Tuning Electronic Properties of Nanoporous Graphene

Different nanoporous graphene structures have shown great promise for a wide variety of applications. However, due to limitations in experimental or computational throughput, nanoporous graphenes have not been investigated systematically. In this work, we combine density functional theory and machine learning to study 460 structures of nanoporous graphene made from four different templates. We shed light on structure-band gap relations and perform molecular dynamics simulations and phonon calculations in order to determine the role of electron-phonon coupling on the renormalization of temperature-dependent band gaps. Our results uncover that certain subsets of nanoporous graphene exhibit a similar trend in the band gap as a function of a structural parameter as has been observed for armchair graphene nanoribbons. Furthermore, we find that electron-phonon coupling varies over a large range in the investigated nanoporous graphenes and that it drives the closing of the band gap with larger temperatures. Finally, we suggest nanoporous graphene structures for different applications, such as field-effect transistors. Thus, our work can help guide the development and improvement of nanoporous graphene-based devices.