Architected materials play an essential role in achieving next-generation electrochemical systems with unprecedented power and energy capabilities. The geometry and chemistry of architected materials can be engineered to address key areas of performance, including electrochemical kinetics and mechanics. Electrochemical kinetics impact key metrics such as power density, efficiency, and lifetime in batteries, fuel cells, and sensors. Additionally, electrochemical reactions can dramatically change material composition, which may result in large strains (in the hundreds of percent) that cause mechanical failure. In this article, we summarize advances in energy storage offered by architected materials and highlight fabrication methods used to realize these advances. We also discuss electrochemistry as an enabling tool for architected materials with functionality beyond energy storage and sensing.

Microcrystal electron diffraction (MicroED) is a cryo-electron microscopy technique that utilizes three-dimensional nano- and microcrystals for high-resolution structure determination. These extremely small crystals are several orders of magnitude smaller than what is used in conventional x-ray diffraction experiments. MicroED is capable of providing high-quality data from samples that would otherwise be considered useless for diffraction measurements. Since its initial implementation, MicroED has been used in the fields of structural biology, chemistry, and materials science. In this article, we provide an overview of the MicroED methodology as well as examples of how MicroED in cryo-electron microscopy has been used for structure determination of a variety of samples.

This article provides an overview of emerging directions in the materials science of biointegrated electronic and microfluidic systems, as defined by technologies that are capable of supporting long-term, intimate, physical interfaces to living organisms. Here, deterministic hard/soft composite structures, including those that leverage concepts in fractal mathematics, serve as the materials foundations for diverse devices of this type. Examples of “epidermal” or skin-like electronic systems for biophysical tracking of patient conditions that range from stroke to hydrocephalus illustrate the engineering maturity and operational sophistication that is now possible. Recent ideas in soft, skin-mounted, microfluidic lab-on-a-chip systems extend the capabilities of such platforms to include biochemical assessments of physiological status via capture, storage, manipulation, and in situ detection of biomarkers in microliter volumes of sweat, collected as it emerges from the surface of the skin. The article concludes with a description of mechanically guided assembly schemes that provide access to three-dimensional, open-mesh constructs, as a frontier area of materials development in this broader area of biointegrated systems.

The high precision offered by small-scale mechanical testing has allowed the relationships between mechanical behavior and specific microstructural features to be determined to an unprecedented degree. However, of most interest to scientists and engineers is often the behavior of materials under service conditions in an extreme environment, such as high/low temperatures, high strain rates, hydrogen atmosphere, or radiation. In this article, we detail progress made to adapt nanomechanical testing systems and techniques to observe materials behavior in situ in extreme environments.

Understanding changes in chemistry, microstructure, and physical properties during synthesis, processing, testing, and even service is vital for materials design and performance. Compared to traditional postmortem material characterization tools, in situ crystallographic characterization can provide considerable data and information on evolution of chemistry, dislocations, twinning, texture, and strains when a material is under external stimuli. Neutrons especially are able to probe material bulk properties and behaviors in extreme environments, thanks to their deep penetrating power and unique sensitivity to differentiate elements from lightweight to transition-metal atoms. In this article, we introduce and describe a diffractometer named VULCAN, which is located at Oak Ridge National Laboratory. This represents a powerful tool to understand materials properties and behaviors under complex environments, in particular, at high temperatures.

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.

Structure–property relationships are the foundation of materials science and are essential for predicting material response to driving forces, managing in-service material degradation, and engineering materials for optimal performance. Elastic, thermal, and acoustic properties provide a convenient gateway to directly or indirectly probe materials structure across multiple length scales. This article will review how using the laser-induced transient grating spectroscopy (TGS) technique, which uses a transient diffraction grating to generate surface acoustic waves and temperature gratings on a material surface, nondestructively reveals the material’s elasticity, thermal diffusivity, and energy dissipation on the sub-microsecond time scale, within a tunable subsurface depth. This technique has already been applied to many challenging problems in materials characterization, from analysis of radiation damage, to colloidal crystals, to phonon-mediated thermal transport in nanostructured systems, to crystal orientation and lattice parameter determination. Examples of these applications, as well as inferring aspects of microstructural evolution, illustrate the wide potential reach of TGS to solve old materials challenges and to uncover new science. We conclude by looking ahead at the tremendous potential of TGS for materials discovery and optimization when applied in situ to dynamically evolving systems.

