Global Intelligence Database
Scientists are using colloidal systems, where individual particles can be tracked, as a perfect training ground for artificial intelligence. This unique visibility provides incredibly rich data, teaching machine learning models to predict how materials behave and helping to design novel ones from scratch.
By Kang, Joo, An, Hwang
Researchers assessed a dual-source scan mode using a tin filter on a photon-counting detector CT system, comparing it against single-source and energy-integrating detector models. While phantom data indicated superior spectral performance for calcium imaging, the clinical component remained limited to a feasibility cohort of four patients.
By Rajendran, Ferrero, Shanblatt, McCollough, Baffour
Scientists have developed a novel method to transform spherical, onion-like carbon nanomaterials into hollow, quasi-two-dimensional discs. By using a layered chemical template, they can precisely control the material's size, shape, and even its fluorescence, paving the way for new applications.
By Laipan, Zhang, Zhu, Yuan, Wang, Guo, Ahmed, Sun
Magnesium hydrides are promising candidates for hydrogen storage but suffer from slow reaction speeds and instability. A new approach called 'spatially programmed confinement' solves this by trapping the material within engineered 1D, 2D, or 3D structures to boost performance. This strategy transforms passive materials into efficient nanoreactors that operate at lower temperatures.
By Li, Ding, Jiang, Lin, Li, Du, Chen, Shaw, Pan