ED-CSP: Crystal Structure Prediction from Electron Diffraction
This work introduces ED-CSP, a machine learning framework that predicts crystal structures from chemical composition, atom count, and multiple detector-plane ED spot sets and establishes a benchmark for generative crystal structure prediction from sparse ED observations and provides a foundation for future transfer to experimental data.
Germain Poloudenny, Arnaud Demortière, Yael Fregier
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