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Understanding vortex pinning in high-temperature superconducting materials is crucial to optimizing their properties. This Technical Review analyses the impact of growth method on vortex microstructure.
Granular matter is ubiquitous in engineering, industrial and natural processes. This Technical Review overviews the latest developments in computational modelling of granular matter with a focus on the role of particle shape and discusses pertaining future challenges.
Graph neural networks have been applied to many important physics tasks at the Large Hadron Collider (LHC). This Technical Review categorizes these applications in a manner accessible to experts and non-experts alike by providing detailed descriptions of LHC physics and graph neural network design considerations.
The dynamic pair distribution function (DyPDF) is an inelastic neutron scattering method that provides information about the local dynamics of a crystalline material. This Technical Review provides a comparison of data across spectrometers and outlines a robust data treatment regimen as a guide to users of this technique.
Photocurrent can be used to reveal the out-of-equilibrium properties of quantum materials over a range of spatiotemporal scales. This Technical Review outlines the principles of photocurrent diagnostics and how it can be used to probe electronic states, quantum geometry and quantum kinetics of materials.
