Litcius/Paper detail

Hierarchical porous N/S-doped carbon with machine learning to predict advanced potassium-ion batteries

Ke Bi, Yue Wang, Guangyuan Zhou

2023Journal of Materials Chemistry A29 citationsDOI

Abstract

PIBs have promising prospects for next-generation energy storage. Machine learning and density functional theory calculations were both used to clarify the relationships between structural parameters and performances.

Topics & Concepts

Density functional theoryDopingPorosityIonCarbon fibersMaterials scienceEnergy storagePotassiumNanotechnologyChemical engineeringEngineering physicsComputer scienceChemistryThermodynamicsOptoelectronicsEngineeringComputational chemistryComposite materialPhysicsMetallurgyOrganic chemistryPower (physics)Composite numberAdvancements in Battery MaterialsAdvanced Battery Materials and TechnologiesAdvanced Battery Technologies Research