Author

S. Chakraborty

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Preprint Aug 2026

Data-driven discovery and rapid, direct synthesis of MXenes

MXenes, two-dimensional transition-metal carbides and nitrides, are typically obtained from MAX phases, yet historical reports suggest a broader, largely unexplored chemical space. Here we combine machine-learning-assisted database mining with experiments to uncover overlooked multilayer (ml) MXenes. Screening of repos...

A. S. Shamshirgar, G. R. Portugal, S. Ershadrad et al. · 0 citations

Preprint Jul 2026

Dual-Level Atomic and Coordination Geometry Learning for Crystal Property Prediction Using Graph Neural Networks

The proposed Coordination Polyhedron Graph Network (CPGN) is a multi-scale GNN that jointly learns atomic, bond, and coordination-polyhedron representations and outperforms existing state-of-the-art GNN models.

S. Chakraborty · 0 citations