News by Subject Chemistry & Physics

Tokyo, Japan - Researchers from Tokyo Metropolitan University have developed a new technology which allows non-contact manipulation of small objects using sound waves. They used a hemispherical array of ultrasound transducers to generate a 3D acoustic fields which stably trapped and lifted a small polystyrene ball from a reflective surface. Although their technique employs a method similar to laser trapping in biology, adaptable to a wider range of particle sizes and materials.

The lithium-ion battery is the future of sustainable energy technology, but drastic volume fluctuations in their anodes related to enhanced battery capacity raises a safety concern. Recently, researchers from the Republic of Korea have found that embedding manganese selenide anodes in a 3D carbon nanosheet matrix is an innovative, simple, and low-cost means of reducing drastic volume expansion while improving the energy density of these batteries.

New European Union regulations on batteries could offer a huge boost to the global decarbonisation mission - but only if it leverages its political and economic weight to ensure a fairer global marketplace.

Scientists proposed zero-dimensional molecular sieve membranes that could enhance the separation selectivity of hydrogen and carbon dioxide.

The importance of aryl sulfides in biologically active compounds has led chemists to develop methods to synthesize them from carbon-sulfur bond forming reactions. The conventional reaction, however, uses thiols that are foul-smelling and toxic. Now, chemists from Waseda University, Japan, report a novel, thiol-free synthesis technique comprising a nickel-catalyzed aryl exchange between 2-pyridyl sulfide and aromatic esters, providing a versatile and inexpensive technology for both scientific and industrial applications.

Army-funded research identified a new material that may lead to lightweight armor, protective coatings, blast shields and other impact-resistant structures.

Implementing algorithms that can simultaneously track multiple objects is essential to unlock many applications, from autonomous driving to advanced public surveillance. However, it is difficult for computers to discriminate between detected objects based on their appearance. Now, researchers at the Gwangju Institute of Science and Technology (GIST) adapted deep learning techniques in a multi-object tracking framework, overcoming short-term occlusion and achieving remarkable performance without sacrificing computational speed.

Researchers at Stanford and the University of Naples study how bubbles form and eventually burst using high-speed cameras and analytical modeling, revealing a new popping process.