Information-Based Development of New Radiation Detectors
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Information-Based Development of New Radiation Detectors Kim F. Ferris1, Bobbie-Jo M. Webb-Robertson1 and Dumont Jones2 1 Computational & Information Sciences, Pacific Northwest National Laboratory, Richland, WA 99352, 2,Proximate Technologies, LLC, Columbus, OH 43209 ABSTRACT With our present concern for a secure environment, the development of new radiation detection materials has focused on the capability of identifying potential radiation sources at increased sensitivity levels. As the initial framework for a materials-informatics approach to radiation detection materials, we have explored the use of both supervised (Support Vector Machines – SVM and Linear Discriminant Analysis – LDA) and unsupervised (Principal Component Analysis – PCA) learning methods for the development of structural signature models. Application of these methods yields complementary results, both of which are necessary to reduce parameter space and variable degeneracy. Using a crystal structure classification test, the use of the nonlinear SVM significantly increases predictive performance, suggesting trade-offs between smaller descriptor spaces and simpler linear models. INTRODUCTION Improvements in x-ray and gamma radiation detector performance are being actively pursued for a variety of applications, ranging from nuclear security to medical diagnostics. An ideal detection material has high sensitivity, high photon energy resolution, short decay time, radiation hardness, and is inexpensive and mechanically robust [1]. Despite this impetus, there have been relatively few candidate materials developed in the last forty years, and many of these closely related in their crystal structure and physical properties [2]. Materials informatics methods have a role in leveraging existing information to produce better radiation detectors, but also in evaluating the composite of data that has been collected thus far, assessing information gaps, and prioritizing the most critical new experiments. The development of new radiation detection materials has been hindered by a number of factors. First, property measurements of candidate materials are not abundant; moreover, measurements and calculations of the same nominal quantity (e.g. bandgap) are typically based on differing and incompletely defined environments, and may not be directly comparable. For example, it has been proposed that electronic-structure calculations of ionization energy and other properties be used to augment limited experimental radiation detector measurements [3]. But such calculations are not immediately comparable across methods and materials structures, or with experiment. Assumptions of equivalence—inadvertent or otherwise--can lead to systematic modeling error or the failure to achieve any model at all. With the above considerations in mind, we have taken several steps towards a general program of information-based materials design. The first step, perhaps ironically, is to reassess the manner in which materials data are stored and retrieved. Conventional datab
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