Improved performance of graphene doped with pyridinic N for Li-ion battery: a density functional theory model

Literature Information

Publication Date 2013-06-05
DOI 10.1039/C3CP51987B
Impact Factor 3.676
Authors

Xiang-kai Kong


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Abstract

The performance of N-doped graphene on Li-ion battery has been investigated systematically by means of a density functional theory method. Pyridinic N doping, graphitic N atoms and 5-8-5 double vacancies have been selected as the functional defects to study their influence on Li storage compared to the pristine graphene. It has been confirmed that introducing pyridinic N atoms with p-type doping is a suitable method, especially for graphene doped with 4 pyridinic N atoms, whose structural distortion induced by Li intercalation is small and supplies strong force for Li adsorption. The diffusion barrier for this model is lower than for pristine graphene, both for the side and center diffusion routes, contributing to the high mobility. In addition, we point out that the strong catch force for Li will cause more Li to stay on the pyridinic N-doped graphene during the charge–discharge cycles, leading to a faster decrease of capacity compared to pristine graphene.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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