System-conditioned reparameterization of the SCAN functional for accurate bandgaps: from analytical constraints to machine learning
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Updated
Mar 13, 2026 - Jupyter Notebook
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bandgap-prediction
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Multimodal Deep Learning pipeline for crystalline bandgap prediction. Combines 1D X-Ray Diffraction (XRD) patterns with engineered tabular features (Magpie & CrystalNN) using a dual-branch PyTorch ResNet architecture. Features high-throughput data extraction via Materials Project API and automated structural featurization.
machine-learning deep-learning pytorch crystallography resnet crystal-structure feature-engineering materials-science materials-informatics x-ray-diffraction magpie multimodal-deep-learning materials-project bandgap-prediction
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Updated
Mar 12, 2026 - Jupyter Notebook
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