Design of polycrystalline metallic alloys under multi-scale uncertainty by connecting atomistic to meso‑scale properties

Uncertainty quantification plays a pivotal role in advancing the development of reliable and high-performance material designs via multiscale materials modeling. This study focuses on modeling the uncertainty of meso‑scale mechanical properties, e.g. modulus of elasticity and yield strength of Ti-7Al, by incorporating the inherent randomness of substitutional atoms of the alloy and its microstructural texture. A molecular dynamics approach is employed to probe the epistemic uncertainty of single-crystal properties. Moreover, the aleatoric uncertainty is quantified using the experimental microstructural texture data of a previous investigation. The propagation of the epistemic and aleatoric uncertainty on the homogenized properties is investigated using an analytical uncertainty quantification method. Subsequently, the Ti-7Al alloy microstructures are designed to improve meso‑scale mechanical properties under uncertainty by integrating the analytical method into the optimization scheme.