A fundamental design rule that nature has developed for biological machines is the intimate correlation between motion and function. One class of biological machines is molecular motors in living cells, which directly convert chemical energy into mechanical work. They coexist in every eukaryotic cell, but differ in their types of motion, the filaments they bind to, the cargos they carry, as well as the work they perform. Such natural structures offer inspiration and blueprints for constructing DNA-assembled artificial systems, which mimic their functionality. In this article, we describe two groups of cytoskeletal motors, linear and rotary motors. We discuss how their artificial analogues can be built using DNA nanotechnology. Finally, we summarize ongoing research directions and conclude that DNA origami has a bright future ahead.

Vaporizing foil actuator welding is a form of impact welding, which can be carried out without the use of chemical explosives. Operating at smaller length scales, but with similar driving pressures as explosive welding, vaporizing foil actuator welding is capable of welding a wide variety of advanced and dissimilar metal combinations. With negligible heating developing during the process, thermal distortion does not occur, and the base-metal properties are retained in the weld. In this article, vaporizing foil actuator welding of an automotive grade aluminum and steel pair is discussed. A currently functional and complete welding system that can be used for research as well as low volume production is also discussed.

This article addresses why biomaterials are a growing part of materials science. We consider two areas at two different scales. At the nanometer scale, enzymes are heterogeneous nanoparticles of extraordinary deformability; this property allows us to view biomolecules informed by concepts of materials science and nonlinear physics. A degree of universality in the mechanical behavior of the molecules appears in the ubiquitous softening transitions; some results obtained dynamically by nanorheology, and others obtained in equilibrium experiments through the method of the DNA springs are summarized. These soft molecules represent an opportunity for studies of dissipation at the atomic scale. At the mesoscopic scale, composite functional materials with biological components hold promise for applications such as low power, chemically driven, biodegradable devices. A concrete example, and a program for the future, is the artificial axon. It is a synthetic structure that supports action potentials based on the same physical mechanism as the voltage spikes in nerve cells. A network of such axons, which is yet to come, would constitute an artificial brain. Beyond device applications, the focus here is on the basic science, namely, a constructivist approach to cybernetics, algorithmic mathematics, and the brain.

Silk and carbon nanomaterials, such as graphene oxide, graphene, and carbon nanotubes, have complementary mechanical properties that feature superior toughness and strength, respectively. Different strategies have been devoted to developing silk/carbon nanocomposites, but challenges remain to fully integrate the mechanical advantages of these two components into one synergistic material system. In this article, we provide a critical summary of structure–mechanics relationships in silk/carbon nanocomposites and highlight the impact of the interaction between silk and carbon nanomaterials on mechanical properties of the hybrid materials. We describe the challenges involved and directions for future designs of silk/carbon nanocomposites.

High-current switching performance of ovonic threshold switching (OTS) selectors have successfully enabled the commercialization of high-density three-dimensional (3D) stackable phase-change memory in Intel’s 3D Xpoint technology. This bridges the huge performance gap between dynamic random access memory (DRAM) and Flash. Similar to phase-change memory, OTS uses chalcogenide-based materials, but whereas phase-change memory reversibly switches between a high-resistance amorphous phase and a low-resistance crystalline phase, OTS freezes in the amorphous phase. In this article, we review recent developments in OTS materials and their performance in devices, especially current density and selectivity. Advantages and challenges of OTS devices in the integration with the phase-change memory are discussed. We introduce the evolution of theoretical models for explaining the OTS behavior, including thermal runaway, field-induced nucleation, and generation/recombination of charge carriers.

