DMREF/GOALI/Collaborative Research: High-Throughput Simulations and Experiments to Develop Metallic Glasses

Yale University, New Haven CT

Investigators

Abstract

Non-Technical Description: The increasing demand for higher performing materials across many fields requires the development of ever more complex materials. In this project a novel materials discovery methodology will be developed based on advances in combinatorial computational thermodynamics and experimental techniques. Bulk metallic glasses will be taken as example materials because of their technological potential - they can be considered high-strength metals that can be formed like plastics - and their suitability for the development of a general methodology. Many alloys - on the order of thousands - will be synthesized and characterized simultaneously. The ability of these alloys to be deformed, a property that correlates with the glass forming ability, will be measured experimentally. The crystalline phases competing with the glassy phase will also be characterized. These crystalline phases will be compared with atomic modeling results considering the energy of many possible crystalline phases. Since direct modeling of the glass forming ability is not possible from first principles, correlations will be established between the experimental glass forming ability and the competing crystalline phases from atomic modeling. The development of such a methodology and correlation through this research will accelerate the pace of discovery and deployment of advanced materials. Specifically for bulk metallic glasses, the potential development of technologically relevant alloys, particularly those that are based on Cu or Al can be expected to have a lasting impact on society. Technical Description: This objective will be realized through an integrated approach of combinatorial ab-initio simulations, combinatorial synthesis of sputtered composition spreads, and high-throughput characterization methods. To massively parallel synthesize complex alloy systems comprising ~1,000 alloys, this research uses combinatorial magnetron sputtering. Compositional libraries will be characterized using specific high-throughput methods for measuring liquidus temperature, formability, thermal, and structural properties. Within such an approach a vast amount of experimental and computational data will be generated, which will be data-mined to identify correlations. Rather than trying to directly simulate glass formation, the strategy will be to integrate experiments and computations to understand which structural and energetic aspects of the liquid and competing crystalline state best correlate with glass forming ability. Identifying correlations is a key aspect of the research and these correlations will be used to search for new glass forming compositions through combined computational and experimental means.