Abstract

Nitriding is the most widely employed thermochemical surface treatment to enhance the mechanical properties of steel. Specifically, gas nitriding, which is a low-temperature process for efficiently producing high-performance steels, has a disadvantage in that it consumes a large amount of time. To enhance the nitriding rate, we studied the surface alloying of iron (Fe) and its effect on ammonia nitriding of Fe using a hierarchical protocol with density functional theory (DFT)-based microkinetics and real-time simulations. First, we considered the NH3 decomposition and nitrogen (N) diffusion mechanism on clean and alloyed (Fe-X) Fe (100) surfaces using DFT. In this study, the alloying elements including transition metals and period III to VI elements in the periodic table were considered for DFT-based computational screening. For the candidate Fe-X systems selected to improve the nitriding rate in the previous step, we calculated all the energy barriers for every elementary reaction step by varying the alloying elements and performed microkinetic analysis using those kinetic energy barriers to determine their influence on the nitriding rate. After adding consideration of thermodynamic factors, selected candidate alloys were subjected to detailed DFT calculations of the nitriding mechanism with N coverage, and based on these results, a kinetic Monte Carlo (kMC) simulation was performed to reconfirm the results under the actual nitriding process conditions. Through a hierarchical protocol, we performed a theoretical analysis and simulation of the effects of alloying elements on the nitriding rate that were not explained experimentally and suggested the best alloying element with the improved nitriding rate.

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