Fusing a machine learning strategy with density functional theory to hasten the discovery of 2D MXene-based catalysts for hydrogen generation
B. Moses Abraham, Priyanka Sinha, Prosun Halder, Jayant K. Singh
Abstract
We establish a robust and broadly applicable multistep workflow using machine learning algorithms to construct well-trained data-driven models for predicting the hydrogen evolution reaction activity of 4500 MM′XT 2 -type MXenes.
Topics & Concepts
MXenesWorkflowDensity functional theoryComputer scienceConstruct (python library)Artificial intelligenceMachine learningChemistryMaterials scienceNanotechnologyComputational chemistryDatabaseProgramming languageMXene and MAX Phase MaterialsAdvanced Photocatalysis TechniquesHydrogen Storage and Materials