α-Graphyne with ultra-low diffusion barriers as a promising sodium-ion battery anode and a computational scheme for accurate estimation of theoretical specific capacity

• Published in: Nanoscale Vol. 16; no. 36; pp. 16900 - 16912
• Main Authors: Dandigunta, Babuji, V G, Abhijitha, Yamijala, Sharma S R K C, Nanda, B R K
• Format: Journal Article
• Language: English
• Published: England Royal Society of Chemistry 19.09.2024
• Subjects: Alternative energy sources; Cluster analysis; Density functional theory; Diffusion barriers; Electrochemical analysis; Lithium-ion batteries; Metal clusters; Molecular dynamics; Sodium; Sodium-ion batteries; Stability; Two dimensional materials; Vertical loads
• ISSN: 2040-3364; 2040-3372; 2040-3372
• DOI: 10.1039/d4nr02797c

Sodium-ion batteries are considered as potential alternatives to conventional lithium-ion batteries. To realize their large-scale practical applications, it is essential to identify suitable anode candidates exhibiting promising electrochemical properties such as high specific capacity, low diffusion energy barrier, and excellent cyclic stability. In this work, using density functional theory (DFT) calculations and molecular dynamics simulations, we examine α-graphyne - a carbon-based 2D material - as a potential anode candidate. Our results show that AGY exhibits an ultra-low diffusion barrier of 0.23 eV along both the horizontal and vertical directions and a low average anodic voltage of 0.36 V. Our AIMD studies at 300 K show excellent thermodynamical stability with the loading of four sodium atoms, resulting in a theoretical specific capacity (TSC) of 279 mA h g . Doping studies show that varying the nature of acetylenic links of AGY with electron-rich (nitrogen) or electron-deficient (boron) elements, the adsorption strength and diffusion barriers for Na atoms on AGY can be tuned. Furthermore, treating AGY as a case study, we find that conventional DFT studies are expected to overestimate the TSC by a huge margin. Specific to AGY, this overestimation can be up to ∼300%. We identify that ignoring the probable formation of temperature-driven metal clusters is the main reason behind such overestimations. Furthermore, we develop a scheme to calculate TSC with higher accuracy. The scheme, which can be easily generalized to the universal class of electrodes, is evolved by concurrently employing AIMD simulations, DFT calculations and cluster analysis.