Nano Science and Technology Institute
Nanotech 2011 Vol. 2
Nanotech 2011 Vol. 2
Nanotechnology 2011: Electronics, Devices, Fabrication, MEMS, Fluidics and Computational
 
Chapter 9: Nano & Micro: Computational Methods, Simulation & Software Tools
 

The Self-Assembly of Nano-Objects code (SANO-Grid) using Grid Interpolation technique: Application to epitaxial organic monolayers adsorbed on metal surfaces

Authors:T.J. Roussel, L.F. Vega
Affilation:Consejo Superior de Investigaciones Científicas. (ICMAB-CSIC), ES
Pages:579 - 582
Keywords:self-assembly, OMBE, Monte-Carlo
Abstract:One of the main challenges is to precisely position the first molecular building blocks in the first layer of thin films in order to tune their hetero-epitaxial properties, or else to adjust the substrates for further steps of growth. A fine balance of weak lateral molecule-molecule interactions and stronger molecule-substrate interactions governs their thermodynamic properties, nucleation and growth mechanisms. Especially with multi-components monolayers since their physical properties are composition dependent. To simulate the self-assembly of large flat-molecules (i.e. more than 50 atoms/molecule), the computational effort required increases rapidly with the number of molecules, and drastically when their number of atoms is consequent. Hence, to model the adsorption of several hundreds to thousands of molecules (meaning systems of ~105 atoms) with a statistical mechanics approach, the internal degrees of freedom of the molecules and the substrates were frozen. It allows us performing full Grand Canonical Monte-Carlo calculations by implementing the grid interpolation technique. We describe the system using empirical model, which provides transferability to many organic molecules and metal surfaces and the approach keeps the same precision than atomistic simulations. We provide some examples for different organic flat molecules adsorbed on different metal surfaces, including defects on the surface.
ISBN:978-1-4398-7139-3
Pages:854
Hardcopy:$199.95
 
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