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Chemistry Computational Surface Science Group

Publications

No. of Publications: 70

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Long-range dispersion-inclusive machine learning potentials for structure search and optimization of hybrid organic–inorganic interfaces

Long-range dispersion-inclusive machine learning potentials for structure search and optimization of hybrid organic–inorganic interfaces

J. Westermayr, S. Chaudhuri, A. Jeindl, O. T. Hofmann, R. J. Maurer, Digital Discovery DOI:10.1039/D2DD00016D (2022)

"We present an ML approach that enables fast, yet accurate, structure optimizations by combining two different types of deep neural networks trained on high-level electronic structure data. The first model is a short-ranged interatomic ML potential trained on local energies and forces, while the second is an ML model of effective atomic volumes derived from atoms-in-molecules partitioning. The latter can be used to connect short-range potentials to well-established density-dependent long-range dispersion correction methods. For two systems, specifically gold nanoclusters on diamond (110) surfaces and organic π-conjugated molecules on silver (111) surfaces, we show the ability of the models to deliver highly efficient structure optimizations and semi-quantitative energy predictions of adsorption structures."

Wed 15 Jun 2022, 10:54 | Tags: Materials structure search, global optimization, machine learning, Density Functional Theory, metal surface, dispersion interactions, many body dispersion, FHIaims

Global structure search for molecules on surfaces: Efficient sampling with curvilinear coordinates

Global structure search for molecules on surfaces: Efficient sampling with curvilinear coordinates

Konstantin Krautgasser, Chiara Panosetti, Dennis Palagin, Karsten Reuter, Reinhard J. Maurer, J. Chem. Phys. 145, 084117 (2016)

We extend our curvilinear coordinate global optimization method to efficiently sample adsorbate structures on surfaces.

Tue 17 Oct 2017, 22:07 | Tags: Density Functional Tight-Binding, Materials structure search, global optimization, semi-empirical methods, metal surface, curvilinear coordinates, Retinoic Acid

Global materials structure search with chemically-motivated coordinates

Global materials structure search with chemically-motivated coordinates

C. Panosetti, K. Krautgasser, D. Palagin, K. Reuter, R. J. Maurer, Nano Lett., 15, 8044-8048 (2015)

We define general purpose coordinates which facilitate computational structure search in cluster and material science.

Mon 16 Oct 2017, 23:06 | Tags: Density Functional Tight-Binding, Materials structure search, global optimization, Silicon clusters, Silicon surface, Basin Hopping, curvilinear coordinates

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