Integrated Computational Engineering of High-performance Alloys


SNIC 2016/34-51


SNAC Large

Principal Investigator:

Pavel Korzhavyi


Kungliga Tekniska högskolan

Start Date:


End Date:


Primary Classification:

20506: Metallurgi och metalliska material

Secondary Classification:

10402: Fysikalisk kemi

Tertiary Classification:

10304: Den kondenserade materiens fysik




The proposed multi-disciplinary research studies planned within this Large-scale allocation project will be in the field of Computational Materials Science. They are related to several active projects funded by Swedish and European Research Foundations: - • Hierarchic Engineering of Industrial Materials “Hero-m 2 Innovation” (Vinnova Competence Center 2016-00668), 2017-2022. Funding source: VINNOVA; - ALUminium oXider för processer och produkter (SSF RMA11-0090 "ALUX"), 2013-2017. Funding source: SSF; These long-term Consortia, as well as several short-term research projects, are supported by and involve industrial partners such as Thermo-Calc Software, Sandvik, SKB, and Sapa Technology. In addition, we have filed several applications to Swedish funding agencies such Vetenskapsrådet and Carl Tryggers Foundation. If granted, these projects will also require computational resources starting from January 2017. All the planned computational activities are linked to the planned experimental work conducted by our partners within the Consortia at KTH (several groups at Main Campus and one in Kista), Chalmers, and Lund University. The project is concerned with theoretical and computational studies of industrially relevant materials starting from their electronic and atomic structure and involving all the relevant length- and time-scales. The main goal is to investigate defects (from 0D point defects to 2D planar defects such as surfaces and interfaces), defect interactions, and defect arrangements in the main phases of industrially relevant materials such as steels, aluminum and copper alloys, and ceramic materials. These studies are to provide data on the atomic-level structures and mechanisms that are important for understanding and controlling the thermodynamic, mechanical, and kinetic properties of the studied materials. We adopt an integrated computational modeling approach based on quantum mechanics and statistical physics, starting from electronic and atomic levels and passing the data to semi-discrete and continuum methods that operate at longer length- and time-scales. Within this approach, we have developed efficient theoretical tools for describing the thermodynamic and kinetic properties of materials at elevated temperatures. These methods enable computer-aided optimization of the compositions and the heat treatment of new grades of steel, superalloys, and refractory ceramics, in order adapt these materials to novel applications in which an unusual combination of properties may be required.