CARBON-2D Topological Descriptor (C2DTD): An Interpretable and Physics-Informed Representation for Two-Dimensional Carbon Networks
This paper introduces C2DTD, a compact, interpretable, and physics-informed topological descriptor that effectively captures multi-scale structural features of 2D carbon networks to enable robust, data-efficient machine learning predictions and deep physical insights into their energy landscapes.