Process-structure Linkages with Materials Knowledge Systems

1 Heirarchical Materials Structure at Multiple Length Scales a). Ide-alized graphene crystalline structure. b). Atomic model for a five-fold icosahedral Al-Ag quasicrystals. c). Delamination cracks in h-BN particles subjected to compressive stress in the (0001) planes (within a silicon nitride particulate-reinforced silicon carbide composite. d). Electron diffraction pattern of an icosahedral Zn-Mg-Ho quasicrystal. e). Spherulites in in poly-3-hydroxy butyrate (PHB) f). Cast iron with magnesium induced spheroidised graphite. h). Cross-section of an aluminium casting g). As-cast wrought-grade aluminium alloy (Al-Mg-Fe-Si) i). Metal component. j). Automotive engine. Structure images courtesy of Core-Materials [1]. 2 The MKS Homogenization workflow (left) consists of four steps. 1. Discretize the raw microstructure with the microstructure function. 2. Compute 2-point statistics to create a natural origin. 3. Create low dimensional microstructure descriptors using dimensionality reduction. 4. Calibrate structure-property linkage with low dimensional microtructure descriptors and effective properties using machine learning. The MKS Localization workflow (right) consists of 2 steps. 1. Discretize the raw microstructure with the microstructure function. 2.