Decoding Dopant-Induced Electronic Modulation in Graphene via Region-Resolved Machine Learning of XANES
This study combines density functional theory and region-resolved machine learning to demonstrate that the pi* region of XANES spectra is the most informative for predicting Bader charge and bond lengths, thereby establishing a robust method to quantify dopant-induced electronic modulation in boron- and nitrogen-doped graphene.