Title:    Thermal properties and segregation behaviour of Pt nanowires modified with Au, Ag and Pd atoms: A Classical Molecular Dynamics Study - data

Citation
Gambu TG, Terranova U, Santos-Carballal D, et al.  (2019). Thermal properties and segregation behaviour of Pt nanowires modified with Au, Ag and Pd atoms: A Classical Molecular Dynamics Study - data. Cardiff University. https://doi.org/10.17035/d.2019.0077930441

Dataset Details

Publisher: Cardiff University

Date (year) of data becoming publicly available: 2019

Coverage start date: 01/09/2017

Coverage end date: 16/06/2019

Data format: .xlsx

Estimated total storage size of dataset: Less than 100 megabytes

Number of Files In Dataset: 1

DOI : 10.17035/d.2019.0077930441

DOI URL: http://doi.org/10.17035/d.2019.0077930441

Description

The thermal properties of bimetallic Pt nanowires have been investigated using classical interatomic potentials. Edge decorated Pt nanowires may improve the inter-facet exchange of reaction intermediates resulting in improved oxygen reduction reaction activities at fuel call cathode electrodes. In this work we report on the melting behaviour of Pt-based nanowires where either an edge atomic row or atomic shell of Pt nanowires are substituted by Au, Ag or Pd. Our overall intention is to find out if edge decorated Pt nanowires can be attained by thermally annealing mixed Pt-Au, Pt-Au or Pt-Pd nanowires—we employ a reverse approach where edge decorated nanowires are thermally treated to study their departure from a well segregated state. The data described here are Microsoft excel sheets containing the data for bond order parameter as a function of temperature for all studied Pt nanowire systems; radial pair distribution data from molecular dynamic simulation; total energy as a function of the number of successful atomic swaps obtained from energy minimization calculations and the radial pair distribution function data for energy minimized nanowires. Our molecular dynamics simulations were performed using Sutton-Chan interatomic potential as implemented in the DL-POLY Classic software.

Research results based upon these data are published at https://doi.org/10.1021/acs.jpcc.9b02730