Ni-Al alloy system has been identified as an important superalloy binary system. Alloys of this system combine high temperature resistance, high strength, and low density. There have been great scientific interests in the development of alloys from the melt owing to the technological demand in an array of applications because of the superior operating features of Ni-Al superalloys at high temperatures.
Properties and microstructure of solidified alloys are majorly determined by heat and mass transport along with liquid state thermodynamics. Therefore, in-depth understanding of the transport and thermodynamic properties of liquid alloys can provide essential information that can be helpful in enhancing quality of alloys and processing paths in the solid state.
Researchers have put their efforts in trying to understand and forecast solidification processes implementing phase-field modelling. Unfortunately, phase-field modeling is currently based on scarce experimental databases of transport and thermodynamic properties of liquid alloys. Experimental measurements of heat and mass transport in liquid alloys are quite challenging. Chemical reactivity, high temperature, and crystallization triggered by container walls are a few factors that can make difficult the experimental analysis of liquid alloys. Therefore, accurate and self-consistent databases for transport and thermodynamic properties of liquid alloys are needed for engineering microstructure of crystal alloys. Such databases are also needed to establish theoretical relations between different transport coefficients in order to enable a quantitative prediction of unknown coefficients from those that can be measured most reliably in experiment.
Doctor Elena Levchenko and colleagues at the University of Newcastle in Australia presented an extensive and a self-consistent database of diffusion and thermotransport properties of molecular-dynamics model of Nickel-Aluminum melts implementing an embedded-atom method potential. The database was generated over a wide range of temperature and composition. The authors undertook a careful comparison of their simulation results with the existing fragmentary experimental data in a bid to ensure reliability of the proposed model description of Ni-Al melts. They performed a comprehensive analysis of the diffusion and thermotransport features of molecular-dynamics models of Ni-Al melts. Their research work is published in peer-reviewed journal, Acta Materialia.
The research team observed that the kinetics of the collective diffusion in the melts was slower than it is normally forecast by the Darken Approximation. They also observed that the Manning factor, which characterizes the relationship between the kinetics of the collective and tracer (single-particle) diffusion, exhibited a composition dependence that had a fairly identical shape as the composition dependence of the mixing enthalpy.
The authors then developed a phenomenological equation for the composition dependence of the enthalpy of mixing in the models of melts, and applied it to facilitate the analysis of partial enthalpies of Nickel and Aluminum species necessary for accurate characterization of thermotransport. As a result, Dr Levchenko and her team computed that the reduced heat of transport, which characterizes the pure heat conduction initiated by the collective diffusion in isothermal conditions, revealed Nickel and Aluminum segregation in the Ni-Al melts, to the cold and hot ends in the presence of a temperature gradient, respectively. This finding is in agreement with a recent exploratory experimental study of thermotransport in Al78.5 Ni21.5 melt.
The approach presented in this work has a great importance for developing and testing of theoretical frameworks to enable sophisticated control of the heat and mass transport in binary melts. Overall, the authors highlighted that the generation and analysis of accurate and self-consistent databases for the transport and thermodynamic properties of binary melts with the aid of the molecular-dynamics method can be considered as one of emerging directions of theoretical and computational materials science and engineering. Very recently, Dr Levchenko and her team have advanced this approach to obtain theoretical insight into relationship between single-particle and collective diffusion observed in both experiment and simulation [Physica A: Statistical Mechanics and its Applications, volume 490 (2018), pages 1446-1453].
Elena V. Levchenko, Tanvir Ahmed, and Alexander V. Evteev. Composition dependence of diffusion and thermotransport in Ni-Al melts: A step towards molecular dynamics assisted databases. Acta Materialia, volume 136 (2017), pages 74-89.
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