A ResNet18 model classifies surface chirality from atomic models at ~73% accuracy and from Fermi surface projections at ~99% accuracy, transferring to experimental synchrotron images after fine-tuning on two frames.
Aguiar , author M
2 Pith papers cite this work. Polarity classification is still indexing.
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cond-mat.mtrl-sci 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Hybrid two-stage optimization framework uses AI for peak/density tasks and physics constraints for robust PXRD crystal structure solving on complex or low-quality cases.
citing papers explorer
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Decoding Crystallographic Surface Chirality with Machine Learning: From Atomic Geometry to Fermi Surface Projections
A ResNet18 model classifies surface chirality from atomic models at ~73% accuracy and from Fermi surface projections at ~99% accuracy, transferring to experimental synchrotron images after fine-tuning on two frames.
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Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction
Hybrid two-stage optimization framework uses AI for peak/density tasks and physics constraints for robust PXRD crystal structure solving on complex or low-quality cases.