4.1 Article Data Paper

Datasets for the microstructure of nanoscale metal network structures and for its evolution during coarsening

Journal

DATA IN BRIEF
Volume 29, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.dib.2019.105030

Keywords

Nanoporous metal; Bicontinuous microstructure; Network structure; Coarsening; Topological genus; Spinodal decomposition; Surface energy anisotropy; Kinetic Monte Carlo simulation

Funding

  1. Deutsche Forschungsgemeinschaft [192346071 - SFB 986]

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The datasets in this work are files containing atom position coordinates of volume elements approximating nanoporous gold made by dealloying and annealing. The material is represented in an as-prepared state and in various stages of coarsening, as described in Phys. Rev. Mater, 3 (2019) 076001. Realistic initial structures of different solid fractions have been constructed by the leveled-wave algorithm, approximating mixtures at the end of early-stage spinodal decomposition. The microstructural evolution during coarsening by surface diffusion was approximated by onlattice kinetic Monte-Carlo simulation. The data sets refer to solid fractions from 0.22 to 0.50, providing for different initial connectivity of the bicontinuous structures. Coarsening at two temperatures, 900 K and 1800 K, explores two different degrees of surface energy anisotropy - more faceted at 900 K and more rough at 1800 K. Each structure takes the form of a face-centred cubic lattice with approximately 32 million sites. A site can be occupied by either void or atom. 3D periodic boundary conditions are satisfied. Tables list each structure's properties, and specifically the specific surface area, two different measures for the ligament size, the net topological genus as well as the scaled genus. The atom coordinate files may serve as the basis for geometry analysis and for atomistic as well as finite element simulation studies of nanoporous as well as spinodally decomposed materials. The data sets are accessible via the TORE repository at http://hdl.handle.net/11420/3253. (C) 2020 The Authors. Published by Elsevier Inc. This is an open access article under

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