Morawietz Tobias, Marsalek Ondrej, Pattenaude Shannon R, Streacker Louis M, Ben-Amotz Dor, Markland Thomas E
Department of Chemistry, Stanford University , Stanford, California 94305, United States.
Charles University, Faculty of Mathematics and Physics, Ke Karlovu 3, 121 16 Prague 2, Czech Republic.
J Phys Chem Lett. 2018 Feb 15;9(4):851-857. doi: 10.1021/acs.jpclett.8b00133. Epub 2018 Feb 7.
While many vibrational Raman spectroscopy studies of liquid water have investigated the temperature dependence of the high-frequency O-H stretching region, few have analyzed the changes in the Raman spectrum as a function of temperature over the entire spectral range. Here, we obtain the Raman spectra of water from its melting to boiling point, both experimentally and from simulations using an ab initio-trained machine learning potential. We use these to assign the Raman bands and show that the entire spectrum can be well described as a combination of two temperature-independent spectra. We then assess which spectral regions exhibit strong dependence on the local tetrahedral order in the liquid. Further, this work demonstrates that changes in this structural parameter can be used to elucidate the temperature dependence of the Raman spectrum of liquid water and provides a guide to the Raman features that signal water ordering in more complex aqueous systems.
虽然许多关于液态水的振动拉曼光谱研究都考察了高频O-H伸缩区域的温度依赖性，但很少有研究分析拉曼光谱在整个光谱范围内随温度的变化。在这里，我们通过实验以及使用从头算训练的机器学习势进行模拟，获得了水从熔点到沸点的拉曼光谱。我们利用这些光谱来归属拉曼谱带，并表明整个光谱可以很好地描述为两个与温度无关的光谱的组合。然后，我们评估哪些光谱区域对液体中的局部四面体有序性表现出强烈依赖性。此外，这项工作表明，这个结构参数的变化可用于阐明液态水拉曼光谱的温度依赖性，并为在更复杂的水体系中指示水有序性的拉曼特征提供了指导。