The water and energy sectors of an economy are inextricably linked. Energy is required in water production, distribution, and recycling, while water is often used for energy generation. In many geographical locations, the energy-water nexus is exacerbated by the shortage of both fresh water resources and energy generation infrastructure. New materials, including metamaterials, are now emerging to address the challenges of providing renewable energy and fresh water, especially to off-the-grid communities struggling with water shortages. Novel nanomaterials have fueled recent technology breakthroughs in solar water desalination, fog and dew collection, and cloud seeding. Materials for passive thermal management of buildings and individuals offer promising strategies to reduce the use of energy and water for heating and cooling. While many challenges remain, emerging materials and technologies improve sustainable management of water and energy resources.

A quantum computer can outperform classical computers for certain tasks. The general challenge to realize a quantum computer is to solve decoherence, which is due to coupling of a quantum state with the local environment. One possible way to overcome decoherence is to use a topological quantum state. Topologically protected states are expected to have long coherence times. In a topological quantum computer, the information is carried by nonlocal Majorana states. Such states can be engineered in a semiconductor nanowire, which has strong spin–orbit interactions, coupled to a superconductor. The first signatures of Majorana states have been observed recently. In order to substantiate the existence of Majorana states and use them as qubits, an exchange—or braiding—operation of these states has to be performed. The current challenge is to improve the quality of the materials and interfaces. Recent progress toward improved Majorana signals using materials science advances is reviewed in this article.

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.

Far-from-equilibrium systems are ubiquitous in nature. They are also rich in terms of diversity and complexity. Therefore, it is an intellectual challenge to be able to understand the physics of far-from-equilibrium phenomena. In this article, we revisit a standard tabletop experiment, the Rayleigh–Bénard convection, to explore some fundamental questions and present a new perspective from a first-principles point of view. We address how nonequilibrium fluctuations differ from equilibrium fluctuations, how emergence of order out of equilibrium breaks symmetries in the system, and how free energy of a system gets locally bifurcated to operate a Carnot-like engine to maintain order. The exploration and investigation of these nontrivial questions are the focus of this article.

The effort to develop metallic alloys with increased structural strength and improved radiation performance has focused on the incorporation of either solute elements or microstructural inhomogeneities to mitigate damage. The recent discovery and development of single-phase concentrated solid-solution alloys (SP-CSAs) has prompted fundamental questions that challenge established theories and models currently applicable to conventional alloys. The current understanding of electronic and atomic effects, defect evolution, and microstructure progression suggests that radiation energy dissipates in SP-CSAs at different interaction strengths via energy carriers (electrons, phonons, and magnons). Modification of electronic- and atomic-level heterogeneities and tailoring of atomic transport processes can be realized through tuning of the chemical complexity of SP-CSAs by the selection of appropriate elements and their concentrations. Fundamental understanding of controlling energy dissipation via site-to-site chemical complexity reveals new design principles for predictive discovery and guided synthesis of new alloys with targeted functionalities, including radiation tolerance.

Density functional theory (DFT) has proved to be exceptionally successful in rationalizing trends in activity and functionality for electrochemical functional materials. With continued increases in computing power, there has been an increased interest in “high-throughput” materials discovery and design based on a few descriptors to scan the phase space en masse for thousands of potential candidates, which could be made technologically and commercially viable. However, given fundamental accuracy limitations associated with DFT, the success of high-throughput material discovery efforts has been limited. In this review, we suggest an additional dimension to aid in high-throughput material discovery related to uncertainty quantification and propagation, which provides a more realistic picture of the likelihood of new candidate materials to improve upon known materials. We demonstrate the approach and its utility through two case studies: (1) electrocatalyst materials for their activity and selectivity for the oxygen reduction reaction, and (2) cathode materials for Li-ion batteries based on Ni-Mn-Co oxides. The ease with which uncertainty quantification and propagation can be incorporated into traditional high-throughput material discovery with almost no additional computational cost allows for its proposed wide usage.