Nanoscale Structural and Electronic Properties of Cellulose/Graphene Interfaces

Authors: Gustavo H. Silvestre, Felipe Crasto de Lima, Juliana S. Bernardes, Adalberto Fazzio, Roberto H. Miwa

arXiv: 2208.11742v1 - DOI (cond-mat.mtrl-sci)
License: CC BY 4.0

Abstract: The development of electronic devices based on the functionalization of (nano)cellulose platforms relies upon an atomistic understanding of the structural, and electronic properties of the combined system, cellulose/functional element. In this work, we present a theoretical study of the nanocellulose/graphene interface (nCL/G) based on first-principles calculations. We find that the binding energies of both hydrophobic/G (nCL$^{\rm phob}$/G) and hydrophilic/G (nCL$^{\rm phil}$/G) interfaces are primarily dictated by the van der Waals interactions, and are comparable with that of their 2D interface counterparts. We verify that the energetic preference of nCL$^{\rm phob}$/G has been reinforced by the inclusion of an aqueous media via the implicit solvation model. Further structural characterization was carried out using a set of simulations of Carbon K-edge X-ray absorption spectra to identify and distinguish the key absorption features of the nCL$^{\rm phob}$/G and nCL$^{\rm phil}$/G interfaces. The electronic structure calculations reveal that the linear energy bands of graphene lie in the band gap of the nCL, sheet, while depletion/accumulation charge density regions are observed. We show that external agents, i.e. electric field and mechanical strain, allow for tunability of the Dirac cone and the charge density at the interface. The control/maintenance of the Dirac cone states in nCL/G is an important feature for the development of electronic devices based on cellulosic platforms.

Submitted to arXiv on 24 Aug. 2022

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.