Computational Design of Alloys for Energy Technologies

Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. In 2017, the US Department of Energy, Office of Fossil Energy and Carbon Management, launched the eXtremeMAT (XMAT) consortium of seven national laboratories to bring together state-of-the-art microstructure-based computational modeling, data science, and cutting-edge experimental tools across the National Laboratory enterprise, in conjunction with industry partnership, to accelerate development and deployment of new heat-resistant alloys. In "Predictive crystal plasticity modeling of single crystal nickel based on first-principles calculations," the multiple scales that govern mechanical behavior of alloys are linked by Qin et al. using a computational approach in which elastic strains imposed during the calculation of ideal shear strength are combined with a model for the evolution of the overall dislocation network to predict hardening at larger strains in single-crystal Ni. [...]in "Crack formation in chill block melt spinning solidification process: a comparative analysis using OpenFOAM®," Pagnola, Barcelo and Useche used CFD with the volume of fluid model to study bubble formation for two non-isothermal, immiscible, and compressible fluids.