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Datasets for the microstructure of nanoscale metal network structures and for its evolution during coarsening
Citation Link: https://doi.org/10.15480/336.2393
Type
Dataset
Date Issued
2019-10-24
Author(s)
Language
English
Institute
TORE-URI
Abstract
The description of the data format as well as the analysis processes for data have been summarized in the file "Description_of_data.pdf" (the last file in this data list). 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 on-lattice 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 topologic 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.
Subjects
nanoporous metal
bicontinuous microstructures
network structures
coarsening
topological genus
spinodal decomposition
surface energy anisotropy
kinetic Monte Carlo simulation
DDC Class
500: Naturwissenschaften
Funding Organisations
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