Welcome to In the Spotlight, where each month we shine a light on something exciting, timely, or simply fascinating from the world of science.
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Latest News Releases
Updates every hour. Last Updated: 17-Nov-2025 22:11 ET (18-Nov-2025 03:11 GMT/UTC)
Chung-Ang University researchers revolutionize non-destructive testing with purpose-built AI technologies
Chung Ang UniversityPeer-Reviewed Publication
Ultrasonic testing is a promising non-destructive evaluation technique across various industries. In a novel breakthrough, researchers from Chung-Ang University have developed DiffectNet, an AI-based technology that facilitates the diffusion-enabled conditional target generation of internal defects in ultrasonic non-destructive testing. This approach significantly outperforms traditional methods, potentially revolutionizing real-time defect reconstruction and prediction in highly reliability-critical industries, including aerospace, power generation, semiconductor manufacturing, and civil infrastructure.
- Journal
- Mechanical Systems and Signal Processing
Laser trial run kickstarts new era of interferometry
ESOBusiness Announcement
Laser trial at ESO kickstarts new era of interferometry
UCD Research & InnovationNew technology may enable precision treatment of pediatric brain tumors
Uppsala UniversityPeer-Reviewed Publication
- Funder
- European Research Council, Barncancerfonden, Cancerfonden, Vetenskapsrådet, Sjöbergstiftelsen, Hjärnfonden, Familjen Erling-Perssons Stiftelse, Knut och Alice Wallenbergs Stiftelse
The reticular revolution: UChicago chemists move from discovery to design with metal-organic frameworks
University of ChicagoA new AI-powered method to automate material analysis and design
Tokyo University of SciencePeer-Reviewed Publication
X-ray absorption spectroscopy (XAS) provides valuable information about a material’s properties and electronic states. However, it requires extensive expertise and manual effort for conventional analysis. Now, researchers from Japan have developed a novel artificial intelligence-based approach for analyzing XAS data that can enable rapid, autonomous, and object material identification. This novel approach outperforms the previous studies in terms of higher accuracy, accelerating the development of new materials.
- Journal
- Scientific Reports
- Funder
- Institute of Molecular Science, Okazaki, Japan, CREST project