Computational modeling and neutron imaging to understand interface shape and solute segregation during the vertical gradient freeze growth of BaBrCl:Eu

•We employ computational models and neutron imaging to understand VGF growth.•Changes in the shape of the solid/liquid interface are explained.•Complicated segregation behavior is observed and understood via model results.•Neutron imaging and modeling reveal what has been hidden in melt crystal grow...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of crystal growth 2020-04, Vol.536 (C), p.125572, Article 125572
Hauptverfasser: Derby, Jeffrey J., Zhang, Chang, Seebeck, Jan, Peterson, Jeffrey H., Tremsin, Anton S., Perrodin, Didier, Bizarri, Gregory A., Bourret, Edith D., Losko, Adrian S., Vogel, Sven C.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•We employ computational models and neutron imaging to understand VGF growth.•Changes in the shape of the solid/liquid interface are explained.•Complicated segregation behavior is observed and understood via model results.•Neutron imaging and modeling reveal what has been hidden in melt crystal growth. We apply continuum models to analyze phase change, heat transfer, fluid flow, solute transport, and segregation in order to understand prior neutron imaging observations of the vertical gradient freeze growth of Eu-doped BaBrCl. The models provide a rigorous framework in which to understand the mechanisms that are responsible for the complicated evolution of interface shape and dopant distribution in the growth experiment. We explain how a transition in the solid/liquid interface shape from concave to convex is driven by changes in radial heat transfer caused by furnace design. We also provide a mechanistic explanation of how dynamic growth conditions and changes of the flow structure in the melt result in complicated segregation patterns in this system. A growth pause caused by controller lock-up is shown to result in a band of solute depletion in accordance with classical theory. However, changing flow patterns during growth result in a non-monotonic axial distribution of solute that cannot be explained by simple application of classical segregation models. We assert that the approach presented here, namely the use of rigorous models in conjunction advanced diagnostics, such as neutron imaging, provides an exciting path forward for process optimization and control, accelerating the incremental advances that have, in the past, typically relied on empiricism, experience, and intuition.
ISSN:0022-0248
1873-5002
DOI:10.1016/j.jcrysgro.2020.125572