DOI: 10.57760/sciencedb.j00213.00063
title: Theoretical prediction of nitrogen-oxygen-anchored monatomic copper-doped graphene as an anode for alkaline ion batteries
title: 氮氧锚定的单原子铜掺杂石墨烯作为碱离子电池负极的理论预测研究

description: This dataset, derived from Density Functional Theory (DFT) calculations, presents a comprehensive theoretical analysis of the potential of nitrogen and oxygen anchored single-atom copper-doped graphene (Cu/NO2G) as an anode material for alkali-ion batteries. Calculations encompass geometric optimization of physical configurations and their energy storage properties, including geometric and electronic structures, adsorption energies, average open-circuit voltages, theoretical capacities, and diffusion barriers. All calculations were performed using the Vienna Ab initio Simulation Package (VASP) software (licensed), employing the Local Density Approximation (LDA) with the Ceperly-Alder functional parameterized by Perdew and Zunger for the exchange-correlation potential. To ensure accuracy, the plane-wave cutoff energy (Ecut) was set to 520 eV, and Brillouin zone sampling was conducted using the Monkhorst-Pack scheme with a 3×3×1 k-point grid for structural optimization and a 5×5×1 grid for electronic structure calculations. Convergence criteria for total energy and ionic forces were 10-5 eV and 10-3 eV/Å, respectively. Phonon dispersion curves were calculated using the phonopy software package, and migration barriers were determined using the Climbing Image Nudged Elastic Band (CI-NEB) method. While inherent limitations of DFT calculations preclude precise error quantification, the employed methodologies are widely accepted in the field and provide valuable qualitative and semi-quantitative insights.The dataset comprises the following files: Figure 1(a)(b).txt contains the optimized crystal structure data for Cu/NO2G; Figure 1(c)-Phonon dispersion curves.csv contains the phonon dispersion data; Figure 1(d)-AIMD.csv contains the Ab Initio Molecular Dynamics (AIMD) simulation data; Figure 2(a).pdf illustrates the adsorption sites on Cu/NO2G and the most stable adsorption configurations of metal atoms on A and B surfaces; Figures 2(b).vasp, 2(c).vasp, and 2(d).vasp represent the most stable adsorption configurations of Li, Na, and K on the A surface, respectively; Figures 2(e).vasp, 2(f).vasp, and 2(g).vasp represent the most stable adsorption configurations of Li, Na, and K on the B surface, respectively; Figures 3(a)-CHGDIFF-Li.vasp, 3(b)-CHGDIFF-Na.vasp, and 3(c)-CHGDIFF-K.vasp represent the charge difference density data for Li, Na, and K adsorbed on the B surface of Cu/NO2G (viewable with VESTA); Figure 4(a).csv contains the density of states (DOS) data for Cu/NO2G; Figure 4(b).csv contains the projected density of states (PDOS) data for C and Cu in Cu/NO2G; Figure 4(c).csv contains the PDOS data for N and O in Cu/NO2G; Figures 4(d).csv, 4(e).csv, and 4(f).csv contain the DOS data for Cu/NO2G with adsorbed Li, Na, and K, respectively; Figure 5.csv contains the average open-circuit voltage (Vocv) data for Cu/NO2G with varying concentrations of Li, Na, and K; Figure 6.csv contains the theoretical capacity data for Cu/NO2G compared to other 2D materials; Figure 7(a)(b)-migration path.pdf illustrates the migration pathways of Li, Na, and K on the A and B surfaces of Cu/NO2G; Figure 7(c).csv contains the diffusion barrier data for Li, Na, and K on the A surface of Cu/NO2G; and Figure 7(d).csv contains the diffusion barrier data for Li, Na, and K on the B surface of Cu/NO2G.This dataset offers profound implications for physics research, particularly in condensed matter physics and materials science, by providing atomic-level insights into electrochemical processes within alkali-ion batteries. It furnishes a theoretical foundation for the design and optimization of novel electrode materials, especially 2D materials like Cu/NO2G, by offering key parameters such as adsorption energies, diffusion barriers, open-circuit voltages, and theoretical capacities. Moreover, it serves as a valuable benchmark for validating and refining computational methods like DFT, ultimately advancing the development of next-generation energy storage devices and deepening our understanding of material properties at the atomic scale.
