Testing the stiffness or tensile strength of fibers in the nano to micro range experimentally, is often very time-consuming. The samples in most cases have to be affixed using adhesive on both ends. Not only curing of the adhesive takes time, but also the sensor to which the fiber is glued cannot be reused. Now researchers from the Technical University of Vienna (TU Wiuen) have developed a test system that overcomes these obstacles.
In Switzerland, Antonia Neels, head of Empa’s Center for X-ray Analytics, has been working on the mysterious material called bulk metallic glasses for about 15 years. Her team investigates the internal structure of metallic glass using various x-ray methods, thereby discovering correlations with properties such as deformability or fracture behavior. In a few months, a sample of metallic glass will be studied in the microgravity of the International Space Station (ISS).
Video description Advancements in material and device fabrication technologies have enabled the development of low-cost, low-power, printed hybrid electronic devices for a variety of applications, including chemical sensors, radio frequency antennae, lab-on-chip health care devices, organic neuromorphic devices, and more.
The development of new thin semiconductor materials requires a quantitative analysis of a large amount of reflection high-energy electron diffraction (RHEED) data, which is time consuming and requires expertise. To tackle this issue, scientists from Tokyo University of Science identify machine learning techniques that can help automate RHEED data analysis.
Scientists at Kyoto University’s Institute for Cell-Material Sciences have discovered a novel cluster compound that could prove useful as a catalyst.
