Additive manufacturing (AM) is a cutting-edge technique for constructing intricate components with unique microstructural features and strength comparable to wrought alloys. Due to their exceptional corrosion resistance and mechanical properties, duplex stainless steels (DSS) are used in a wide range of critical applications. Over the past several years, a substantial body of research has been conducted on the AM of DSS. In-depth knowledge is required to understand the complete benefits of the AM process. This review overviews the AM-processed DSS parts based on process-specific microstructural changes, mechanical behavior, electrochemical performance, and postheat treatment processes based on the classifications of directed energy deposition and powder bed fusion AM techniques along with future perspectives. Major challenges in AM of DSS are optimizing the austenite–ferrite fractions and controlling the formations of deleterious phases. This review will be extensively useful to researchers and industries working in the AM of DSS.
The microstructure and composition of the scales formed are examined after being exposed to atmosphere containing 2.0% SO2 + 5.0% O2 for 60 min in the temperature range of 900–1200 °C. The composition of the scale post-oxidation primarily varies with temperature rather than silicon content. FeS exhibits a melting temperature of 950 °C, whereas FeSi2O4 melts at 1150 °C. Two mechanisms for FeS formation are proposed. Eutectoid transformation of molten FeS occurs during subsequent cooling, resulting in lamellar FeS + Fe–S–O compounds. Above 1150 °C, the melt of Fe2SiO4 further increases the Fe diffusion rate. This dual-liquefaction mechanism involving FeS and Fe2SiO4 accounts for the anomalous oxidative mass gain observed in Fe–Si alloys exposed to a sulfur-containing atmosphere.
This work presents the development and validation of a static thermochemical model for predicting process parameters in the MIDREX shaft furnace, a method used for producing direct reduced iron from lump ore and pellets. Industrial plant data is used to validate the model. Furthermore, the model is utilized to analyze the process based on different parameters. Genetic algorithm (GA) is used to estimate the critical parameters of the process (like reaction factors and extent of reactions) and validate the model with industrial data. Further investigations are conducted to assess the possibility of replacing the reformer gas (bustle gas) with hydrogen and coke oven gas (COG) to make the process greener and almost free from carbon emissions, using a systematic approach of overall heat balance, using already developed coupled thermodynamics and kinetics-based model, and further using those data to estimate the reaction factors and extent of reactions using GA to be used in the static model. The results demonstrate the feasibility of replacing hydrogen and COG without much adverse effect on the process outcomes; however, this results in better metallization and reduced carbon footprint of the process effectively.