description: This dataset, derived from Density Functional Theory (DFT) calculations, presents a comprehensive theoretical analysis of the potential of nitrogen and oxygen anchored single-atom copper-doped graphene (Cu/NO2G) as an anode material for alkali-ion batteries. Calculations encompass geometric optimization of physical configurations and their energy storage properties, including geometric and electronic structures, adsorption energies, average open-circuit voltages, theoretical capacities, and diffusion barriers. All calculations were performed using the Vienna Ab initio Simulation Package (VASP) software (licensed), employing the Local Density Approximation (LDA) with the Ceperly-Alder functional parameterized by Perdew and Zunger for the exchange-correlation potential. To ensure accuracy, the plane-wave cutoff energy (Ecut) was set to 520 eV, and Brillouin zone sampling was conducted using the Monkhorst-Pack scheme with a 3×3×1 k-point grid for structural optimization and a 5×5×1 grid for electronic structure calculations. Convergence criteria for total energy and ionic forces were 10-5 eV and 10-3 eV/Å, respectively. Phonon dispersion curves were calculated using the phonopy software package, and migration barriers were determined using the Climbing Image Nudged Elastic Band (CI-NEB) method. While inherent limitations of DFT calculations preclude precise error quantification, the employed methodologies are widely accepted in the field and provide valuable qualitative and semi-quantitative insights.The dataset comprises the following files: Figure 1(a)(b).txt contains the optimized crystal structure data for Cu/NO2G; Figure 1(c)-Phonon dispersion curves.csv contains the phonon dispersion data; Figure 1(d)-AIMD.csv contains the Ab Initio Molecular Dynamics (AIMD) simulation data; Figure 2(a).pdf illustrates the adsorption sites on Cu/NO2G and the most stable adsorption configurations of metal atoms on A and B surfaces; Figures 2(b).vasp, 2(c).vasp, and 2(d).vasp represent the most stable adsorption configurations of Li, Na, and K on the A surface, respectively; Figures 2(e).vasp, 2(f).vasp, and 2(g).vasp represent the most stable adsorption configurations of Li, Na, and K on the B surface, respectively; Figures 3(a)-CHGDIFF-Li.vasp, 3(b)-CHGDIFF-Na.vasp, and 3(c)-CHGDIFF-K.vasp represent the charge difference density data for Li, Na, and K adsorbed on the B surface of Cu/NO2G (viewable with VESTA); Figure 4(a).csv contains the density of states (DOS) data for Cu/NO2G; Figure 4(b).csv contains the projected density of states (PDOS) data for C and Cu in Cu/NO2G; Figure 4(c).csv contains the PDOS data for N and O in Cu/NO2G; Figures 4(d).csv, 4(e).csv, and 4(f).csv contain the DOS data for Cu/NO2G with adsorbed Li, Na, and K, respectively; Figure 5.csv contains the average open-circuit voltage (Vocv) data for Cu/NO2G with varying concentrations of Li, Na, and K; Figure 6.csv contains the theoretical capacity data for Cu/NO2G compared to other 2D materials; Figure 7(a)(b)-migration path.pdf illustrates the migration pathways of Li, Na, and K on the A and B surfaces of Cu/NO2G; Figure 7(c).csv contains the diffusion barrier data for Li, Na, and K on the A surface of Cu/NO2G; and Figure 7(d).csv contains the diffusion barrier data for Li, Na, and K on the B surface of Cu/NO2G.This dataset offers profound implications for physics research, particularly in condensed matter physics and materials science, by providing atomic-level insights into electrochemical processes within alkali-ion batteries. It furnishes a theoretical foundation for the design and optimization of novel electrode materials, especially 2D materials like Cu/NO2G, by offering key parameters such as adsorption energies, diffusion barriers, open-circuit voltages, and theoretical capacities. Moreover, it serves as a valuable benchmark for validating and refining computational methods like DFT, ultimately advancing the development of next-generation energy storage devices and deepening our understanding of material properties at the atomic scale.