UV-A Flexible LEDs Based on Core-Shell GaN/AlGaN Quantum Well Microwires.

Nanostructured ultraviolet (UV) light sources represent a growing research field in view of their potential applications in wearable optoelectronics or medical treatment devices. In this work, we report the demonstration of the first flexible UV-A light emitting diode (LED) based on AlGaN/GaN core-shell microwires. The device is based on a composite microwire/poly(dimethylsiloxane) (PDMS) membrane with flexible transparent electrodes.

Capturing Catalyst Strain Dynamics during CO Oxidation.

Understanding the strain dynamic behavior of catalysts is crucial for the development of cost-effective, efficient, stable, and long-lasting catalysts. Using time-resolved Bragg coherent diffraction imaging at the fourth generation Extremely Brilliant Source of the European Synchrotron (ESRF-EBS), we achieved subsecond time resolution during chemical reactions. Upon investigation of Pt nanoparticles during CO oxidation, the three-dimensional strain profile highlights significant changes in the surface and subsurface regions, where localized strain is probed along the [111] direction.

Unveiling Core-Shell Structure Formation in a NiFe Nanoparticle with In Situ Multi-Bragg Coherent Diffraction Imaging.

Solid-state reactions play a key role in materials science. The evolution of the structure of a single 350 nm NiFe nanoparticle, , its morphology (facets) as well as its deformation field, has been followed by applying multireflection Bragg coherent diffraction imaging. Through this approach, we unveiled a demixing process that occurs at high temperatures (600 °C) under an Ar atmosphere.

LaueNN: neural-network-based recognition of Laue spots and its application to polycrystalline materials.

A feed-forward neural-network-based model is presented to index, in real time, the diffraction spots recorded during synchrotron X-ray Laue microdiffraction experiments. Data dimensionality reduction is applied to extract physical 1D features from the 2D X-ray diffraction Laue images, thereby making it possible to train a neural network on the fly for any crystal system. The capabilities of the LaueNN model are illustrated through three examples: a two-phase nano-structure, a textured high-symmetry specimen deformed and a polycrystalline low-symmetry material.