Schild Axel
Laboratory for Physical Chemistry, ETH Zürich, Zurich, Switzerland.
Front Chem. 2019 Jun 6;7:424. doi: 10.3389/fchem.2019.00424. eCollection 2019.
For localized and oriented vibrationally excited molecules, the qualitative features of the one-body probability density of the nuclei (one-nucleus density) are investigated. Like the familiar and widely used one-electron density that represents the probability of finding an electron at a given location in space, the one-nucleus density represents the probability of finding a nucleus at a given position in space independent of the location of the other nuclei and independent of their type. In contrast to the electrons, however, the nuclei are comparably localized. Due to this localization of the individual nuclei, the one-nucleus density provides a quantum-mechanical representation of the "chemical picture" of the molecule as an object that can largely be understood in a three-dimensional space, even though its full nuclear probability density is defined on the high-dimensional configuration space of all the nuclei. We study how the nodal structure of the wavefunctions of vibrationally excited states translates to the one-nucleus density. It is found that nodes do not necessarily lead to visible changes in the one-nucleus density: Already for relatively small molecules, only certain vibrational excitations change the one-nucleus density qualitatively compared to the ground state. It turns out that there are simple rules for predicting the shape of the one-nucleus density from the normal mode coordinates. A Python module for the computation of the one-nucleus density is provided at https://gitlab.com/axelschild/mQNMc.
对于局域化且取向的振动激发分子，研究了原子核单体概率密度（单核密度）的定性特征。如同表示在空间给定位置找到一个电子概率的广为人知且广泛使用的单电子密度一样，单核密度表示在空间给定位置找到一个原子核的概率，该概率与其他原子核的位置及其类型无关。然而，与电子不同的是，原子核相对局域化。由于单个原子核的这种局域化，单核密度提供了分子“化学图像”的量子力学表示，该分子作为一个物体在很大程度上可以在三维空间中理解，尽管其完整的核概率密度是在所有原子核的高维构型空间上定义的。我们研究振动激发态波函数的节点结构如何转化为单核密度。结果发现，节点不一定会导致单核密度出现明显变化：对于相对较小的分子，与基态相比，只有某些振动激发会使单核密度发生定性变化。事实证明，从简正模式坐标预测单核密度的形状有一些简单规则。可在https://gitlab.com/axelschild/mQNMc获取用于计算单核密度的Python模块。
