Multiscale Sciences in Materials Discovery and Development

The ability to quantify and understand cause and effect relationships between various scales of hierarchy of material structure and material properties is key to design and development of new and improved materials.  Both experiments and computational simulation at and across various length and time scales are essential to understanding mechanisms that affect material responses.  There is typically considerable uncertainty in muiltiscale process-structure-property relations across length and time scales.  Systems engineering approaches and modern data sciences offer powerful additional means to accelerate the rate of materials discovery and development, including digital representations of structures, data analytics, data mining, and machine learning for process-structure and structure-property relations.

The Institute of Materials is helping to define the Materials Innovation Ecosystem at Georgia Tech and more broadly in the US by investing in materials data sciences and informatics approaches to pursue e-collaborations and advanced correlations between structure and properties.  These approaches are being applied through seed funding, graduate level course in materials informatics, and a joint IMat-College of Computing NSF IGERT program FLAMEL to educate and train the future workforce in data sciences and informatics at the intersection of materials and manufacturing.  These initiatives are being applied to broad ranges of material classes, from structural metals and composites to nematic crystals, to materials and interfaces for catalysis, to thermoplastic polymers, to extrusion membranes, nanoporous foams, to thin film transistors and nanowires.

Furthermore, a web-based platform MATIN is being developed to facilitate e-collaboration of distributed research teams, including advanced data representation, data analytics and correlations, and tracking of collaborative workflows.  These activities represent a strong vision and strategy to take advantage of explosive advances in big data and open source web applications in advancing 21st century multiscale materials science.