New research published in Science Advances, led by Yuan Yang, associate professor of materials science at Columbia Engineering, and collaborators at Lamont-Doherty Earth Observatory, demonstrates a novel technique for isolating isotopes.
Researchers based at the Department of Energy’s Pacific Northwest National Laboratory (PNNL) have made a breakthrough in redox flow battery technology using a simple sugar additive that could address key concerns while enhancing grid energy resilience.
New research sheds light on the mechanism behind how a special material changes from an electrically conducting metal to an electric insulator. The researchers studied lanthanum strontium nickel oxide (La1.67Sr0.33NiO4) derived from a quantum material La2NiO4.
A team from Ames National Laboratory conducted an in-depth investigation of the magnetism of TbMn6Sn6, a Kagome layered topological magnet. They were surprised to find that the magnetic spin reorientation in TbMn6Sn6 occurs by generating increasing numbers of magnetically isotropic ions as the temperature increases.
The Electrochemical Society (ECS) has selected scientist Shirley Meng of the U.S. Department of Energy's (DOE) Argonne National Laboratory as the recipient of the 2023 Battery Division Research Award for innovative research on interfacial science, which has led to improved battery technologies.
An international research team involving scientists from the University of Vienna, the Faculty of Physics of the University of Warsaw and Univeristy of Edinburgh has described the process of growing three-dimensional manganese dendrites.
Phase change memory is a type of nonvolatile memory that harnesses a phase change material's (PCM) ability to shift from an amorphous state, i.e., where atoms are disorganized, to a crystalline state, i.e., where atoms are tightly packed close together.
Solid electrolytes with high lithium-ion conductivity can be designed for millimeter-thick battery electrodes by increasing the complexity of their composite superionic crystals, report researchers from Tokyo Tech.
Using a combination of high-powered X-rays, phase-retrieval algorithms and machine learning, Cornell researchers revealed the intricate nanotextures in thin-film materials, offering scientists a new, streamlined approach to analyzing potential candidates for quantum computing and microelectronics, among other applications.
The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a simulation technique that offers both high fidelity and scalability across different time and length scales has long been a roadblock for the progress of these technologies.
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