Identifying the charge density and dielectric environment of graphene using Raman spectroscopy and deep learning
Zhuofa Chen, Yousif Khaireddin, Anna K. Swan
Abstract
. Our approach has the potential for fast and reliable estimation of graphene doping levels and dielectric environments. The proposed model paves the way for achieving efficient analytical tools to evaluate the properties of graphene.
Topics & Concepts
GrapheneRaman spectroscopyDielectricArtificial intelligenceNoise (video)Materials scienceConvolutional neural networkDopingMachine learningComputer scienceComputational physicsOptoelectronicsBiological systemNanotechnologyPhysicsOpticsImage (mathematics)BiologyGraphene research and applicationsSpectroscopy Techniques in Biomedical and Chemical ResearchMachine Learning in Materials Science