Study of the Electronic Band Structure and Structural Stability of Al(CN)₂ and Si(CN)₂ by Density Functional Theory

Abstract

By substituting the A site in P21/c-A(CN)2 and varying the lattice parameters a, b, c, and the unit-cell angles, along with using crystal graph convolutional neural networks to calculate their cohesive energy, the candidate compounds, Al(CN)2 and Si(CN)2, were selected from the structure with the lowest cohesive energy. The two candidate structures were then optimized using first-principles calculations, and their phonon, electronic, and elastic properties were computed. As a result, two dynamically stable structures were found: Al(CN)2 with a space group of Cmcm and Si(CN)2 with a space group of R3¯m. Their phonon spectra exhibited no imaginary frequencies; thus, their elastic constants satisfied the mechanical stability criteria. Structurally, Si(CN)2 is similar to 6H-SiC and 15R-SiC. Its elastic constants indicated that it is harder than those SiC materials. Al(CN)2 exhibits metallic properties and the indirect wide-bandgap of Si(CN)2 was calculated by the generalized gradient approximation, the local density approximation, and the screened hybrid functional of Heyd, Scuseria, and Ernzerhof (HSE06) is found to be 3.093, 3.048, and 4.589 eV, respectively. According to this wide bandgap, we can conclude that Si(CN)2 has the potential to be used in high-temperature and high-power environments, making it usable in a broad range of applications.

Keywords

• density functional theory
• crystal graph convolutional neural networks
• cyanide