氟化铀的空间分辨拉曼光谱研究:仪器优化重要性的案例研究

IF 2.2 3区 化学 Q2 INSTRUMENTS & INSTRUMENTATION Applied Spectroscopy Pub Date : 2024-05-02 DOI:10.1177/00037028241252847
Tyler L. Spano, Hunter B. Andrews, Andrew Miskowiec, Toya N. Beiswenger, Benjamin T. Manard
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引用次数: 0

摘要

拉曼光谱是一种新兴技术,可用于快速、无损地分析用于法医和防扩散应用的核材料,因为它是区分具有类似化学计量学的材料的多种化学形式的有力工具。光谱软件的最新发展实现了快速数据收集和高速拉曼光谱绘图功能。然而,一些富铀材料在潮湿空气和/或激光诱导的相变中容易发生降解。为了减轻环境或测量相关的潜在样品降解,我们采用了一种系统的方法,为核燃料循环中重要的中间材料氟化铀(UO2F2)的高通量测量定义了优化的数据采集参数。首先,我们系统地描述了光学放大倍率(5 倍至 100 倍)、激光功率和曝光时间对获得相同颗粒 UO2F2 信号的影响,发现在低激光功率和曝光时间下,无论光学放大倍率如何,都能获得可比信号。其次,我们在数据收集过程中确保了样品的完整性;第三,收集光谱图时采用了优化参数,以缩短获得空间分辨光谱信息所需的时间。我们讨论了测量时间缩短 90% 和 99% 的问题,因为这与在相同的绘图区域内分辨颗粒光谱特征的差异有关。在这项工作中,我们发现需要额外的数据处理选项,因此开发了一个定制的 Python 脚本,用于导入、处理、分析和可视化拉曼光谱图数据。
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Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization
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.
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来源期刊
Applied Spectroscopy
Applied Spectroscopy 工程技术-光谱学
CiteScore
6.60
自引率
5.70%
发文量
139
审稿时长
3.5 months
期刊介绍: Applied Spectroscopy is one of the world''s leading spectroscopy journals, publishing high-quality peer-reviewed articles, both fundamental and applied, covering all aspects of spectroscopy. Established in 1951, the journal is owned by the Society for Applied Spectroscopy and is published monthly. The journal is dedicated to fulfilling the mission of the Society to “…advance and disseminate knowledge and information concerning the art and science of spectroscopy and other allied sciences.”
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