journal article·2021-02-23

Data-Driven Discovery and Understanding of Ultrahigh-Modulus Crystals

Qian Shao, Ruishan Li, Zuogong Yue, Yanlei Wang, Enlai Gao

Chemistry of Materials· Volume 33· Issue 4
Publisher page

Abstract

High-modulus materials that yield small elastic deformation under mechanical loads hold great promise for use in a wide range of engineering applications. However, the discovery and understanding of high-modulus materials remain a long-term challenge, as the traditional experimental trial-and-error approach is time-consuming. In this work, we discovered two new ultrahigh-modulus crystals (CN2 and OsN2), exhibiting a maximum Young’s modulus (1555.3 and 1382.7 GPa, respectively) greater than that of diamond (1152.0 GPa in our calculations), by data mining of 13 122 crystals and first-principles verifications. More surprisingly, the density of CN2 is lower than that of diamond, which endows it with high modulus and light weight. Furthermore, we explored the mechanical behaviors of the discovered ultrahigh-modulus crystals by performing tensile tests and found that CN2 and OsN2 also boast high strength while maintaining decent ductility. The underlying mechanism for the ultrahigh modulus of these two crystals was explained by analyses of the electron density and bond order. To further broaden our understanding, a data-driven analysis was conducted to quantify the structure–modulus correlations of 10 903 crystals, and six crucial structural and compositional features that are highly correlated to the maximum Young’s moduli of crystals were identified. Based on these six features, a nonlinear classifier was developed, which successfully predicted crystals possessing a maximum Young’s modulus greater than 1000 GPa and separated them from the others, making this approach useful for falsifiable prediction and discovery of high-modulus crystals. Based on this understanding, suggestions were made to guide the design and synthesis of high-modulus crystals. Additionally, the formation and stabilities of CN2 and OsN2 were explored for practical applications.
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Research context

OpenAlex topics: Electronic and Structural Properties of Oxides · X-ray Diffraction in Crystallography · Machine Learning in Materials Science

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Engineering Mechanics, School of Civil Engineering, Wuhan University, Wuhan, Hubei 430072, China

School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW 2052, Australia

Beijing Key Laboratory of Ionic Liquids Clean Process, CAS Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China

Innovation Academy for Green Manufacture, Chinese Academy of Sciences, Beijing 100190, China

Funding

Natural Science Foundation of Hubei Province · National Natural Science Foundation of China

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