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Burnley, Pamela C.

Publications and source records attributed to Burnley, Pamela C..

11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ultrahigh-pressure disordered eight-coordinated phase of Mg 2 GeO 4 : Analogue for super-Earth mantles

Mg 2 GeO 4 is important as an analog for the ultrahigh-pressure behavior of Mg 2 SiO 4 , a major component of planetary interiors. In this study, we have investigated magnesium germanate to 275 GPa and over 2,000 K using a laser-heated diamond anvil cell combined with in situ synchrotron X-ray diffraction and density functional theory (DFT) computations. The experimental results are consistent with the formation of a phase with disordered Mg and Ge, in which germanium adopts eightfold coordination with oxygen: the cubic, Th 3 P 4 -type structure. DFT computations suggest partial Mg-Ge order, resulting in a tetragonal $I\bar{4}2d$ structure indistinguishable from $I\bar{4}3d$ Th 3 P 4 in our experiments. If applicable to silicates, the formation of this highly coordinated and intrinsically disordered phase may have important implications for the interior mineralogy of large, rocky extrasolar planets.

58 GEOSCIENCES↗
DOE OSTI2019

Modeling gamma radiation exposure rates using geologic and remote sensing data to locate radiogenic anomalies

Aerial Gamma-Ray Surveys (GRS) are ideal for tracking anthropogenic gamma radiation releases and transport. The interpretation of a GRS can be complicated by natural gamma-ray sources such as atmospheric radon, cosmic rays, geologic materials, and even the survey equipment itself. Some of these complicating factors can be accounted for or corrected by calibration or mathematic techniques. Real-time algorithms that attempt to enhance potential radiogenic anomalies over background are also in use. However, natural geology is a source of significant background gamma-ray production and neither mathematical corrections nor real-time algorithmic approaches directly account for geology and geochemistry. Here in this study, we advance techniques to predict geologic background exposure rates using rapid and practical methods which can be achieved in the field. In addition we generate models that focus specifically on highlighting radiogenic anomalies for emergency response or further investigation. Predictive models developed in this study were generally able to predict background with medians of ± 1.0 μR/h compared to measured data, and were also able to highlight anomalous areas even where radiation exposure rates were within the range of natural background.

58 GEOSCIENCES↗