Datasets used in the paper "Electrostatic Discovery Atomic Force Microscopy"



Dataset of molecules used for generating the training data for the machine learning models as well as simulated and experimental atomic force microscopy (AFM) data used in the paper "Electrostatic Discovery Atomic Force Microscopy".

The molecules in molecules_rebias.tar.gz are saved in the xyz format containing the atomic coordinates, elements, and partial charges.

The AFM data is in edafm-data.tar.gz, and contains data for six different systems:

-1-bromo-3,5-dichlorobenzene (BCB)
-N2-(2-chloroethyl)-N-(2,6-dimethylphenyl)-N2-methylglycinamide (NCM)
-4-pyridinecarboxylic acid, 2-[(1E)-2-thienylmethylene]-hydrazide (PTH)
-tetrathiafulvalene thiadiazole (TTF-TDZ)
-perylenetetracarboxylic dianhydride (PTCDA)
-a cluster of seven water molecules on Cu(111)
Both simulated and experimental data are provided for BCB, PTCDA, and the water cluster, while the other three only have simulated data.

For each system, there are AFM images obtained both with a CO and a Xe tip, saved in the data_CO.npz and data_Xe.npz numpy files. In each npz file there are three data entries: "data", "lengthX", and "lengthY", which contain the image data, and the physical extent of the scan region in Ånströms in the x and y directions.

Additionally the archive contains for each system the "Electrostatic Map" descriptor in ESMapHartree.npy numpy file, the molecule geometry in, and a png image of the molecule.
Koska saatavilla11 elok. 2021

Dataset Licences

  • CC-BY-4.0

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