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With machine learning, researchers embrace the atomic-scale complexity of batteries
For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...
Understanding the influence of quasiperiodicity on magnetic fluctuations could ultimately enable the design of materials with ...
Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...
Researchers at the University of Toronto's Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon steel but the ...
Many techniques in computational materials science require scientists to identify the right set of parameters that capture the physics of the specific material they are studying. Calculating these ...
Researchers have used machine learning to design nano-architected materials that have the strength of carbon steel but the lightness of Styrofoam. The team describes how they made nanomaterials with ...
Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...
Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...
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