with CO2. Carbon-bearing sources have been characterized in terms of their structural properties. XRD analysis revealed that the amount of disordered carbon increased in the order: coke < calcined petroleum coke ~ biocoke (3 wt.% torrefied wood) < biocoke (3 wt.% petroleum coke + 3 wt.% charcoal) < biochar. The results obtained on the physical, chemical, and structural properties of carbon sources are the basis for further research on the behavior of slag foaming.

How to reduce the energy consumption of the rotary kiln-electric furnace (RKEF) process has become an important issue for the stainless steel industry. The aim of this study is to reduce the energy consumption of ferronickel production from saprolite nickel laterite in the RKEF process. The effects of the slag binary basicity, FeO content, and Cr 2 O 3 content on the melting temperature and electric conductivity of the slag as well as the effects of coal dosage, smelting temperature, smelting time, and binary basicity on the smelting process, within the new slag system of CaO–MgO–SiO 2 –Al 2 O 3 –FeO–Cr 2 O 3 , have been systematically investigated. It was found that properly increasing the binary basicity and FeO content of slag tends to lower smelting temperature and higher electrical conductivity, while decreasing the Cr 2 O 3 content is beneficial to decreasing the melting temperature of slags as well as the electrical conductivity. Through the optimization of slag composition and smelting parameters, ferronickel with 22.11% Ni, 77.24% Fe, and 0.08% Cr can be obtained at corresponding recovery rates of 99.17%, 28.01%, and 0.54%, respectively, under the conditions of 0.2 binary basicity, coal dosage of 14% at 1550 °C for 30 min based on the guidance of 9.4% CaO-18.2% MgO-47% SiO 2 -3.4% Al 2 O 3 -20% FeO-2.0% Cr 2 O 3 slag system. In addition, the main phase composition of slags obtained is mainly composed of forsterite, hortonolite, enstatite, diopside, and melilite, which have a lower melting point than contrast the slag from industrial production site with the main phase of pyroxene and magnesioferrite olivine. So, the new slag system is helpful for reducing the temperature and time of smelting, and reducing the energy consumption of the RKEF process. Graphical Abstract