Investigation of the temperature dependence of the skyrmion Hall effect reveals further insights into possible new data storage devices.
Nanotechnology News from Nanowerk
Investigation of the temperature dependence of the skyrmion Hall effect reveals further insights into possible new data storage devices. • Email to a friend • The novel light detector consists of two-dimensional layers of different materials that are coupled to a silicon optical waveguide. In the future, this approach can also be used to make LEDs and optical modulators. • Email to a friend • Researchers developed a nanosensor able to accurately detect biomarkers for cancer in an extremely broad range of concentrations: from 10 particles per microliter to a million particles per microliter. • Email to a friend • Scientists have developed an energy harvesting device that generates over 5 volts of electricity from a liquid droplet. This device, made of flexible thin films, generates electricity when drops of liquid slide down along its surface. • Email to a friend • Researchers have succeeded for the first time in temporally shaping the electric field of an attosecond pulse. • Email to a friend • New advances in Micro Electro-Mechanical' technology including progression towards new semiconductors with greater capacity will open the door to a myriad of new opportunities for the maritime sector, according to an EU study. • Email to a friend • Using a technique called molecular layer etching can help manufacturers and researchers develop new ways of making nanostructures. • Email to a friend • Oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER) are among the core electrochemical processes in clean energy conversion and storage devices, such as metal-air batteries, water electrolyzers, and fuel cells. Single-atom catalysts have emerged as a new frontier of heterogeneous catalysts for these reactions due to their highly increased coverage of active sites, enhanced catalytic performance, and maximal metal utilization. By using machine learning algorithms, researchers provide a new paradigm for directly predicting the catalytic performance from physical properties of catalyst candidates. • Email to a friend • |
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