We present a method to create and erase spatially resolved doping profiles in graphenehexagonal boron nitride (hBN) heterostructures. The technique is based on photo-induced doping by a focused laser and does neither require masks nor photo resists. This makes our technique interesting for rapid prototyping of unconventional electronic device schemes, where the spatial resolution of the rewritable, long-term stable doping profiles is only limited by the
Graphene-based conductors such as films and fibers aim to transfer graphene's extraordinary properties to the macroscopic scale. They show great potential for large-scale applications, but there is a lack of theoretical models to describe their electrical characteristics. We present a network simulation method to model the electrical conductivity of graphene-based conductors. The method considers all of the relevant microscopic parameters such as graphene flake conductivity, interlayer conductivity, packing density, and flake size. To provide a mathematical framework, we derive an analytical expression, which reproduces the essential features of the network model. We also find good agreement with experimental data. Our results offer production guidelines and enable the systematic optimization of high-performance graphene-based conductor materials. A generalization of the model to any conductor based on two-dimensional materials is straightforward.
Graphene films have emerged as a promising nanostructured material class to exploit graphene's outstanding nanoscopic properties on the macroscale. Their potential applications include solar cells (Eda et al 2008 Appl. Phys. Lett.
92, 233305; Müllen et al 2008 Nano Lett.
8, 323–7), antennas (Zhang et al 2018 Electronics
7, 285; Song et al 2018 Carbon
130, 164–9), or electromagnetic interference shielding (Zhou et al 2017 Nanoscale
9, 18613–8; Wan et al 2017 Carbon
122, 74–81; Wang et al 2018 Small
14, 1704332), all of which require a high electrical conductivity. While an outstanding electrical conductivity is a key feature of pristine graphene monolayers, the transfer to the macroscale is challenging. Here, we combined theory and experiment to quantify the impact of specific structural graphene film properties. We synthesized graphene films with systematically varied flake sizes, studied their electrical conductivities, and found excellent agreement to simulations with a three-dimensional random resistor network model. In a further percolation-type study, we computed the critical share of non-conductive elements in a graphene film θ
c = 10% where a substantial loss of electrical conductivity occurs. We prepared mixed films from graphene and graphene oxide to validate the threshold experimentally. In combination, experiments and simulations provide a coherent picture of how the graphene film microstructure is related to the macroscopic electrical conductivity (Rizzi et al 2018 ACS Appl. Mater. Interfaces
10 43088–94; Rizzi et al 2019 Comput. Mater. Sci.
161, 364–70). Our findings provide valuable insights for the production of highly conductive graphene-based macro-materials.
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