通过实验设计、化学计量学和拉曼光谱遥感硝酸和温度

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
David V. Russell, Luke R. Sadergaski*, Jeffrey D. Einkauf, Laetitia H. Delmau and Jonathan D. Burns*, 
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引用次数: 0

摘要

本研究介绍了一种通过优化实验设计、化学计量学和拉曼光谱对硝酸(0.1-9 M)和温度(20-60 °C)进行定量的有效方法。拉曼光谱可以使用光导纤维部署在热室环境中,以支持核领域和工业中的加工操作。化学操作经常使用硝酸,并在非环境温度下运行,这可能是设计原因,也可能是环境原因。工业领域应用拉曼光谱定量硝酸的例子比比皆是。然而,温度对定量的影响往往被忽视,在实际应用中应加以考虑。实验的统计设计用于建立部分最小二乘回归和支持向量回归(SVR)模型的训练集。采用非线性核的 SVR 模型在温度方面的表现优于顶级部分最小二乘模型,对硝酸和温度的预测均方根误差分别为 1.8% 和 2.3%。与传统的七级全因子方案相比,D-优化设计策略减少了 75% 的取样时间。新方法推动了化学计量学在核领域和工业内外的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Remote Sensing of Nitric Acid and Temperature via Design of Experiments, Chemometrics, and Raman Spectroscopy

This study presents an effective method for the quantification of nitric acid (0.1–9 M) and the temperature (20–60 °C) through optimal experimental design, chemometrics, and Raman spectroscopy. Raman spectroscopy can be deployed using fiber-optic cables in hot cell environments to support processing operations in the nuclear field and industry. Chemical operations frequently use nitric acid and operate at nonambient temperatures either by design or by circumstance. Examples of Raman spectroscopy for the quantification of nitric acid with applications in the industrial field are profuse. However, the effect of temperature on quantification is often ignored and should be considered in real-world scenarios. Statistical design of experiments was used to build training sets for partial least-squares regression and support vector regression (SVR) models. The SVR model with a nonlinear kernel outperformed the top partial least-squares models with respect to temperature and resulted in percent root-mean-square error of prediction of 1.8% and 2.3% for nitric acid and temperature, respectively. The D-optimal design strategy decreased the sampling time by 75% compared to a more traditional seven-level full factorial option. The new method advances chemometric applications within and beyond the nuclear field and industry.

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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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