Highlights

Scientists at the University of Pennsylvania discovered a unique self-assembling network structure that forms when certain liquid crystal materials separate. These networks spontaneously create intricate patterns of filaments and disc-shaped structures through a series of physical transformations driven by competing forces.

Researchers John Crocker and Andrew Liu at the University of Pennsylvania have discovered that biopolymer networks pruned by tension-inhibited methods remain rigid at much lower coordinations than those pruned randomly. This finding helps explain the evolutionary advantage of tension-inhibited filament-severing proteins in biological systems.

Toyota Research Institute of North America, collaborating with MRSEC-supported scientists and facilities have developed a novel [LiCl]/[FeOCl] heterointerface composite material (LFH) that achieves high lithium-ion conductivity from two traditionally non-conductive materials. The unique core-shell structure facilitates interstitial lithium-ion diffusion.

Researchers at the University of Pennsylvania and Swarthmore College developed new non-invasive methods to measure the mechanical properties of defects in liquid crystals using magnetic fields and advanced imaging. The study revealed that the line tension of twist disclinations ranges from 75 to 200 piconewtons and increases logarithmically with sample thickness, providing crucial quantitative data for testing theoretical models of these defects.

MRSEC researchers at the University of Pennsylvania have demonstrated that introducing geometric disorder in mechanical metamaterials leads to distributed damage during failure, resulting in significantly enhanced fracture toughness with minimal loss of strength. This finding challenges the traditional reliance on periodic unit cell geometries in architected materials.

Researchers have successfully intercalated a stable monolayer of lead (Pb) into an experimental setup involving EG/SiC using a method that allows for detailed study of extremely thin heavy metal films. This technique enables higher coverage and better results than traditional methods. Notably, the lead layers show unique structural features and improved spin properties, indicating potential for new applications in spin transport phenomena. This finding highlights the promising use of Pb in creating innovative materials for future technologies.

A research team has created a new method to discover high-entropy oxides (HEOs), which are materials with unique properties due to their disorder. They combined computer simulations and experiments to efficiently explore different HEO compositions. By using advanced machine-learning techniques, they accurately predicted the stability of various HEOs, leading to the discovery of a new type containing calcium. This approach will soon be used to investigate more complex crystal structures for potential new applications.

Researchers demonstrated that by applying electric fields to a two-dimensional gallium layer, they could detect a permanent dipole moment. This breakthrough, shown through microreflectivity, confirms earlier predictions about non-centrosymmetric bonding in 2D metals. The technique, called AC electric double layer gating, effectively modulates the material's properties, paving the way for new insights into the electronic structure and electro-optic characteristics of ultra-thin materials.

Researchers have developed a new method to create single crystals of a unique one-dimensional helical crystal called GaSI. This crystal has a distinctive "squircle" shape, combining square and circular features, which affects its properties. It also has a band gap of 3.7 eV and introduces a non-centrosymmetric unit cell, which leads to notable second harmonic generation. This work is significant for advancing our understanding of chiral materials and their optical and electronic behaviors.

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.