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.

Natural living conductive biofilms transport electrons between electrodes and cells, as well as among cells fixed within the film, catalyzing an array of reactions from acetate oxidation to CO2 reduction. Synthetic biology offers tools to modify or improve electron transport through biofilms, creating a new class of engineered living conductive materials. Engineered living conductive materials could be used in a range of applications for which traditional conducting polymers are not appropriate, including improved catalytic coatings for microbial fuel-cell electrodes, self-powered sensors for austere environments, and next-generation living components of bioelectronic devices that interact with the human microbiome.

Energy density and safety are the main factors that govern the development of the rechargeable battery technology. Currently, batteries beyond typical Li-ion batteries such as those based on solid-state electrolytes (SSEs) or other active elements (e.g., Na or Mg) are being examined as alternatives. For example, SSEs that would enable stable and reliable operation of all-solid-state Li-, Na-, and Mg-based batteries, with preferably improved capacity, are considered to be one of the most desired inventions. Lightweight complex metal hydrides are a family of solid compounds that were recently discovered to have extraordinary ionic conductivities and, in some cases, electrochemical properties that enabled battery reversibility. Consequently, they have become one of the promising electrolyte materials for future development of electrochemical storage devices. In this work, we present an overview of a wide range of lightweight hydride-based materials that could be used as electrolytes and/or anodes for mono-/divalent batteries and have a pivotal role in the implementation of new technological solutions in the field of electrochemistry.

Machine learning (ML) has been perceived as a promising tool for the design and discovery of novel materials for a broad range of applications. In this prospective paper, we summarize recent progress in the applications of ML to composite materials modeling and design. An overview of how different types of ML algorithms can be applied to accelerate composite research is presented. This framework is envisioned to revolutionize approaches to design and optimize composites for the next generation of materials with unprecedented properties.

In the current manuscript we discuss the response of dynamic metallogels that display reversion to the liquid state when exposed to phosphines. The metallogels are formed through the condensation of formaldehyde and poly(alkyloxide)amines in polar aprotic solvents. The gel formation can be catalyzed with trivalent metals (Al(III and Fe(III)) with concomitant enhanced dynamism (gelation/degelation). When various phosphines are introduced, the metallogel is irreversibly liquefied. This process adds a new vector for controlling the bulk properties of this class of materials. Here, we explore the mechanism in detail for the reaction of tris(carboxyethyl)phosphine with N,N,N-triethoxylethyl-1,3,5-hexahydro-1,3,5-triazine (HEHT, 1) a stable derivative of the active hexahydrotriazine (HT) core in dimethylformamide in the presence or absence of Al(III). Additionally, density functional theory is used on the model N,N,N-trimethyl system (MHT, 2) to estimate reaction parameters and predict nuclear magnetic resonance spectra.

Immune cells can be genetically engineered with a synthetic chimeric antigen receptor (CAR) to eliminate cancer cells, but clinical efficacy in solid tumors has been disappointing due in part to the immunosuppressive tumor microenvironment (TME). Additionally, the cost and logistical issues of personalized medicine necessitate the creation of an off-the-shelf CAR therapy. Synthetic biology tools were implemented in addressing these problems: an anti-mesothelin CAR, membrane-bound IL-15/IL-15Rα complex, and inducible caspase 9 “kill switch” were expressed in natural killer cells for tumor-targeting capabilities, immunostimulatory effects, and safety in treating a preclinical model of ovarian cancer with a renewable, allogenic cell therapy.

Plasticity and fracture of materials at the nanoscale levels can deviate significantly from the same phenomena in bulk properties, which may have important implications if they are to be used in real-world engineering systems. Nanoscale metal–metal multilayered materials provide a model material system platform to understand plasticity and fracture based on dislocation interactions with microstructural features. Recently, there is a growing trend to understand the fracture of multilayered materials to see the interactions between the crack and multilayered interface through novel experimentation techniques. In this review, we will introduce the rationale, the current microfracture methods to test and analyze the multilayer fracture behavior and the challenges faced in performing them. Four examples of in situ fracture techniques are highlighted in this work through tensile testing of film on a substrate: microfracture clamped beam bending technique across the multilayers and delamination along the multilayered interface.