Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Esben L. Kolsbjerg"'
Autor:
Kræn C. Adamsen, Stig Koust, Esben L. Kolsbjerg, Lutz Lammich, Stefan Wendt, Jeppe V. Lauritsen, Bjørk Hammer
Publikováno v:
Physical Review Materials. 4
We utilized scanning tunneling microscopy (STM) experiments and density functional theory (DFT) calculations to study the diffusion of ammonia $({\mathrm{NH}}_{3})$ on anatase ${\mathrm{TiO}}_{2}(101)$. From time-lapsed STM imaging, we observed monom
Autor:
Bjørk Hammer, Esben L. Kolsbjerg, Siddharth J. Jethwa, Lutz Lammich, Kurt V. Gothelf, Sundar R. Vadapoo, Jacob R. Cramer, Trolle R. Linderoth
Publikováno v:
Jethwa, S, Kolsbjerg, E L, Vadapoo, S R, Lind Cramer, J, Lammich, L, Gothelf, K V, Hammer, B & Linderoth, T R 2017, ' Supramolecular Corrals on Surfaces Resulting from Aromatic Interactions of Nonplanar Triazoles ', ACS Nano, vol. 11, no. 8, pp. 8302-8310 . https://doi.org/10.1021/acsnano.7b03484
Interaction forces between aromatic moieties, often referred to as π–π interactions, are an important element in stabilizing complex supramolecular structures. For supramolecular self-assembly occurring on surfaces, where aromatic moieties are ty
Publikováno v:
Kolsbjerg, E L, Peterson, A A & Hammer, B 2018, ' Neural-network-enhanced evolutionary algorithm applied to supported metal nanoparticles ', Physical Review B, vol. 97, no. 19, 195424 . https://doi.org/10.1103/PhysRevB.97.195424
We show that approximate structural relaxation with a neural network enables orders of magnitude faster global optimization with an evolutionary algorithm in a density functional theory framework. The increased speed facilitates reliable identificati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17098ff7e7976b003721a35766c09c72
https://pure.au.dk/portal/da/publications/neuralnetworkenhanced-evolutionary-algorithm-applied-to-supported-metal-nanoparticles(883477dc-c66e-4c2b-870d-0df9be44882a).html
https://pure.au.dk/portal/da/publications/neuralnetworkenhanced-evolutionary-algorithm-applied-to-supported-metal-nanoparticles(883477dc-c66e-4c2b-870d-0df9be44882a).html
Publikováno v:
Kolsbjerg, E L, Groves, M N & Hammer, B 2018, ' Erratum: “An automated nudged elastic band method” [J. Chem. Phys. 145, 094107 (2016)] ', Journal of Chemical Physics, vol. 148, no. 2, 029903 . https://doi.org/10.1063/1.5021153
Autor:
Henrik Lund Mortensen, Thomas L. Jacobsen, Esben L. Kolsbjerg, Mathias Jørgensen, Knud H. Sørensen, Søren A. Meldgaard, Bjørk Hammer
Publikováno v:
Jorgensen, M S, Mortensen, H L, Meldgaard, S A, Kolsbjerg, E L, Jacobsen, T L, Sorensen, K H & Hammer, B 2019, ' Atomistic structure learning ', Journal of Chemical Physics, vol. 151, no. 5, 054111 . https://doi.org/10.1063/1.5108871
One endeavour of modern physical chemistry is to use bottom-up approaches to design materials and drugs with desired properties. Here we introduce an atomistic structure learning algorithm (ASLA) that utilizes a convolutional neural network to build
Publikováno v:
Kolsbjerg, E L, Groves, M N & Hammer, B 2016, ' An automated nudged elastic band method ', Journal of Chemical Physics, vol. 145, no. 9, 094107 . https://doi.org/10.1063/1.4961868
A robust, efficient, dynamic, and automated nudged elastic band (AutoNEB) algorithm to effectively locate transition states is presented. The strength of the algorithm is its ability to use fewer resources than the nudged elastic band (NEB) method by
Publikováno v:
Kolsbjerg, E L, Groves, M N & Hammer, B 2016, ' Pyridine adsorption and diffusion on Pt(111) investigated with density functional theory ', Journal of Chemical Physics, vol. 144, no. 16, 164112 . https://doi.org/10.1063/1.4947225
The adsorption, diffusion, and dissociation of pyridine, C5H5N, on Pt(111) are investigated with van derWaals-corrected density functional theory. An elaborate search for local minima in the adsorption potential energy landscape reveals that the inta
Publikováno v:
Meldgaard, S A, Kolsbjerg, E L & Hammer, B 2018, ' Machine learning enhanced global optimization by clustering local environments to enable bundled atomic energies ', Journal of Chemical Physics, vol. 149, 134104 . https://doi.org/10.1063/1.5048290
We show how to speed up global optimization of molecular structures using machine learning methods. To represent the molecular structures, we introduce the auto-bag feature vector that combines (i) a local feature vector for each atom, (ii) an unsupe
Publikováno v:
Kolsbjerg, E L, Goubert, G, McBreen, P H & Hammer, B 2018, ' Rotation and diffusion of naphthalene on Pt(111) ', The Journal of Chemical Physics, vol. 148, no. 12, 124703 . https://doi.org/10.1063/1.5017581
The behavior of naphthalene on Pt(111) surfaces is studied by combining insight from scanning tunneling microscopy (STM) and van der Waals enabled density functional theory. Adsorption, diffusion, and rotation are investigated by a series of variable
Autor:
Bjørk Hammer, Kræn C. Adamsen, Esben L. Kolsbjerg, Stefan Wendt, Stig Koust, Jeppe V. Lauritsen, Zhongshan Li
Publikováno v:
Koust, S, Adamsen, K C, Kolsbjerg, E L, Li, Z, Hammer, B, Wendt, S & Lauritsen, J V 2018, ' NH3 adsorption on anatase-TiO 2 (101) ', The Journal of Chemical Physics, vol. 148, no. 12, 124704 . https://doi.org/10.1063/1.5021407
The adsorption of ammonia on anatase TiO2 is of fundamental importance for several catalytic applications of TiO2 and for probing acid-base interactions. Utilizing high-resolution scanning tunneling microscopy (STM), synchrotron X-ray photoelectron s