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Investigation on the thermodynamic stability of nanocrystalline W-based alloys: A combined theoretical and experimental approach

TitoloInvestigation on the thermodynamic stability of nanocrystalline W-based alloys: A combined theoretical and experimental approach
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2021
AutoriTorre, F., Mingazzini C., Mirabile Gattia Daniele, Huminiuc T., Rinaldi A., Polcar T., Delogu F., and Locci A.M.
Parole chiaveAluminum alloys, Ball milling, Binary alloys, Experimental approaches, Grain boundaries, Grain-boundaries, Length scale, Metal alloys, Nanocrystalline alloys, Nanocrystallines, Nanocrystals, Nanostructured metals, Novel theoretical approaches, Segregated structures, Silver alloys, Stability prediction, System stability, Theoretical approach, Thermodynamic stability

The stability of nanostructured metal alloys is currently being extensively investigated, and several mathematical models have been developed to describe the thermodynamics of these systems. However, model capability in terms of thermal stability predictions strongly relies on grain boundary-related parameters that are difficult to measure or estimate accurately. To overcome this limitation, a novel theoretical approach is proposed and adopted in this work to identify W-based nanocrystalline alloys which are potentially able to show thermodynamic stability. A comparison between model outcomes and experimental findings is reported for two selected alloys, namely W-Ag and W-Al. Experimental results clearly highlight that W-Ag mixtures retain a segregated structure on relatively coarse length scales even after prolonged mechanical treatments. Moreover, annealing at moderate temperatures readily induces demixing of the constituent elements. In contrast, homogeneous nanostructured W-Al solid solutions are obtained by ball milling of elemental powders. These alloys show enhanced thermal stability with respect to pure W even at high homologous temperatures. Experimental evidences agree with model predictions for both the investigated systems. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.


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Citation KeyTorre2021