Electronic and thermal transport in novel carbon-based bilayer with tetragonal rings: a combined study using first-principles and machine learning approach
Abstract
In this article, the structural, electronic and thermal transport characteristics of bilayer tetragonal graphene (TG) are systematically explored with a combination of first-principles calculations and machine-learning interatomic potential approaches. Optimized ground state geometry of the bilayer TG structure is predicted and examined by employing various stability criteria. Electronic bandstructure analysis confirmed that bilayer TG exhibits a metallic band structure similar to the monolayer T-graphene structure. Thermal transport characteristics of the bilayer TG structure are explored by analysing thermal conductivity, the Seebeck coefficient, and electrical conductivity. The electronic part of the thermal conductivity shows linearly increasing behaviour with temperature, however the lattice part exhibits the opposite character. The lattice thermal conductivity part is investigated in terms of the three phonon scattering rates and weighted phase space. On the other hand, the Seebeck coefficient goes through a transition from negative to positive values with increasing temperature. The Wiedemann–Franz law regarding electrical transport of the bilayer TG is verified and confirms the universal Lorentz number. Specific heat of the bilayer TG structure follows the Debye model at low temperature and constant behaviour at high temperature. Moreover, the Debye temperature of the bilayer TG structure is verified by ab initio calculations as well as fitting the specific heat data using the Debye model.
- This article is part of the themed collections: 2021 PCCP HOT Articles and Emerging AI Approaches in Physical Chemistry