Three-dimensional Reconstructions and Quantitative Indicators for colloidal particles in Dry and Liquid Conditions in Scanning Transmission Electron Microscope (STEM)

  1. Arenas Esteban, Daniel 1
  2. Wang, Da 1
  3. Kadu, Ajinkya 1
  4. Bals, Sara 1
  5. Liz-Marzán, Luis 2
  1. 1 University of Antwerp
    info

    University of Antwerp

    Amberes, Bélgica

    ROR https://ror.org/008x57b05

  2. 2 Universidade de Vigo
    info

    Universidade de Vigo

    Vigo, España

    ROR https://ror.org/05rdf8595

Editor: Zenodo

Año de publicación: 2024

Tipo: Dataset

CC BY 4.0

Resumen

This dataset accompanies the research presented in the paper: Esteban, D.A., Wang, D., Kadu, A., Olluyn, N., Iglesias, A.S., Perez, A.G., Casablanca, J.G., Nicolopoulos, S., Liz-Marzán, L.M. and Bals, S., 2023. Liquid phase fast electron tomography unravels the true 3D structure of colloidal assemblies. arXiv preprint arXiv:2311.05309. [link] It provides a comprehensive collection of three-dimensional reconstructions and quantitative descriptors for small colloidal particles. These gold nanoparticles are arranged in tetrahedral and other intricate geometries under both dry and liquid conditions. The dataset contains 3D reconstructions and quantitative indicators such as centroids, volumes, surface areas, solidity measures, and principal axis lengths for assemblies with 4, 5, and 6 particles.  The dataset includes: N4_dry_dart.rec and N4_liquid_dart.rec for the 3D reconstructions of an assembly with 4 particles in dry and liquid conditions respectively; N4_quant_descriptors_dry.mat and N4_quant_descriptors_liquid.mat providing quantitative descriptors for these conditions. Similar files are provided for assemblies with 5 and 6 particles, such as N5_dry_dart.rec, N5_liquid_dart.rec, N5_quant_descriptors_dry.mat, N5_quant_descriptors_liquid.mat, and the corresponding files for N6.  This dataset can be used to study the structural dynamics of nanoparticle assemblies and studies in colloidal chemistry, materials science, and nanotechnology. The .rec files can be visualized using volume rendering software (e.g. Amira or Avizo), while the .mat files contain structured data for analysis in MATLAB. The supporting code and scripts for this dataset are available on the GitHub repository: https://github.com/ajinkyakadu/LiquidET_NatComm2024.