Wöhl Justus, Kopp Wassja A, Yevlakhovych Iryna, Bahr Leo, Koß Hans-Jürgen, Leonhard Kai
Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany.
J Phys Chem A. 2022 May 12;126(18):2845-2853. doi: 10.1021/acs.jpca.2c01061. Epub 2022 Apr 27.
The spectroscopic quantification of mixture compositions usually requires pure compounds and mixtures of known compositions for calibration. Since they are not always available, methods to fill such gaps have evolved, which are, however, not generally applicable. Therefore, calibration can be extremely challenging, especially when multiple unstable species, for example, intermediates, exist in a system. This study presents a new calibration approach that uses molecular dynamics (AIMD)-simulated spectra to set up and calibrate models for the physics-based spectral analysis method indirect hard modeling (IHM). To demonstrate our approach called AIMD-IHM, we analyze Raman spectra of ternary hydrogen-bonding mixtures of acetone, methanol, and ethanol. The derived AIMD-IHM pure-component models and calibration coefficients are in good agreement with conventionally generated experimental results. The method yields compositions with prediction errors of less than 5% without any experimental calibration input. Our approach can be extended, in principle, to infrared and NMR spectroscopy and allows for the analysis of systems that were hitherto inaccessible to quantitative spectroscopic analysis.
混合物成分的光谱定量分析通常需要纯化合物和已知成分的混合物进行校准。由于它们并非总是可得,填补此类空白的方法不断发展,然而这些方法并不普遍适用。因此,校准可能极具挑战性,尤其是当系统中存在多种不稳定物种(例如中间体)时。本研究提出了一种新的校准方法,该方法使用分子动力学(AIMD)模拟光谱来建立和校准基于物理的光谱分析方法间接硬建模(IHM)的模型。为了展示我们称为AIMD-IHM的方法,我们分析了丙酮、甲醇和乙醇的三元氢键混合物的拉曼光谱。推导得到的AIMD-IHM纯组分模型和校准系数与传统生成的实验结果高度吻合。该方法在无需任何实验校准输入的情况下,得到的成分预测误差小于5%。原则上,我们的方法可以扩展到红外光谱和核磁共振光谱,并允许分析迄今为止无法进行定量光谱分析的系统。