Abstract
Abstract
In this study, we thoroughly explored the thermal transport and thermoelectric properties of BN-co-doped phagraphene structures in the context of first-principles computations combined with machine learning interatomic potential (MLIP) techniques. Our results demonstrate that doping positions can critically tune the thermal properties, offering potential advantages for both thermoelectric and heat transfer applications. Notably, enhanced thermal conductivity has been obtained for phagraphene with 10
%
co-doping. Additionally, the rectangular structural symmetry of phagraphene plays an important role for targeted thermal transport. Further, we observe negative Grüneisen parameter in these structures, suggesting negative thermal expansion. This will serves as an unique mechanism for controlling the thermal conductivity at different frequencies. Interestingly, n-type behavior of the structures is indicative of its negative Seebeck coefficient within the temperature range of 300–900 K. Moreover, these structures display significantly larger electrical conductivity compared to other two-dimensional (2D) materials. Apart from that, the calculated figure of merit of the structures under a constant relaxation time at 300 K shows considerably better response for some specific doped structures. We believe this study will play an important role in understanding the importance of structural modifications in tailoring the thermal properties of carbon-based 2D systems.