In a report published in Small, researchers introduce “ingrained”, an automated framework for the fusion of atomic-resolution materials imaging simulations into the experimental images to which they correspond.
In a report published in PNAS, researchers report on a newly developed laser-pumped X-ray nanodiffraction imaging capability with 25 nm and 100 ps resolutions.
In a study published in Communications Physics, researchers reveal the presence of three types of magnetic order in an iron superconductor (LaFeAs1-ₓPₓO).
In a study published in Advanced Materials, researchers imaged for the first time the conduction channel formed in a memristor using an X-ray microscope at the Advanced Photon Source.
In a study published in Proceedings of the National Academy of Sciences, researchers report that machine learning can reveal all the critical features within X-ray scattering “big data” required to determine the origin of structural correlations.
For a study published in Patterns, researchers developed a predictive framework for zinc blende semiconductors and impurity atoms from across the periodic table.
For a study published in Science, researchers developed and tested a perovskite nickelate with which computer chips can be designed to reconfigure their circuits when presented with new information.
In a study published in Nature Communications, researchers report a reinforcement learning-based algorithm for developing molecular models that predict potential energy surfaces of elemental nanoclusters and bulk systems.