Deep learning plays important roles in artificial intelligence (AI), which yet faces challenges in object representation. In particular, with object sizes decrease, recognition and detection become more difficult and inaccurate.
A kind of high-performance molybdenum alloy, nanoscale ZrC dispersion strengthened Mo alloy with high strength and excellent ductility, was fabricated recently by a collaborated research team from Institute of Solid State Physics, Hefei Institutes of physical science (HFIPS), Chinese Academy of Sciences (CAS), and Nuclear Power Institute of China.
Researchers led by Prof. WANG Yingjian from the Hefei Institutes of Physical Science (HFIPS), Chinese Academy of Sciences (CAS) developed a new, image-free moving object position method.
Fe-18 at.%Ga alloys with magnetostrictive coefficients up to 400 ppm are expected to have high damping based on the magneto-mechanical hysteresis damping (MMHD) model. However, in some studies of the magnetostrictive properties of Fe-Ga alloys, it was found that the magnetization curves of Fe-Ga alloys seem to be reversible, linear, and non-hysteretic curves, which indicates the damping is zero for Fe-Ga alloys. This contradiction makes it a challenge to explore the damping mechanism of iron-based high damping alloys and possible ways to increase the damping of the alloys.
A novel detection technology, developed by a research team led by Prof. ZHANG Weijun from Hefei Institutes of Physical Science (HFIPS), Chinese Academy of Sciences (CAS) recently, realized fast and sensitive detection of nitrogen dioxide (NO2).