Contacts:
Tue Gunst, DTU Nanotech, (tue.gunst@nanotech.dtu.dk)
Mads Brandbyge, DTU Nanotech, (mads.brandbyge@nanotech.dtu.dk)
In a transmission electron microscope (TEM), in situ high precision writing by an electron beam can be used for nanoperforating graphene. In this project we will examine the mechanical properties of experimentally realized graphene nanoholes (see figure) obtained from the high resolution TEM images at DTU-CEN in the center for nanostructured graphene (www.cng.dtu.dk). However, in the TEM obtains a 2D projection of the atomic positions rather than the full 3D information. The buckling of the graphene membrane is important for many properties such as electron transport and chemical reactivity and therefore it is of great interest to try to obtain information about this based on the 2D information.
In this project we will employ computer molecular dynamics simulation (MD) based on an empirical potential for the atom-atom interactions and the 2D input from the TEM experiments in order to try to find the most likely corresponding 3D structures. We will perform molecular dynamics simulations in order to access the stability of the structures at finite temperatures.
The project idea can be sketched as:
INPUT: 2D bond-length projections obtained from experiments (TEM+Math)[1,2]
PROJECT: Use 2D projected bondlengths from TEM in a Molecular Dynamics simulation (Brenner potential[3,4]) + kinetic Monte-Carlo simulation (kMC).
OUTPUT/AIM: 3D information: out-of-plane buckling, local strain.
- MD relaxation:
Strain versus local binding energy of carbon atoms.
Is it easier to kick out atoms, where it is strained/buckling (use binding energy in kinetic Monte-Carlo simulation[6,7])?
Quantify increase in reactivity where the system is strained/buckled[5].
The exact nature of the project will depend upon the student's interests. Possible further activities could include:
a) Molecular dynamics of structures extracted from high resolution TEM images.
b) Modelling of the e-beam knock-out damage for creating the structures.
c) Simulations of thermal expansion in nanostructured graphene.
Prerequisite:
Interest in computer simulation. Preferably some experience with matlab, python or similar.
Nice-to-have: Basic knowledge of quantum physics and solid state physics is recommended.
References
[1] Pattern recognition approach to quantify the atomic structure of graphene, Jens Kling et al. DOI: http://dx.doi.org/10.1016/j.carbon.2014.03.013
Reference: CARBON 8837, March 2014;
[2] J. S. Vestergaard et al. ,Structure identication in high-resolution transmission electron microscopy images: an example on graphene, Jens Kling, et al., Submitted to Pattern Recognition,
[3] Brenner potential: D. W. Brenner, et al.,J. Phys. Cond. Mat. 14, 783 (2002);
[4] GULP Molecular Dynamics program: J. D. Gale, Journal of the Chemical Society, Faraday Transactions 93, 629 (1997).
[5] J. T. Rasmussen et al. , Electronic and transport properties of kinked graphene, Beilstein J. Nanotechnol. 2013, 4, 103–110.
[6] J. Kotakoski et al., "Kinetic Monte Carlo simulations of the response of carbon nanotubes to electron irradiation", J. Comp. Theor. Nanoscience 4 (2007) 1153-1159.
[7] A. V. Krasheninnikov et al., "Engineering of nanostructured carbon materials with electron or ion beams", Nature Materials, 6 (2007) 723
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