Complex element coupling

Increasing chemical complexity expands the design space and drives the coupling of materials science and computational techniques.

Materials design has largely expanded to multiple compositions, which requires the mixing of an increasing number of elements. In this joint Focus issue with Nature Materials, we take a closer look at the role of computational methods for guiding exploration within such vast chemical spaces.

Zhi-Wei Shan, a professor at Xi’an Jiaotong University (School of Materials Science and Engineering), talks to Nature Materials about the non-negligible impact of trace impurities in metallic structural materials.

Machine learning models have been widely applied to boost the computational efficiency of searching vast chemical space of compositionally complex materials. This Perspective summarizes the recent developments and proposes future opportunities, such as the physics-informed machine learning models.

Complex materials offer promises for exotic materials properties that enable novel applications. Nevertheless, there are numerous computational challenges for a rational design of defects in such materials, thus inspiring opportunities for developing advanced defect models.

The computational characterization of short-range order in compositionally complex materials relies on effective interatomic potentials. In this Review, challenges and opportunities in developing advanced potentials for such systems are discussed, with a focus on machine learning-based potentials.

Scandium added to Al–Cu–Mg–Ag alloys leads to an in situ phase transformation of coherent Cu-rich nanoprecipitates at elevated temperature, with Sc atoms diffusing and occupying their interstitial sites. The transformed nanoprecipitates have enhanced thermal stability while maintaining a large volume fraction and these two microstructural features enable high tensile strength of the Al alloy with creep resistance up to 400 °C.

Outstanding resistance to destructive radiation damage in structural alloys is realized by ultra-high-density reversible nanoprecipitate inclusions, and the improvement is attributed to the reordering process of low-misfit superlattices in highly supersaturated matrices.

A general method by controlling reaction kinetics is proposed to synthesize 67 kinds of two-dimensional crystal with custom-made phases and compositions, in particular, Fe- and Cr-based (layered and non-layered) chalcogenides and phosphorous chalcogenides, which show interesting ferromagnetism and superconductivity properties.

High-density, highly stable coherent nanoprecipitates are created in Al alloys that enable high strength and creep resistance at 400 °C. This is realized via a growth-ledge-triggered in situ phase transformation assembling slow-diffusing solutes with high-solubility solutes into nanoprecipitates.

The cycling disordering–ordering transition of low-misfit superlattice nanoprecipitates in metallic materials continuously annihilates radiation defects via a short-range atom-reshuffling process, giving rise to high radiation tolerance.

A competitive-chemical-reaction-based growth mechanism by controlling the kinetic parameters can easily realize the growth of transition metal chalcogenides and transition metal phosphorous chalcogenides with different compositions and phases.