Accurate Neural Network Description of Surface Phonons in Reactive Gas-Surface Dynamics: N-2 + Ru(0001)

A publication (journal article) of the University of Göttingen

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​Accurate Neural Network Description of Surface Phonons in Reactive Gas-Surface Dynamics: N-2 + Ru(0001)​
Shakouri, K.; Behler, J. ; Meyer, J. & Kroes, G.-J.​ (2017) 
The Journal of Physical Chemistry Letters8(10) pp. 2131​-2136​.​

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Authors
Shakouri, Khosrow
Behler, Joerg 
Meyer, Joerg
Kroes, Geert-Jan
Abstract
Ab initio molecular dynamics (AIMD) simulations enable the accurate description of reactive molecule-surface scattering especially if energy transfer involving surface phonons is important. However, presently, the computational expense of AIMD rules out its application to systems where reaction probabilities are smaller than about 1%. Here we show that this problem can be overcome by a high-dimensional neural network fit of the molecule-surface interaction potential, which also incorporates the dependence on phonons by taking into account all degrees of freedom of the surface explicitly. As shown for N-2 + Ru(0001), which is a prototypical case for highly activated dissociative chemisorption, the method allows an accurate description of the coupling of molecular and surface atom motion and accurately accounts for vibrational properties of the employed slab model of Ru(0001). The neural network potential allows reaction probabilities as low as 10(-5) to be computed, showing good agreement with experimental results.
Issue Date
2017
Status
published
Type
Journal Article
Publisher
Amer Chemical Soc
Journal
The Journal of Physical Chemistry Letters 
ISSN
1948-7185

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