Nano Archive

A genetic algorithm approach to probing the evolution of self-organized nanostructured systems

Siepmann, Peter and Martin, Christopher P. and Vancea, Ioan and Moriarty, Philip J. and Krasnogor, Natalio (2007) A genetic algorithm approach to probing the evolution of self-organized nanostructured systems. NANO LETTERS, 7 (7). pp. 1985-1990.

Full text is not hosted in this archive but may be available via the Official URL, or by requesting a copy from the corresponding author.

Official URL: http://pubs.acs.org/doi/abs/10.1021/nl070773m

Abstract

We present a new methodology, based on a combination of genetic algorithms and image morphometry, for matching the outcome of a Monte Carlo simulation to experimental observations of a far-from-equilibrium nanosystem. The Monte Carlo model used simulates a colloidal solution of nanoparticles drying on a solid substrate and has previously been shown to produce patterns very similar to those observed experimentally. Our approach enables the broad parameter space associated with simulated nanoparticle self-organization to be searched effectively for a given experimental target morphology.

Item Type:Article
Subjects:Physical Science > Nanophysics
Biomedical Science > Nanobiotechnology
ID Code:3558
Deposited By:Farnush Anwar
Deposited On:16 Jan 2009 16:03
Last Modified:16 Jan 2009 16:03

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