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Adsorption of Oxygen on Low Miller index Surfaces of hcp Cobalt

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posted on 2024-09-18, 10:29 authored by Barbara FarkasBarbara Farkas, A Cadi-Essadek, David Santos CarballalDavid Santos Carballal, NH de Leeuw
As characteristics of the cobalt nanoparticles are directly connected to the properties and behaviour of the dominant surfaces, to model their oxidation each surface has to be examined separately. Data for seven low Miller index surfaces is stored in one .xlsx file. As surfaces are built from the hcp cobalt bulk, first data Sheet has lattice vectors, coordinates, and total free energy of the optimised hexagonal cell with two cobalt atoms, together with electronic (density of state) and mechanic (bulk modulus) properties. Lattice constant is given as a scaling factor for the accompanying matrix with lattice vectors, followed by the number of atoms and their coordinates (x,y,z). Structures of seven surfaces are given in the same format in the second data Sheet which also contains the most important surface properties - workfunction (eV) and magnetisation of each atom and the whole system (µB). In the third Sheet there are total free energy, magnetisation (µB), and vibrational frequencies (cm-1) of oxygen molecule in gas phase, later included in the oxidation process. Following seven Sheets contain energetic (total free energy) and electronic (Bader charges and magnetisation) changes for each of seven surfaces, starting from clean surface (N=0) to surface with a full coverage of oxygen. Adsorption sites (top, bridge, hollow) have been stated next to the number of oxygen atoms considered (N). All units have been given alongside the name of the physical property. 

Data has been generated through the density functional theory as implemented in the VASP code, and therefore all information is in the form as provided by the software.

Research results based upon these data are published at https://doi.org/10.1016/j.mtla.2019.100381


Funding

Computational Nano-materials and Catalysis (2017-10-01 - 2020-09-30); Farkas, Barbara. Funder: Engineering and Physical Sciences Research Council

History

Language(s) in dataset

  • English-Great Britain (EN-GB)

Data-collection start date

2017-10-02

Data-collection end date

2018-05-01

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    School of Chemistry

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