Disentangling morphology and conductance in amorphous graphene

TL;DR

This paper combines deep learning simulations and percolation theory to analyze how morphology influences electronic conductance in amorphous graphene, revealing potential control mechanisms via gate voltage.

Contribution

It introduces a novel approach that avoids boundary condition issues and explores conductance dependence on morphology in amorphous graphene.

Findings

Conductance depends on morphology in amorphous graphene.

Conductance networks evolve from crystallite localization to defect localization.

Gate voltage can potentially control conductance properties.

Abstract

Amorphous graphene or amorphous monolayer carbon (AMC) is a family of carbon films that exhibit a surprising sensitivity of electronic conductance to morphology. We combine deep learning-enhanced simulation techniques with percolation theory to analyze three morphologically distinct mesoscale AMCs. Our approach avoids the pitfalls of applying periodic boundary conditions to these fundamentally aperiodic systems or equating crystalline inclusions with conducting sites. We reproduce the previously reported dependence of charge conductance on morphology and explore the limitations of partial morphology descriptors in witnessing conductance properties. Finally, we perform crystallinity analysis of conductance networks along the electronic energy spectrum and show that they metamorphose from being localized on crystallites at band edges to localized on defects around the Fermi energy opening the possibility of control through gate voltage.