Computational Design of Materials for Sintering: Challenges and Prospects

This study discusses strategies and challenges for computational design of sintered materials. In this context, the importance of fast acting reduced order models to efficiently explore the multi-dimensional design space of materials is highlighted. The study also presents an example of a reduced order model for designing pre-alloyed powders that can be densified by using super-solidus liquid phase sintering. The design exercise is based on an integrated computational materials engineering (ICME) framework involving genetic algorithm to optimize the chemical composition of high-speed steels (HSS) to simultaneously improve the sintering response and the resultant properties. Thermodynamic simulations, based on the CALPHAD method, are used to establish microstructural constraints through phase stability at equilibrium. Results of the design exercise in comparison with conventional alloys are presented. We show that new HSS alloys with improved sintering performance can be designed while simultaneously enhancing their performance properties.