Paper under double-blind review
Condensed matter physics;Materials science;Material properties prediction;Crystallographic Information Files (CIFs);Natural Language Processing (NLP) in materials;Word2Vec-inspired technique;Atomic embeddings;CIFSemantics model;Band gap;Formation energy;Material representation
Atoms as Words: A Novel Approach to Deciphering Material Properties using NLP-inspired Machine Learning on Crystallographic Information Files (CIFs)