Chemical Communications · 2018 · 129 citations · 44 references
Natural SciencesMaterials EngineeringMaterials ScienceComputational ChemistryComputational Materials ScienceTheoretical ChemistryAtomistic ModelingAtomistic SimulationCarbon-based Energy MaterialsDensity Functional TheoryElectrode MaterialsMaterial ModelingCarbon ElectrodesCarbon MaterialsCarbon Nanomaterials For Energy StorageCarbon-based Electrode MaterialsCarbon-based ElectrodesCarbon-based NanomaterialsMachine Learning Potential Energy Surfaces
Disordered nanoporous and "hard" carbons are widely used in batteries and supercapacitors, but their atomic structures are poorly determined. Here, we combine machine learning and DFT to obtain new atomistic insight into carbonaceous energy materials. We study structural models of porous and graphitic carbons, and Na intercalation as relevant for sodium-ion batteries.
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Generalized Gradient Approximation Made Simple
John P. Perdew, Kieron Burke, Matthias Ernzerhof · Physical Review Letters · 1996 · 211.5K citations · Full text
Natural Sciences, Chemistry, Physics +16