Citation

BibTex format

@article{Savazzi:2018:10.1021/acs.jpclett.8b00421,
author = {Savazzi, F and Risplendi, F and Mallia, G and Harrison, NM and Cicero, G},
doi = {10.1021/acs.jpclett.8b00421},
journal = {Journal of Physical Chemistry Letters},
pages = {1746--1749},
title = {Unravelling some of the structure-property relationships in graphene oxide at low degree of oxidation},
url = {http://dx.doi.org/10.1021/acs.jpclett.8b00421},
volume = {9},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Graphene oxide (GO) is a versatile 2D material whose properties can be tuned by changing the type and concentration of oxygen-containing functional groups attached to its surface. However, a detailed knowledge of the dependence of the chemo/physical features of this material on its chemical composition is largely unknown. We combine classical molecular dynamics and density functional theory simulations to predict the structural and electronic properties of GO at low degree of oxidation and suggest a revision of the Lerf–Klinowski model. We find that layer deformation is larger for samples containing high concentrations of epoxy groups and that correspondingly the band gap increases. Targeted chemical modification of the GO surface appears to be an effective route to tailor the electronic properties of the monolayer for given applications. Our simulations also show that the chemical shift of the C-1s XPS peak allows one to unambiguously characterize GO composition, resolving the peak attribution uncertainty often encountered in experiments.
AU - Savazzi,F
AU - Risplendi,F
AU - Mallia,G
AU - Harrison,NM
AU - Cicero,G
DO - 10.1021/acs.jpclett.8b00421
EP - 1749
PY - 2018///
SN - 1948-7185
SP - 1746
TI - Unravelling some of the structure-property relationships in graphene oxide at low degree of oxidation
T2 - Journal of Physical Chemistry Letters
UR - http://dx.doi.org/10.1021/acs.jpclett.8b00421
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000429626900043&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
VL - 9
ER -

Computational Materials Science

Computational Materials Science