cff-version: 1.2.0
abstract: "<p>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.</p>"
authors:
  - family-names: Li
    given-names: Jun
  - family-names: Tezsevin
    given-names: Ilker
    orcid: "https://orcid.org/0000-0001-5648-3943"
  - family-names: Merkx
    given-names: Marc J. M.
    orcid: "https://orcid.org/0000-0002-3886-0220"
  - family-names: Maas
    given-names: Joost F. W.
  - family-names: Kessels
    given-names: Wilhelmus M. M.
    orcid: "https://orcid.org/0000-0002-7630-8226"
  - family-names: Sandoval
    given-names: Tania E.
    orcid: "https://orcid.org/0000-0001-9418-5031"
  - family-names: Mackus
    given-names: Adrie
    orcid: "https://orcid.org/0000-0001-6944-9867"
title: "Data underlying the publication: Packing of inhibitor molecules during area-selective atomic layer deposition studied using random sequential adsorption simulations"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/33df3424-ed9b-49cb-910e-64a6d37aa6b0.v1
license: CC BY 4.0
date-released: 2023-08-07