We perform basic research on understanding the process-structure-property linkages by developing predictive tools. These predictive tools include multi-physics software for studying the process-structure-property relationships spanning length scales from nanometers to meters, and machine learning for the statistically driven process-structure-property relationships to enable optimization of materials and manufacturing processes to yield high quality and high-performance components to be used in space and on earth.