(212a) Time-Dependent, Thermal-Capillary Analyses of the Micro-Pull-Down Crystal Growth System | AIChE

(212a) Time-Dependent, Thermal-Capillary Analyses of the Micro-Pull-Down Crystal Growth System

Authors 

Samanta, G. - Presenter, University of Minnesota
Yeckel, A. - Presenter, University of Minnesota
Derby, J. J. - Presenter, University of Minnesota


The micro-pull-down crystal growth technique is becoming increasingly popular to grow small-diameter, fiber crystals.  Recently, it is also being developed for quick screening of promising scintillator crystals for radiation detectors in the crystal growth facility of E.D. Bourret-Courchesne at Lawrence Berkeley National Laboratory (LBNL).  In this use, time delays are often associated with establishing suitable growth conditions for micro-pull-down experiments for new materials that have never been grown before. 

The goal of our research is to develop computational models that can address the determination of suitable growth conditions in the micro-pull-down systems using a minimal amount of information.  In keeping with this goal, we first developed a two- dimensional, quasi-steady-state (QSS), thermal-capillary model of the micro-pull-down system to grow sapphire crystals. We used this model to identify growth windows with respect to process parameters representing heater input, ambient temperature, pull rate, and melt static head. However, we did not establish the stability of the QSS solution branches.

In this presentation, we focus on results from transient simulations of the thermal- capillary model used to establish the stability behavior of those solution branches. For this purpose, starting with a quasi-steady-state solution, we provide step changes to any of the process parameters stated above and evolve the thermal-capillary system in time. By following the crystal radius evolution over time, we conclude whether a particular solution branch is stable or not. We also conduct transient simulations of a batchwise set-up of the micro-pull-down process and, for the first time, present temporal predictions of system evolution.

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