4.1 High-throughput in-situ measurements and analyses supporting model development for accelerated sustainable materials innovations
Establishing protocols and methods for CALPHAD - demonstrating the value of large LSI datasets for modelling.
Project summary
High-throughput experimental methods and combinatorial material analyses have received significant attention lately, in particular for functional materials where properties may be more directly related to the chemistry of the material. In the case of structural materials, chemistry is clearly important, but the materials processing also takes a prominent role. Computational materials design (CMD) approaches such as CALPHAD-based modelling is today well established for accelerated development of structural materials and their processes. CMD approaches can be further leveraged by feeding and validating in-situ experimental insights representative of structural evolution during processing. Large-scale infrastructures, in particular synchrotron facilities, offer a unique capability to probe structures using high-throughput approaches. However, the effective utilization of this capability requires streamlined research methods where the specimen synthesis, sample environment, data handling, data analysis, database development and model correlation are considered comprehensively. In this project, we will therefore develop such high-throughput streamlined research methods to efficiently study phase equilibria, non-equilibrium phase transformation, and precipitation of structural materials. The streamlined methods will be validated by proof-of-concept studies and high-throughput protocols that will be devised to assist all partners to take advantage of the opportunity for accelerated materials and process innovations.
Key people
Project leader: Tao Zhou (KTH)
Project partners
KTH (project lead), GKN, Outokumpu, Scania, Scatterin, Seco Tools, Siemens Energy, ThermoCalc, Sandvik Coromant, Sandvik Mining, Prevas, Ovako.