MetalHawk: Enhanced Classification of Metal Coordination Geometries by Artificial Neural Networks
Abstract
A machine learning-based approach for classifying metal site geometry.
Fields of Study & Subjects
Machine Learning in Materials Science
Crystal structures of chemical compounds
Machine Learning in Bioinformatics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 19 January 2026
- Language
- EN