Tuesday, November 6, 2007 - 5:00 PM
323f

Computational Models To Improve The Growth Of Radiation Detector Crystals

David Gasperino1, Lisa Lun1, Andrew Yeckel1, and Jeffrey J. Derby2. (1) Chemical Engineering and Materials Science, University of Minnesota, 151 Amundson Hall, Minneapolis, MN 55455, (2) Chemical Eningeering and Materials Science, University of Minnesota, 151 Amundson Hall, Minneapolis, MN 55455-0132

Crystals are the central materials element of most gamma radiation detection systems, yet there remains relatively little fundamental understanding about how these crystals grow and, especially, how crystal growth conditions affect the properties of grown crystals. The inherent properties of many of these crystals makes their growth challenging; however, much of the blame for the lack of progress is the very conservative nature of crystal growth process engineering. Crystal growth is often described as an art, and process developments are typically incremental, based on prior experience and empiricism. Therefore, modeling can serve as a powerful tool to complement experiments and characterization. It provides an important approach to close the loop between materials discovery, device research, systems performance, and producibility

In this paper, we discuss our efforts to model gradient freeze furnaces used to grow large crystals of cadmium zinc telluride (CZT) at Pacific Northwest National Laboratories and Wahington State University. Specifically, we present simulations from detailed analyses in which a global model, CrysVUn developed by the Crystal Growth Laboratory, Erlangen, Germany, that computes high-temperature, furnace heat transfer, is coupled with a local model, Cats2D developed by our group, which solves for heat transfer, incompressible melt flow, and melt-crystal interface shape. The global model includes all of the details of the furnace and ampoule assembly, while the local model is chosen to consist only of the melt, interface, and a portion of the crystal. These models are solved using an iterative scheme to compute a self-consistent solution.

We present results from model validation experiments and discuss initial computations of parametric sensitivity for these growth processes. With a self-consistent model of the crystal growth apparatus and the growing crystal, we are able to explore methods of improving the crystal growth process. Of particular interest is how different growth strategies are predicted to impact the shape of and thermal gradients near the crystal interface.