Process Systems Engineering (AVT.SVT), 9165RWTH Aachen University, Aachen, Germany.
Energy Systems Engineering, Institute for Energy and Climate Research IEK-10, Jülich, Germany.
Appl Spectrosc. 2021 May;75(5):506-519. doi: 10.1177/0003702820973275. Epub 2020 Dec 4.
We propose an approach for monitoring the concentration of dissociated carboxylic acid species in dilute aqueous solution. The dissociated acid species are quantified employing inline Raman spectroscopy in combination with indirect hard modeling (IHM) and multivariate curve resolution (MCR). We introduce two different titration-based hard model (HM) calibration procedures for a single mono- or polyprotic acid in water with well-known (method A) or unknown (method B) acid dissociation constants p. In both methods, spectra of only one acid species in water are prepared for each acid species. These spectra are used for the construction of HMs. For method A, the HMs are calibrated with calculated ideal dissociation equilibria. For method B, we estimate p values by fitting ideal acid dissociation equilibria to acid peak areas that are obtained from a spectral HM. The HM in turn is constructed on the basis of MCR data. Thus, method B on the basis of IHM is independent of a priori known p values, but instead provides them as part of the calibration procedure. As a detailed example, we analyze itaconic acid in aqueous solution. For all acid species and water, we obtain low HM errors of < 2.87 × 10mol mol in the cases of both methods A and B. With only four calibration samples, IHM yields more accurate results than partial least squares regression. Furthermore, we apply our approach to formic, acetic, and citric acid in water, thereby verifying its generalizability as a process analytical technology for quantitative monitoring of processes containing carboxylic acids.
我们提出了一种监测稀水溶液中游离羧酸浓度的方法。采用在线拉曼光谱结合间接硬建模（IHM）和多变量曲线分辨（MCR）定量分析游离酸。我们引入了两种不同的基于滴定的硬模型（HM）校准程序，用于在水中具有已知（方法 A）或未知（方法 B）酸离解常数 p 的单一或多元酸。在这两种方法中，对于每种酸，仅在水中制备一种酸的光谱。这些光谱用于构建 HMs。对于方法 A，使用计算出的理想解离平衡来校准 HMs。对于方法 B，我们通过拟合理想酸解离平衡来估计 p 值，从光谱 HM 中获得酸峰面积。HM 反过来是基于 MCR 数据构建的。因此，基于 IHM 的方法 B 不依赖于先验已知的 p 值，而是将其作为校准过程的一部分提供。作为一个详细的例子，我们分析了水溶液中的衣康酸。对于所有的酸和水，在方法 A 和 B 的情况下，HM 的误差都低于 2.87×10-3mol/mol。仅用四个校准样品，IHM 比偏最小二乘回归得到更准确的结果。此外，我们将我们的方法应用于甲酸、乙酸和柠檬酸在水中，从而验证了它作为一种定量监测含羧酸过程的过程分析技术的通用性。
