{"title":"Nitrogen Diffusion in Vacancy-Rich Ferrite and Austenite, from First Principles to Applications","authors":"A. Karimi, M. Auinger","doi":"10.2139/ssrn.3694759","DOIUrl":null,"url":null,"abstract":"This work contains a systematic study of the diffusion of nitrogen in Ferrite (α Fe, BCC) and Austenite (γ Fe, FCC) from first principles, using a robust multi scale model which combines Density Functional Theory (DFT) and Kinetic Monte Carlo (KMC). Both ferromagnetic BCC and non-magnetic FCC iron are considered using DFT to drive a diffusion model, which shows strong agreement with experimental diffusion data in literature. Further, quantified predictions are calculated for nitrogen diffusion in iron crystals which are vacancy-rich. In particular, it was found that an extended diffusion coefficient of nitrogen can be expressed as a function of nitrogen and vacancy concentration by fitting polynomial coefficients. These are calculated within the 100◦C < T < 1500◦C temperature range, and 0.01 at.% < cN < 10.0 at.% nitrogen concentration range. Such insights in vacancy-rich crystals may be useful to nitriding manufacturers, as enhanced diffusion models are an important factor in improving existing processes and avoiding common manufacturing problems such as the egg-shell-effect.","PeriodicalId":11974,"journal":{"name":"EngRN: Engineering Design Process (Topic)","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EngRN: Engineering Design Process (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3694759","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This work contains a systematic study of the diffusion of nitrogen in Ferrite (α Fe, BCC) and Austenite (γ Fe, FCC) from first principles, using a robust multi scale model which combines Density Functional Theory (DFT) and Kinetic Monte Carlo (KMC). Both ferromagnetic BCC and non-magnetic FCC iron are considered using DFT to drive a diffusion model, which shows strong agreement with experimental diffusion data in literature. Further, quantified predictions are calculated for nitrogen diffusion in iron crystals which are vacancy-rich. In particular, it was found that an extended diffusion coefficient of nitrogen can be expressed as a function of nitrogen and vacancy concentration by fitting polynomial coefficients. These are calculated within the 100◦C < T < 1500◦C temperature range, and 0.01 at.% < cN < 10.0 at.% nitrogen concentration range. Such insights in vacancy-rich crystals may be useful to nitriding manufacturers, as enhanced diffusion models are an important factor in improving existing processes and avoiding common manufacturing problems such as the egg-shell-effect.