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A new neural network-based method called Neural Network Kinetics (NNK) has been developed to predict how chemicals and structures change over time in complex environments. This technique effectively models atom movements and diffusion barriers. Researchers applied NNK to study the NbMoTa alloy, discovering a key temperature where a specific chemical order peaks. They found significant variations in atom mobility near this temperature, which are crucial for understanding chemical ordering and the formation of the B2 structure.

Flat bands have been associated with excoct effects in materials, such as strong correlations, superconductivity, or the fractional quantum Hall effect. In bulk materials they are difficult to be isolated form other electronic states. In addition, they are often at non-accessible energies. In this work, Schoop and Bernevig collaborated to access flat bands in a new material using soft-chemical modification of a known materials.

Block polymers are a class of versatile self-assembling soft materials that can form exquisite nanostructures for applications including ion transport membranes for batteries and fuel cells, and templates for inorganic oxide catalysts. Using molecular dynamics simulations and transferable force fields, we designed a series of symmetric triblock amphiphiles (or high-χ “block oligomers”) comprising incompatible sugar-based (A) and hydrocarbon (B) blocks that can self-assemble into ordered nanostructures with full domain pitches as small as 1.2 nm.

Fig. 1 Device schematic, optical micrograph, and initialization scheme.

Designable Porous Organic Networks Represent A New Strategy for Nanoparticle Assembly

The artist residency program at the Center for Dynamics and Control of Materials enables artists to work with CDCM faculty to create contemporary art installations that demonstrate emerging science and technology, bringing fundamental concepts in science to the public in very tangible, engaging ways.

Replacing steel with lightweight Aluminum alloys could significantly improve fuel economy of vehicles.  Existing lightweight alloys are difficult to use, because they have poor ductility, and tend to tear while they are stamped to form a complex part.  Adding small quantities of additional allying elements to lightweight alloys could improve their ductility.  But at present the only way to identify the correct elements is to make, and test, many possible combinations - an impossible task.

Researchers developed active solids made of centimeter-scale building blocks that can move and adapt in different environments. These prototypes show unique elasticity, which allows them to change their movement patterns and navigate various terrains effectively, similar to complex robotic systems. This study highlights the potential of these materials to link robotics and material science and suggests new ways to control dynamic systems in nature and technology.

Super-moiré patterns identified in WSe2 bilayer with large twist angles. While moiré superlattices in graphene and transition metal dichalcogenide (TMD) bilayers with small twist angles are known to exhibit flat bands and host exotic correlated phases, strong lattice reconstruction in these systems poses challenges. In contrast, large-angle bilayers are structurally robust but typically considered electronically decoupled. Here, we discover robust super-moiré patterns emerging near a large commensurate angle, combining the advantages of both regimes—structural stability with flat electronic bands. This work expands moiré twistronics and flat-band quantum physics into the large twist-angle regime.

After discovering a new magnetic host of skyrmion states, UC Santa Barbara IRG-1 researchers were able to show that chemically alloying the compound FePd1−xPtxMo3N allows for the size of the skyrmion defects to be controlled while still preserving their stability.  Skyrmion states are broadly sought in new materials due to their potential uses in low power memory devices and other spin-based electronics.