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Decarbonising the StainlessSteelmaking through Alloy Solutions

Time: Wed 2023-06-14 09.00

Location: F3, Lindstedtsvägen 26 & 28, Stockholm

Video link:

Language: English

Subject area: Materials Science and Engineering

Doctoral student: Wenjing Wei , Processer

Opponent: Dr. Birat Jean Pierre,

Supervisor: Professor Pär Jönsson, Processer; Dr Peter Samuelsson, Processer


To reach the goal of the Paris Agreement, the reduction of greenhouse gas emissions (GHG)is becoming one of the most pressing issues in the world today. Unlike most other sectors, thestainless steel industry has a significantly higher burden from upstream emissions comparedto operational emissions. The main contributing source of these upstream emissions instainless steelmaking is the use of alloy materials (Mo, Ni, Cr, etc.), accounting forapproximately 70% of the total stainless steel’s CO2 emissions. The thesis provides insights into the decarbonisation of stainless steelmaking through alloy solutions. In order to producea sustainable stainless steel product of high quality, it is necessary to establish decarbonisationstrategies using an interactive optimization framework that considers material, process, andquality factors.

First, this is to select low-carbon footprint alloys, which helps to reduce the overall upstreamemissions of the stainless steel production process. In Part I-Material Selection Optimization,the production of FeMo, Ni alloy, and HC FeCr has been assessed through LCA based energyand GHG emissions. The inventory data is calculated by using a static thermodynamic modelbased on mass and energy conservation. The results reveal the following low-carbon alloyoptions: 1) FeMo produced as a co-product from copper mine; 2) nickel metal processed withsulfide ore using a flash smelting process and 3) HC FeCr produced using a closed submergedarc furnace with preheating.

The next step is to set up a reliable process model to predict the desired alloy content forprocess optimization. This enables a reduction of the waste, GHG emissions and productioncosts. Nitrogen, as an important alloy element in stainless steel, is normally added by injectingnitrogen gas into the AOD process. In Part II-Process Parameter Optimization, a timedependent thermodynamic model, TimeAOD3TM, was proposed to predict the dissolvednitrogen content in the bath. The model provides good predictions of the nitrogen contentduring the reduction and desulfurization stages. The higher deviation between modelling andmeasurement during the decarburization stage is mostly due to the limitation of the one-cellmodel in which the same total pressure is used for the nitrogen and carbon equilibriumreactions. The improvement of the model requires implementing different gas pressures tocalculate the equilibrium reactions of N and C, as well as considering the kinetic mechanismsof the reactions. To further improve the modelling accuracy of nitrogen, the blown gas mixturein the AOD nozzle was studied by using a kinetic CFD model. The results show that thepressure at the inlet is a crucial parameter for controlling the process, as it impacts theproperties of the gas that is released from the nozzle, including its velocity, density,temperature, flow rate and outlet pressure. With the proposed model, it is possible to capturethe relevant gas properties under a variety of different conditions. Moreover, the predictionof the gas flow’s critical state allows for optimizing the blowing process, which can helpreduce the resources (material, energy) usage and lower the environmental impact.

The final step is to ensure that the final steel product meets the requisite quality standards,including the material properties and the environmental impacts. In Part III-Steel QualityOptimization, these quality-related performances are optimized through a statisticalmodelling approach, named a Taguchi based Grey Relational Analysis. This approach wasused to rank multiple performances and to determine the optimal steel design related to alloycontents. The results show that nitrogen plays the most important role in determining thesteel’s combined performance, because it appears in the empirical equations for the pittingcorrosion resistance, proof strength, and tensile strength. Also, the coefficient of nitrogen ismuch higher than the coefficients of other alloy elements, which can significantly influencesteel performance. In addition, the optimum steel designs consist of high contents of nitrogen,chromium, molybdenum, copper and low contents of nickel.

The findings of this research provide the fundaments for decarbonisation of the stainlesssteelmaking, highlighting the need for a holistic approach that considers material, process,and product quality in reducing carbon emissions.