In a study published in Nature Communications, researchers explained a local, fluctuating, orbital-degeneracy-lifted state. A phenomenon likely to be widespread amongst diverse classes of partially filled nominally degenerate d-electron systems.

In a study published in Physical Review Materials, researchers discovered that low spin state for a tetrahedral environment provides a novel platform for spin state manipulation in solid state materials.

In a recent study published in ACS Nano, researchers found that spectroscopic measurements reveal that borophene grown on Au(111) possesses a metallic electronic structure.

In a recent study published in Nanoscale, researchers show increases in cooling time for poorer hydrocarbon solvents compared to better solvents, indicate penetration of solvent into the ligand layer facilitates improved heat transfer to the matrix.

In a study published in Physical Review Letters, researchers reported single crystal neutron diffraction measurements that establish that the ground state is indeed magnetic.

In a recent study published in Nanoscale, researchers found that above the threshold ligand coverage density, NPSLs surprisingly preserve their crystalline order even under high applied pressures and show a completely reversible pressure behavior.

In a recent study published in Proceedings of the National Academy of Sciences, researchers demonstrate that dynamic holographic optical tweezers are capable of manipulating single micrometer-scale anisotropic particles in a microfluidic environment.

In a recent study published in Chemistry of Materials, researchers found nanodiffracton results suggest a necessary path to enhance stability of perovskite optoelectronic materials and devices from light-emitting diodes to high-energy detectors.

In a study published in PNAS, researchers developed a targeted evolution genetic algorithm to create a vortex-pinning genome that can be used to enhance the current carrying capability of high temperature superconductors.

In a study published in Science Advances, researchers presented a machine learning approach in which the conformationally dependent electronic structure of a molecule is mapped directly to CG pseudo-atom configurations.