Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
Department of Chemistry, College of Idaho, Caldwell, Idaho 83605, United States.
Anal Chem. 2021 Apr 13;93(14):5890-5896. doi: 10.1021/acs.analchem.1c00244. Epub 2021 Mar 29.
Complex chemical systems that exhibit varied and matrix-dependent speciation are notoriously difficult to monitor and characterize online and in real-time. Optical spectroscopy is an ideal tool for in situ characterization of chemical species that can enable quantification as well as species identification. Chemometric modeling, a multivariate method, has been successfully paired with optical spectroscopy to enable measurement of analyte concentrations even in complex solutions where univariate methods such as Beer's law analysis fail. Here, Raman spectroscopy is used to quantify the concentration of phosphoric acid and its three deprotonated forms during a titration. In this system, univariate approaches would be difficult to apply due to multiple species being present simultaneously within the solution as the pH is varied. Locally weighted regression (LWR) modeling was used to determine phosphate concentration from spectral signature. LWR results, in tandem with multivariate curve resolution modeling, provide a direct measurement of the concentration of each phosphate species using only the Raman signal. Furthermore, results are presented within the context of fundamental solution chemistry, including Pitzer equations, to compensate for activity coefficients and nonidealities associated with high ionic strength systems.
复杂的化学体系表现出多样的和基质依赖的形态，因此很难进行在线和实时监测和表征。光谱学是一种理想的工具，可用于对化学物质进行原位表征，从而实现定量和物质识别。化学计量学建模是一种多元方法，已成功与光谱学结合使用，即使在复杂溶液中（单变量方法如比尔定律分析失败），也可以测量分析物浓度。在这里，拉曼光谱用于在滴定过程中定量磷酸及其三种去质子形式的浓度。在该系统中，由于溶液中同时存在多种物质，因此 pH 值发生变化时，单变量方法很难应用。局部加权回归 (LWR) 建模用于根据光谱特征确定磷酸盐浓度。LWR 结果与多元曲线分辨建模相结合，仅使用拉曼信号即可直接测量每种磷酸盐物质的浓度。此外，结果还结合了基本溶液化学（包括 Pitzer 方程）的内容，以补偿与高离子强度系统相关的活度系数和非理想性。
