Data underlying the publication: Packing of inhibitor molecules during area-selective atomic layer deposition studied using random sequential adsorption simulations

doi:10.4121/33df3424-ed9b-49cb-910e-64a6d37aa6b0.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/33df3424-ed9b-49cb-910e-64a6d37aa6b0
Datacite citation style:
Li, Jun; Tezsevin, Ilker; Merkx, Marc J. M.; Maas, Joost F. W.; Kessels, Wilhelmus M. M. et. al. (2023): Data underlying the publication: Packing of inhibitor molecules during area-selective atomic layer deposition studied using random sequential adsorption simulations. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/33df3424-ed9b-49cb-910e-64a6d37aa6b0.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This dataset includes raw and processed data published in manuscript "Packing of inhibitor molecules during area-selective atomic layer deposition studied using random sequential adsorption simulations". Area-selective atomic layer deposition (ALD) can be achieved by functionalization of the area where no growth is desired with inhibitor molecules. The packing of these inhibitor molecules, in terms of molecule arrangement and surface density, plays a vital role in deactivating the surface by blocking the precursor adsorption. Here, we performed random sequential adsorption (RSA) simulations to investigate the packing of small molecule inhibitors (SMIs) on a surface to predict how effective the SMI blocks precursor adsorption. We demonstrated that RSA simulations provide an insightful and straightforward method for screening SMIs in terms of their potential for area-selective ALD. This Dataset includes all the simulation and experimental data used in the manuscript. In the 'Processed data" folder, the reader can find the Matlab code to run RSA simulations, original figure files and data files. The "Raw data" folder includes all Matlab input and outputs without any editing.

history
  • 2023-08-07 first online, published, posted
publisher
4TU.ResearchData
format
image files: (.xcf, .pdf, .tif, .fig, .png), Origin and Matlab files: (.opju, .m, .mat), BASH files: (.sh, .slurm)
funding
  • European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 949202)
  • ANID FONDECYT (Agencia Nacionalde Investigación y Desarrollo - Fondo Nacional de DesarrolloCientífico y Tecnológico) 11180906
organizations
Eindhoven University of Technology, Department of Applied Physics, The Netherlands;
Universidad Técnica Federico Santa María, Department of Chemical and Environmental Engineering, Santiago, Chile

DATA

files (2)