Atomistic scale simulation of the magnetic anistropy in steels

Steel is the most used material globally by value and one of the most recyclable materials, making it a vital foundation industry. Greater monitoring and digitalisation of the production process through diverse sensing and data collating capabilities (i.e. industry 4.0 approach) will support greater sustainability of the industry. There is an increasing demand for online microstructure control, particularly for high value steels, which allows for better quality, productivity, the profitability of the company, and reduces the downgrading and scrapping, resource use and energy consumption. 

Having sensor signal records that represents the steel microstructure at the end of the process provides a powerful digital tool for through process modelling and manufacturing informatics. Electromagnetic sensors have shown significant potential in characterising microstructure in hot strip mills and correlating to mechanical properties in the cold mill. To explore the full potential for greater use of the EM techniques, the complex relationship between the magnetic measurements and key microstructural parameters needs to be understood. The proposed research focuses on individual microstructural parameter and developing fundamental atomic level modelling capability to relate texture to magnetic properties and generate valuable magnetic parameter data for crystallographic anisotropy in steels that will support the use of EM sensors for texture characterisation online in steel mills. Whilst this project focuses on one application sector, the research is also highly interdisciplinary and involves a variety of areas such as metallurgy, electromagnetics, modelling and simulation. The atomistic modelling technique and the approach of applying its outcome to meso/macro scale models can be applied to mechanical, thermal and electrical properties modelling across a range of foundation industry sectors.

Lei Zhou

University of Warwick