Atomically Precise Prediction of 2D Self-Assembly of Weakly Bonded Nanostructures: STM Insight into Concentration-Dependent Architectures

El Garah M, Dianat A, Cadeddu A, Gutierrez R, Cecchini M, Cook TR, Ciesielski A, Stang PJ, Cuniberti G, Samori P (2016)


Publication Type: Journal article

Publication year: 2016

Journal

Book Volume: 12

Pages Range: 343-350

Journal Issue: 3

DOI: 10.1002/smll.201502957

Abstract

A joint experimental and computational study is reported on the concentration-dependant self-assembly of a flat C3-symmetric molecule on a graphite surface. As a model system a tripodal molecule, 1,3,5-tris(pyridin-3-ylethynyl)benzene, has been chosen, which can adopt either C3h or Cs symmetry when planar, as a result of pyridyl rotation along the alkynyl spacers. Density functional theory (DFT) simulations of 2D nanopatterns with different surface coverage reveal that the molecule can generate different types of self-assembled motifs. The stability of fourteen 2D patterns and the influence of concentration are analyzed. It is found that ordered, densely packed monolayers and 2D porous networks are obtained at high and low concentrations, respectively. A concentration-dependent scanning tunneling microscopy (STM) investigation of this molecular self-assembly system at a solution/graphite interface reveals four supramolecular motifs, which are in perfect agreement with those predicted by simulations. Therefore, this DFT method represents a key step forward toward the atomically precise prediction of molecular self-assembly on surfaces and at interfaces.

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How to cite

APA:

El Garah, M., Dianat, A., Cadeddu, A., Gutierrez, R., Cecchini, M., Cook, T.R.,... Samori, P. (2016). Atomically Precise Prediction of 2D Self-Assembly of Weakly Bonded Nanostructures: STM Insight into Concentration-Dependent Architectures. Small, 12(3), 343-350. https://doi.org/10.1002/smll.201502957

MLA:

El Garah, Mohamed, et al. "Atomically Precise Prediction of 2D Self-Assembly of Weakly Bonded Nanostructures: STM Insight into Concentration-Dependent Architectures." Small 12.3 (2016): 343-350.

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