Machine learning reveals 5-angstrom sweet spot behind metallic glass stability

Using the second-nearest neighboring atoms to predict metallic glass stability can help researchers more accurately model the disordered solid with strong, elastic properties, according to a recent ...
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Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding

a.The architecture of the all-optical CNN for OAM-mediated machine learning, which can be applied to encode a data-specific image into OAM states. The photonic neural network comprises a trainable ...
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A novel strategy for detecting trace-level nanoplastics in aquatic environments: Multi-feature machine learning-enhanced SERS quantification leveraging the coffee ring effect

A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2025.240260 discusses a novel strategy for detecting trace-level nanoplastics in aquatic environments. Plastic materials have ...
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Machine Learning Approaches for Accelerated Materials Discovery

Artificial Intelligence and its related tools, such as machine learning, deep learning, and neural networks, are revolutionizing every field of life. The domain of materials science and engineering is ...