In situ nanomechanical testing in (scanning) transmission electron microscopy provides unique opportunities for studying fundamental deformation processes in materials. New insights have been gained by combining advanced imaging techniques with novel preparation methods and controlled loading scenarios. For instance, by applying in situ high-resolution imaging during tensile deformation of metallic nanostructures, the interplay of dislocation slip and surface diffusion has been identified as the key enabler of superplasticity. Evidence for dislocation pinning by hydrogen defect complexes has been provided by in situ imaging under cyclic pillar compression in a tunable gas environment. And, for the very first time, individual dislocations have been moved around in situ in two-dimensional materials by combining micromanipulation and imaging in a scanning electron microscope.

The field of in situ nanomechanics is greatly benefiting from microelectromechanical systems (MEMS) technology and integrated microscale testing machines that can measure a wide range of mechanical properties at nanometer scales, while characterizing the damage or microstructure evolution in electron microscopes. This article focuses on the latest advances in MEMS-based nanomechanical testing techniques that go beyond stress and strain measurements under typical monotonic loadings. Specifically, recent advances in MEMS testing machines now enable probing key mechanical properties of nanomaterials related to fracture, fatigue, and wear. Tensile properties can be measured without instabilities or at high strain rates, and signature parameters such as activation volume can be obtained. Opportunities for environmental in situ nanomechanics enabled by MEMS technology are also discussed.

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.

Many materials systems comprise complex structures where multiple materials are integrated to achieve a desired performance. Often in these systems, it is a combination of both the materials and their structure that dictate performance. Here the authors layout an integrated computational–statistical–experimental methodology for hierarchical materials systems that takes a holistic design approach to both the material and structure. The authors used computational modeling of the physical system combined with statistical design of experiments to explore an activated carbon adsorption bed. The large parameter space makes experimental optimization impractical. Instead, a computational–statistical approach is coupled with physical experiments to validate the optimization results.

Tribology—the study of contacting, sliding surfaces—seeks to explain the fundamental mechanisms underlying friction, adhesion, lubrication, and wear, and to apply this knowledge to technologies ranging from transportation and manufacturing to biomedicine and energy. Investigating the contact and sliding of materials is complicated by the fact that the interface is buried from view, inaccessible to conventional experimental tools. In situ investigations are thus critical in visualizing and identifying the underlying physical processes. This article presents key recent advances in the understanding of tribological phenomena made possible by in situ experiments at the nanoscale. Specifically, progress in three key areas is highlighted: (1) direct observation of physical processes in the sliding contact; (2) quantitative analysis of the synergistic action of sliding and chemical reactions (known as tribochemistry) that drives material removal; and (3) understanding the surface and subsurface deformations occurring during sliding of metals. The article also outlines emerging areas where in situ nanoscale investigations can answer critical tribological questions in the future.

The software package ESPEI has been developed for efficient evaluation of thermodynamic model parameters within the CALPHAD method. ESPEI uses a linear fitting strategy to parameterize Gibbs energy functions of single phases based on their thermochemical data and refines the model parameters using phase equilibrium data through Bayesian parameter estimation within a Markov Chain Monte Carlo machine learning approach. In this paper, the methodologies employed in ESPEI are discussed in detail and demonstrated for the Cu–Mg system down to 0 K using unary descriptions based on segmented regression. The model parameter uncertainties are quantified and propagated to the Gibbs energy functions.