Combinatorial exploration of stability regions of high component single-phase solid solutions with near-equiatomic composition

Yale University, New Haven CT

Investigators

Abstract

Non-technical Abstract Technological advances require higher performing materials, which are often realized by increasing the material's complexity. A new class of materials, called "High entropy alloys" consist of at least 5 components and exemplify this trend. This is in contrast to traditional alloys that are typically composed of a principal element with other constituents in only small fractions. Identifying these materials out of the potential vast compositional space has been challenging. Addressing this vast composition space with theories or correlations with a priori known information has been very limited. In this work, a new combinatorial strategy will be employed. This approach will allow considering ~1,000 alloys simultaneously, hence generating an unprecedented quantity of data. All data will be openly shared through an online data repository. The rapid data generation and open sharing of such data will allow the scientific community to develop improved theories for understanding and eventually developing new materials. More generally, proposed strategy offers a novel approach to materials research where very large amounts of data that are consistently measured are accessible to the entire scientific community. The students involved in this project will be trained in this open approach to materials science, which will contribute greatly to the training of the next generation of scientists at the cutting edge of their field. Technical Abstract High Entropy Alloys (HEAs) form single-phase solid solutions at equiatomic or near-equiatomic composition. This design principle provides a new perspective on alloy discovery, by turning our focus away from the corner of the phase diagram towards the center. A broad range of promising mechanical properties drives technological excitement about HEAs. However, identifying HEAs out of the potential vast compositional space has been challenging. Addressing this vast composition space with first principle theories or correlations with a priori known information has been very limited. Due to the vast potential compositional space and the weak predictability, a combinatorial strategy will be employed. This approach will allow considering ~1,000 alloys simultaneously, hence generating an unprecedented quantity of data. All data will be openly shared through an online data repository. The rapid data generation and open sharing of such data will allow the scientific community to develop improved theories for understanding formation motifs and eventually predicting HEAs. More generally, the proposed strategy offers a novel approach to materials research where very large amounts of data that are consistently measured are accessible to the entire scientific community. The students involved in this project will be trained in this open approach to materials science, which will contribute greatly to the training of the next generation of scientist at the cutting edge of their field. As a high-throughput materials synthesis method, combinatorial sputtering is used to create large libraries of ~1000 alloys. Rapid screening chemical analysis and structural analysis are used to characterize the alloys within the library. Altogether, over 100,000 alloys will be fabricated and phase boundaries identified within this project. These data will be curated and shared with the community through the Materials Atlas Project online repository. Curated data sets will indicate the compositional space of the single phase solid solution, these of multiple phase regions, and their boundaries. Mining of the data will be employed to identify correlations between properties of the alloy and alloy components. Based on such correlations, current theories can be tested and new theories developed. For example, quantifying if and when enthalpic motifs can be overwritten by entropic benefits, e.g., suppression of phase separation.