Water O鈥揌 Stretching Raman Signature for Strong Acid Monitoring via Multivariate Analysis

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• 作者：Amanda J. Casella ; Tatiana G. Levitskaia ; James M. Peterson ; Samuel A. Bryan
• 刊名：Analytical Chemistry
• 出版年：2013
• 出版时间：April 16, 2013
• 年：2013
• 卷：85
• 期：8
• 页码：4120-4128
• 全文大小：420K
• 年卷期：v.85,no.8(April 16, 2013)
• ISSN：1520-6882

文摘

A distinct need exists for real time information on an acid concentration of industrial aqueous streams. Acid strength affects efficiency and selectivity of many separation processes, including nuclear fuel reprocessing. Despite the seeming simplicity of the problem, no practical solution has been offered yet, particularly for the large-scale schemes involving toxic streams such as highly radioactive nuclear wastes. The classic potentiometric technique is not amiable for online measurements due to the requirements of frequent calibration/maintenance and poor long-term stability in aggressive chemical and radiation environments. Therefore, an alternative analytical method is needed. In this work, the potential of using Raman spectroscopic measurements for online monitoring of strong acid concentration in solutions relevant to dissolved used nuclear fuel was investigated. The Raman water signature was monitored for solution systems containing nitric and hydrochloric acids and their sodium salts of systematically varied composition, ionic strength, and temperature. The trivalent neodymium ion simulated the presence of multivalent f metals. The Gaussian deconvolution analysis was used to interpret observed effects of the solution nature on the Raman water O鈥揌 stretching spectrum. The generated Raman spectroscopic database was used to develop predictive multivariate regression models for the quantification of the acid and other solution components, as well as selected physicochemical properties. This method was validated using independent experiments conducted in a flow solvent extraction system.