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Mapping the future: AI deciphers alloy microstructures to enhance properties prediction and design
In a world of 8 billion people, there's one thing that makes each of us unique: our fingerprints. A variety of genetic and ...
Scientists at the Center for Nanoscale Materials have developed a machine learning technique for materials research (Nature Computational Materials, "Machine learning enabled autonomous ...
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High-precision analysis of 2D materials microstructures achieved using electron microscopy and machine learning
A research team led by NIMS has, for the first time, produced nanoscale images of two key features in an ultra-thin material: twist domains (areas where one atomic layer is slightly rotated relative ...
Schematic diagrams illustrating the atomic arrangement of an MoS₂ specimen observed using 4D-STEM, showing atomic-scale mapping in real-space coordinates x and y and corresponding diffraction patterns ...
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