An ultra-fast tabletop X-ray source for Spintronics … and 4 other research advances

A very fast tabletop X-ray source for studying the components of Spintronics

Expensive and high-demand synchrotron beams are not required to track the spin dynamics in a rare-earth heterostructure aimed at Spintronics. With the opportunity to increase the power of the Ytterbium laser, an international research team has achieved – through high harmonic generation, HHG – a tabletop soft X-ray source that is sharp, consistent and focused enough to perform scattered measurements. Resonant magnetic (XRMS). Enough to access the magnetic behavior of a sample of cobalt-terbium with a temporal resolution of less than 100 femtoseconds and a spatial resolution of a few nanometers.

G.Fan et al. Ultrafast magnetic scattering on ferrimagnets enabled by a bright Yb-based soft X-ray source. Optica volume. 9, number 4, p. 399-407 (2022).

Generating green hydrogen using GaN-type semiconductors

Photoelectrolysis of water makes it possible to produce green hydrogen in a single step using a photo-catalyst subject to sunlight, but much research is still needed. A French team has shown that photo-electrodes obtained by depositing a thin layer of III-V composite semiconductor in a silicon layer have attractive candidates despite having vertically formed crystal defects. They are actually able to absorb photons to create electrical charges and transport these charges. The physical properties of these crystals can therefore be exploited to achieve competitive photoelectric performance.

Chen L., et al., “Epitaxial III-V / Si Vertical Heterostructure with Hybrid 2D-Semimetal / Semiconductor Ambipolar and Photoactive Properties”, Advanced Science, 2022, 9.

Detect metal 3D printing errors with laser-based ultrasound

American researchers have developed a new ultrasound technique capable of detecting the formation of defects in a metallic 3D printing process. Their technique is based on surface acoustic waves generated by laser-based ultrasound. These waves can expose small surface and sub-surface defects in metal laser powder bed fusion 3D printing. The results of their laser-based ultrasound examination were verified by light microscopy, for surface features, and for X-ray computed tomography for surface features.

Katherine Jeanne Harke et al, Surface and Sub-Surface Features of Laser-Based Ultrasound Interrogation in Advanced Manufacturing Materials, Scientific Report (2022).

Artificial skin responds to various stimuli

To develop autonomous and intelligent robotics, capable of making decisions alongside a human, we must begin with access to the same information. An Austrian team has created an “e-skin” that can simultaneously detect pressure, humidity and temperature. Constructed as an array of pixels, the synthetic skin responds in a position-specific manner to each stimulus through an active layer consisting of an array of hydrogel nanorods surrounded by zinc oxide. Changes in temperature and humidity in the environment will cause the hydrogel to swell, affect the zinc shell, and create a measurable mechanical effect by the system. As a result, the skin receives a resolution of 500 nm, which is twice as precise as that of a human finger.

Taher Abu Ali etc. Smart core? Shell Nanostructures for Ball, Moisture, and Temperature Multi? Stimulus responsiveness. Advanced Materials Technologies (2022)

Learn to flock to detect cancer while protecting information privacy

British scientists have set up a type of artificial intelligence, called swarm learning, to find out if computers could be used to help predict cancer by keeping data secret. This swarm education includes training an AI model based on patient data from a local hospital or university. The system then sends this locally trained model – but not most patient data – to a central computer. There, it is combined with other models produced similarly in other hospitals to create a more efficient overall model. It is then sent back to the local hospital, where it is re-applied to the original data to improve cancer detection.

Saldanha, OL and others. Learning to swarm for decentralized artificial intelligence in cancer histopathology. Nat Med, 2022

Selected For you

Leave a Comment