Electromechanics of Twisted Graphene Nanoribbons

Abstract

Graphene nanoribbons are the flimsiest material systems in the world, and they get readily distorted. Distortion by twisting, for one, is important because it couples to ribbon's electronic properties. In this Letter, using simulations with density-functional tight-binding and revised periodic boundary conditions, I show that twisting appears almost equivalent to stretching; electronic structures in a given nanoribbon either upon twisting or upon certain stretching are quantitatively similar. This simple equivalence will provide a valuable guideline for interpreting and designing experiments with these flimsy ribbons.

3 pages, 3 figures

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Cited by in corpus (19)

• Twisting Graphene Nanoribbons into Carbon Nanotubes
• Cyclic Density Functional Theory : A route to the first principles simulation of bending in nanostructures
• Helicoidal Graphene Nanoribbons: Chiraltronics
• Topological Signatures in the Electronic Structure of Graphene Spirals
• Graphene nanoribbons subject to gentle bends
• Revised Periodic Boundary Conditions: Fundamentals, Electrostatics, and the Tight-Binding Approximation
• Bending-Induced Delamination of van der Waals Solids
• Ab initio framework for systems with helical symmetry: theory, numerical implementation and applications to torsional deformations in nanostructures
• Optically Forged Diffraction-Unlimited Ripples in Graphene
• Bending-induced extension in two-dimensional crystals
• Quantum Simulations of One-Dimensional Nanostructures under Arbitrary Deformations
• Rippling of two-dimensional materials by line defects
• Twisting or untwisting graphene twisted nanoribbons without rotation
• Electronic Structure and Carrier Mobilities of Twisted Graphene Helix
• Electronic Structure Trends of Möbius Graphene Nanoribbons from Minimal-Cell Simulations
• Twisted ultrathin silicon nanowires: a possible torsion electromechanical nanodevice
• Twisted Helical shaped Graphene Nano-Ribbons: Role of Symmetries and Passivation
• Length and torsion dependence of thermal conductivity in twisted graphene nanoribbons
• Machine learning based prediction of the electronic structure of quasi-one-dimensional materials under strain