Researchers at the National Institute for Materials Science have developed a machine learning model to predict the mechanical properties of polymers, such as polypropylene, based on X-ray diffraction data. This non-destructive method links material structure to properties like stiffness and elasticity, offering a faster and cheaper alternative to traditional testing. The model could revolutionize polymer testing and design, leading to more efficient materials development. This approach may also be extended to other analytical techniques for both organic and inorganic materials.
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