Issue 22, 2011
From the journal:

Physical Chemistry Chemical Physics

Modelling molecule–surface interactions—an automated quantum-classical approach using a genetic algorithm

Claudia R. Herbers,a   Karen Johnstonb  and  Nico F. A. van der Vegt*a  

* Corresponding authors

a Center of Smart Interfaces-TU Darmstadt, Petersenstr. 32, 64287 Darmstadt, Germany
E-mail: vandervegt@csi.tu-darmstadt.de
Fax: +49 06151 162048
Tel: +49 06151 164356

b Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany

Abstract

We present an automated and efficient method to develop force fields for molecule–surface interactions. A genetic algorithm (GA) is used to parameterise a classical force field so that the classical adsorption energy landscape of a molecule on a surface matches the corresponding landscape from density functional theory (DFT) calculations. The procedure performs a sophisticated search in the parameter phase space and converges very quickly. The method is capable of fitting a significant number of structures and corresponding adsorption energies. Water on a ZnO(0001) surface was chosen as a benchmark system but the method is implemented in a flexible way and can be applied to any system of interest. In the present case, pairwise Lennard Jones (LJ) and Coulomb potentials are used to describe the molecule–surface interactions. In the course of the fitting procedure, the LJ parameters are refined in order to reproduce the adsorption energy landscape. The classical model is capable of describing a wide range of energies, which is essential for a realistic description of a fluid–solid interface.

Graphical abstract: Modelling molecule–surface interactions—an automated quantum-classical approach using a genetic algorithm

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Article information

DOI
https://doi.org/10.1039/C0CP02889D
Article type
Paper
Submitted
16 Dec 2010
Accepted
09 May 2011
First published
18 May 2011

Phys. Chem. Chem. Phys., 2011,13, 10577-10583

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Modelling molecule–surface interactions—an automated quantum-classical approach using a genetic algorithm

C. R. Herbers, K. Johnston and N. F. A. van der Vegt, Phys. Chem. Chem. Phys., 2011, 13, 10577 DOI: 10.1039/C0CP02889D

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