This article reviews the concept of metastability in alloy design. While most materials are thermodynamically metastable at some stage during synthesis and service, we discuss here cases where metastable phases are not coincidentally inherited from processing, but rather are engineered. Specifically, we aim at compositional (partitioning), thermal (kinetics), and microstructure (size effects and confinement) tuning of metastable phases so that they can trigger athermal transformation effects when mechanically, thermally, or electromagnetically loaded. Such a concept works both at the bulk scale and also at a spatially confined microstructure scale, such as at lattice defects. In the latter case, local stability tuning works primarily through elemental partitioning to dislocation cores, stacking faults, interfaces, and precipitates. Depending on stability, spatial confinement, misfit, and dispersion, both bulk and local load-driven athermal transformations can equip alloys with substantial gain in strength, ductility, and damage tolerance. Examples include self-organized metastable nanolaminates, austenite reversion steels, metastable medium- and high-entropy alloys, as well as steels and titanium alloys with martensitic phase transformation and twinning-induced plasticity effects.

Predicting the structural response of advanced multiphase alloys and understanding the underlying microscopic mechanisms that are responsible for it are two critically important roles that modeling plays in alloy development. The demonstration of superior properties of an alloy, such as high strength, creep resistance, high ductility, and fracture toughness, is not sufficient to secure its use in widespread applications. Still, a good model is needed to take measurable alloy properties, such as microstructure and chemical composition, and forecast how the alloy will perform in specified mechanical deformation conditions, including temperature, time, and rate. Here, we highlight recent achievements using multiscale modeling in elucidating the coupled effects of alloying, microstructure, and mechanism dynamics on the mechanical properties of polycrystalline alloys. Much of the understanding gained by these efforts relies on the integration of computational tools that vary over many length scales and time scales, from first-principles density functional theory, atomistic simulation methods, dislocation and defect theory, micromechanics, phase-field modeling, single crystal plasticity, and polycrystalline plasticity.

Historically, the advent of robotics has important roots in metallurgy. The first industrial robot, Unimate, was used by General Motors to handle hot metal—transporting die castings and welding them to an automotive body. Now, nearly 60 years later, metallurgical use of robotics is still largely confined to automation of dangerous, complex, and repetitive tasks. Beyond metallurgy, the field of autonomy is undergoing a renaissance, impacting applications from pharmaceuticals to transportation. In this article, we review the emerging elements of high-throughput experimental automation, which, when combined with artificial intelligence or machine-learning systems, will enable autonomous discovery of novel alloys and process routes.

Over the past three years, my colleagues and I have embarked on an exciting journey into electric-field control of magnetism, parts of which we describe in this article. What we present to you is something that we believe is extremely exciting from both a fundamental science and applications perspective, and has the potential to revolutionize our world. Needless to say, this will require a lot of new innovations, both in the fundamental science arena as well as translating scientific discoveries into real applications. We hope this article will help spur more research in electric-field control of magnetism within the broad materials community.

The discovery, design, and development of new alloys have long been critical elements of advanced engineering systems. Challenged by their chemical and structural complexity, this design process is, however, often too slow. This article highlights progress in theory, computation, data, and advanced experimental techniques that are advancing our capabilities for rapid discovery and design of new multicomponent alloys. Applied across the length scales, these new capabilities support exploration across broad composition spaces; examples of new materials and associated advances in the understanding of underlying thermochemical and thermomechanical phenomena are presented. We highlight current challenges, gaps, and specific areas that, if further developed, could have future high payoff.

Modern approaches to alloy design increasingly exploit the framework of computational thermodynamics and kinetics to guide the selection of alloy compositions and processing strategies, to achieve desired microstructures, and yield tailored properties. In this context, phase diagrams play a critical role and their assessment can represent a bottleneck in the design of new multicomponent systems. In recent years, it has become possible to accelerate this process through the coupling of the CALculation of PHAse Diagram (CALPHAD) computational thermodynamics framework with high-throughput quantum mechanical calculations. This article reviews recent developments and applications in this area, and discusses future opportunities for high-throughput calculations in the context of modeling kinetics, highlighting the important role of interfacial processes and atomic mobilities.

We highlight the current understanding of mechanisms of phase transformation, strengthening, and the role of alloying elements in aluminum, magnesium, and titanium alloys, including nucleation and growth of precipitates, precipitate–dislocation interactions, solute segregation at precipitate–matrix interfaces and planar defects, and the development of strengthening models that account for the real particle shape. Future directions such as atomic-scale elemental mapping and computation, and the influence of particle shape on mechanical properties are discussed. With the combination of advanced characterization and computational tools, it is anticipated that much less time will be needed to develop the next generation of light alloys.