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

非技术进步需要更高性能的材料，这通常是通过增加材料的复杂性来实现的。一类新的材料，称为“高熵合金”，由至少5种成分组成，是这一趋势的例证。这与传统的合金不同，传统的合金通常由一种主要元素和只有一小部分其他成分组成。从潜在的巨大成分空间中识别出这些材料一直是一个挑战。用理论或与先验已知信息的关联来处理这个巨大的组成空间一直是非常有限的。在这项工作中，将采用一种新的组合策略。这种方法将允许同时考虑~1000种合金，从而产生前所未有的数据量。所有数据将通过在线数据存储库公开共享。这种数据的快速生成和开放共享将使科学界能够为理解并最终开发新材料发展更好的理论。更广泛地说，拟议的战略为材料研究提供了一种新的方法，在这种方法中，整个科学界都可以访问持续测量的大量数据。参与该项目的学生将接受这种开放式材料科学方法的培训，这将极大地有助于培养其领域尖端的下一代科学家。技术摘要高熵合金(HEAs)在等原子或近等原子成分下形成单相固溶体。这一设计原则通过将我们的注意力从相图的角落转向中心，为合金的发现提供了一个新的视角。一系列前景看好的机械性能推动了人们对HEAS的技术兴趣。然而，在潜在的巨大组成空间中识别家用电器一直是一项具有挑战性的工作。用第一原理理论或与先验已知信息的关联来处理这一巨大的组成空间一直是非常有限的。由于潜在的组成空间广阔，可预测性较弱，因此将采用组合策略。这种方法将允许同时考虑~1,000种合金，从而产生前所未有的数据量。所有数据将通过在线数据存储库公开共享。这种数据的快速生成和开放共享将使科学界能够开发出更好的理论来理解形成主题并最终预测HEA。更广泛地说，拟议的战略为材料研究提供了一种新的方法，在这种方法中，整个科学界都可以访问持续测量的大量数据。参与该项目的学生将接受这种开放式材料科学方法的培训，这将极大地有助于培养其领域前沿的下一代科学家。作为一种高通量的材料合成方法，组合溅射被用来建立大量的~1000合金。使用快速筛选、化学分析和结构分析来表征库中的合金。在这个项目中，总共将制造100,000多种合金，并确定相边界。这些数据将经过整理，并通过材料地图集项目在线储存库与社区共享。精选的数据集将指示单相固溶体的组成空间、多相区的组成空间以及它们的边界。对数据的挖掘将用于确定合金和合金成分的性能之间的相关性。基于这种相关性，可以检验现有的理论并开发新的理论。例如，量化焓基序是否以及何时可以被熵效益覆盖，例如，抑制相分离。

Non-technical AbstractTechnological 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 AbstractHigh 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.