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Bona-fide method for the determination of short range order and transport properties in a ferro-aluminosilicate slag.
Karalis, Konstantinos T; Dellis, Dimitrios; Antipas, Georgios S E; Xenidis, Anthimos.
  • Karalis KT; School of Mining Engineering and Metallurgy, National Technical University of Athens, Zografou Campus, Athens 15780, Greece.
  • Dellis D; Greek Research &Technology Network, Mesogeion 56, Athens 11527, Greece.
  • Antipas GS; School of Mining Engineering and Metallurgy, National Technical University of Athens, Zografou Campus, Athens 15780, Greece.
  • Xenidis A; School of Mining Engineering and Metallurgy, National Technical University of Athens, Zografou Campus, Athens 15780, Greece.
Sci Rep ; 6: 30216, 2016 07 26.
Article en En | MEDLINE | ID: mdl-27455915
ABSTRACT
The thermodynamics, structural and transport properties (density, melting point, heat capacity, thermal expansion coefficient, viscosity and electrical conductivity) of a ferro-aluminosilicate slag have been studied in the solid and liquid state (1273-2273 K) using molecular dynamics. The simulations were based on a Buckingham-type potential, which was extended here, to account for the presence of Cr and Cu. The potential was optimized by fitting pair distribution function partials to values determined by Reverse Monte Carlo modelling of X-ray and neutron diffraction experiments. The resulting short range order features and ring statistics were in tight agreement with experimental data and created consensus for the accurate prediction of transport properties. Accordingly, calculations yielded rational values both for the average heat capacity, equal to 1668.58 J/(kg·K), and for the viscosity, in the range of 4.09-87.64 cP. The potential was consistent in predicting accurate values for mass density (i.e. 2961.50 kg/m(3) vs. an experimental value of 2940 kg/m(3)) and for electrical conductivity (5.3-233 S/m within a temperature range of 1273.15-2273.15 K).

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2016 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2016 Tipo del documento: Article