Nebil A. Katcho

The study of magnetic structures from a crystallographic perspective remains a niche field, largely confined to physical crystallography and microscopic magnetism. Unlike general or superspace crystallography, magnetic structure analysis lacks standardization, primarily due to the small research community and the reliance on specialized experimental techniques like neutron diffraction. However, emerging topics in condensed matter physics, such as topological materials, multiferroics, and skyrmions, have heightened the importance of understanding magnetic ordering. As a result, the analysis of magnetic neutron scattering data is becoming increasingly relevant, requiring unified methodologies. Since 2011, the IUCr Commission on Magnetic Structures has been working to improve the situation. This paper reviews the most commonly used methods for describing magnetic structures and highlights the capabilities of the FullProf Suite for analysing magnetic neutron diffraction data.

FullProfAPP is a software tool for data processing, refinement and visualization of large collections of powder diffraction patterns. Featuring an intuitive graphical user interface, it seamlessly facilitates a variety of tasks. These include conducting full-profile phase searches, sequential and high-throughput Rietveld refinements, and managing background (and peak) detection. FullProfAPP also provides convenient interaction with crystallographic databases and supports the visualization and export of high-quality pixel and vector graphics depicting the refinement results, among other functionalities. FullProfAPP wraps around the refinement program FullProf [Rodríguez-Carvajal (1993), Physica B, 192, 55–69] and offers the flexibility of user-defined workflows by accessing and editing FullProf's input files and triggering its execution as necessary. FullProfAPP is distributed as open-source software and is presently available for Windows and Linux operating systems.

We describe a new software package for the data reduction of single crystal neutron diffraction using large 2D detectors. The software consists of a graphical user interface from which the user can visualize, interact with and process the data. The data reduction is achieved by sequentially executing a series of programs designed for performing the following tasks: peak detection, indexing, refinement of the orientation matrix and motor offsets, and integration. The graphical tools of the software allow visualization of and interaction with the data in two and three dimensions, both in direct and reciprocal spaces. They make it easy to validate the different steps of the data reduction and will be of great help in the treatment of complex problems involving incommensurate structures, twins or diffuse scattering.

Progress in energy-related technologies demands new and improved materials with high ionic conductivities. Na- and Li-based compounds have high priority in this regard owing to their importance for batteries. This work presents a high-throughput exploration of the chemical space for such compounds. The results suggest that there are significantly fewer Na-based conductors with low migration energies as compared to Li-based ones. This is traced to the fact that, in contrast to Li, the low diffusion barriers hinge on unusual values of some structural properties. Crystal structures are characterized through descriptors derived from bond-valence theory, graph percolation and geometric analysis. A machine-learning analysis reveals that the ion migration energy is mainly determined by the global bottleneck for ion migration, by the coordination number of the cation and by the volume fraction of the mobile species. This workflow has been implemented in the open-source Crystallographic Fortran Modules Library (CrysFML) and the program BondStr. A ranking of Li- and Na-based ionic compounds with low migration energies is provided.

The search for Si-based anodes capable of undergoing low volume changes during electrochemical operation in rechargeable batteries is ample and active. Here we focus on crystalline Si₂₄, a recently discovered open-cage allotrope of silicon, to thoroughly investigate its electrochemical performance using density functional theory calculations. In particular, we examine the phase stability of Na _x Si₂₄ along the whole composition range (0 ≤ x ≤ 4), volume and voltage changes during the (de)sodiation process, and sodium ion mobility. We show that Na _x Si₂₄ forms a solid solution with minimal volume changes. Yet sodium diffusion is predicted to be insufficiently fast for facile kinetics of Na-ion intake. Considering these advantages and limitations, we discuss the potential usefulness of Si₂₄ as anode material for Na-ion batteries.

Transition metal layered oxides are promising cathode materials for sodium‐ion batteries. Phase transitions involving different stacking sequences of the oxide layers often plague the electrochemistry of these materials during cycling, which strongly impacts in their electrochemical performance. However, the underlying mechanisms of these processes remain elusive. Interestingly, P2‐ and O3‐Na_2/3Fe_2/3Mn_1/3O₂ phases are the first transition metal layered oxide polymorphs that have been synthesized with exactly the same composition. This offers unprecedented access to the study of bistability in these systems as well as isolates the effect of local structure on Na ion mobility. Here, first‐principles calculations and experiments are combined to unveil the physical origin of such bistability and identify important differences in Na ion diffusion between these two phases. It has been found that electrostatic interactions between oxide layers control the bistable nature of P2 and O3 phases. It is also put forward that the interlayer distance between oxide layers may be a useful descriptor to rationalize the relative stability of other P and O phases in general. Furthermore, this study tracks down to the molecular level the differences regarding Na ion mobility in P2‐ and O3‐Na_2/3Fe_2/3Mn_1/3O₂ by computing activation energies and estimating diffusion coefficients.

The structure of electrochemically active Li_1.5Fe(SO₄)₂ with difference Fourier maps highlighting the two lithium positions, which are also represented in the unit cell.