Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Author:

Spano Tyler L.1ORCID,Andrews Hunter B.2ORCID,Miskowiec Andrew1,Beiswenger Toya N.1,Manard Benjamin T.3ORCID

Affiliation:

1. Nuclear Nonproliferation Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

2. Radioisotope Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

3. Chemical Science Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

Abstract

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO2F2), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO2F2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. During this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

Funder

UT-Battelle

Publisher

SAGE Publications

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