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Research.fi
Dataset . 2022
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F4TCNQ and TTF on approximate supported graphene, 3D surface adsorbate search with BOSS

Authors: Järvi, Jari; Todorović, Milica; Rinke, Patrick;

F4TCNQ and TTF on approximate supported graphene, 3D surface adsorbate search with BOSS

Abstract

These datasets were employed in the manuscript: [1] J. Järvi, M. Todorović, and P. Rinke, Efficient modeling of organic adsorbates on oxygen-intercalated graphene on Ir(111), Phys. Rev. B 105, 195304 (2022). DOI: 10.1103/PhysRevB.105.195304 The two datasets feature DFT sampling of adsorption configurations for F4TCNQ and TTF on approximate supported graphene (Gr) using the Bayesian Optimization Structure Search (BOSS) method. The 3D configurational searches were conducted for each molecule over two molecular translations (x, y) and an in-plane rotation (gamma). The search range of on-surface translation (x, y) is [0, 1] in fractional coordinates of the Gr unit cell. The in-plane rotation (gamma) is done in the range [0, 180] deg. Energy (Eads) is the adsorption energy of F4TCNQ or TTF on the approximate supported Gr, computed with DFT. For additional details on search coordinates and DFT calculations please refer to [1]. The 3D models of the adsorption energy surfaces were constructed with 500 energy points for each molecule, the full lists are provided in the datasets. Each calculation is denoted with an ID number (001-500). The raw data for each calculation can be found in the NOMAD repository with the corresponding ID, DOI: 10.17172/NOMAD/2022.04.07-1

Country
Finland
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Keywords

organic surface adsorbates, Bayesian inference, structure search, density-functional theory

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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