forthcoming articles

Machine learning interatomic potentials (MLIPs) offer a significantly faster alternative to density functional theory for theoretical crystal structure calculations with comparable accuracy. Geometry-optimized structures generated using the universal models for atoms MLIP, trained on the Open Molecular Crystals 2025 dataset, were used to verify 216 919 selected structures from the Cambridge Structural Database with the aim of detecting issues in both the interpretation of the original X-ray experiments and the performance of the used MLIP.

Metadata catalogs are essential for implementing FAIR data principles in photon and neutron (PaN) science, enabling experimental data to become findable, accessible, and reusable. This work provides an analysis of current catalog systems in the PaN field and offers practical recommendations to advance interoperability and build a federated, FAIR-compliant data infrastructure.

This review summarizes recent experimental and theoretical advances in the magnetism of quasicrystals and their approximant crystals, and formulates two hierarchical design principles – valence electron concentration and crystal electric field-induced anisotropy – as primary tools for systematically tuning the magnetic ground states in these compounds.

We describe proof-of-concept experiments towards correlated serial synchrotron crystallography (SSX) and X-ray emission spectroscopy (XES) from microcrystals on a microfocus synchrotron beamline. A droplet-on-demand tape drive system delivers microcrystals to the beam within well separated droplets with a volume of hundreds of picolitres, while XES allows validation of the redox states of metals within protein crystals.

Post-acquisition super resolution (PASR) is a pre-processing step which can be utilized to exceed the resolution limit of already acquired data if the limit is reached. It is designed to be as minimally invasive to all general single particle workflows as possible, allowing users to choose which suite they prefer.