论文标题

使用实时依赖性密度理论的电离水链中的质子转移动力学

Proton-transfer dynamics in ionized water chains using real-time Time Dependent Density Functional Theory

论文作者

Sharma, Vidushi, Fernández-Serra, Marivi

论文摘要

在光电离水基系统的密度功能理论研究中,电荷定位在质子转移动力学中的作用尚不清楚。这是由于在存在交换和相关功能误差的情况下提取耦合电子 - 核非绝热动态的贡献的固有复杂性。在这项工作中,我们通过使用实时依赖时间的密度功能理论(RT-TDDFT)基于基于时间的EHRENFEST动力学来模拟电离线性H键簇的模型系统来解决此问题。我们的目的是了解半局部交换和相关功能中的自我交流误差如何影响质子转移的概率。特别是,我们表明,对于H键(h $ _2 $ o)$ _ n^+$链(带有$ n> 3 $),质子转移概率可达到最大值,与混合功能的预测相当。这是因为在延长的H键结构中,半叉型几何形状的形成在很大程度上被抑制。我们还展示了初始光孔的定位程度如何连接到质子转移反应的概率,以及电子电荷和核电荷之间的分离。将这些结果与具有绝热动力学获得的结果进行了比较,在这种动力学中,允许初始波函数放松到离子簇的基态,从而解释了为什么不同的功能和动力学方法会导致定量不同的结果。

In density functional-theoretic studies of photoionized water-based systems, the role of charge localization in proton-transfer dynamics is not well understood. This is due to the inherent complexity in extracting the contributions of coupled electron-nuclear non-adiabatic dynamics in the presence of exchange and correlation functional errors. In this work, we address this problem by simulating a model system of ionized linear H-bonded water clusters using real-time Time Dependent Density Functional Theory (rt-TDDFT)-based Ehrenfest dynamics. Our aim is to understand how self-interaction error in semilocal exchange and correlation functionals affects the probability of proton transfer. In particular, we show that for H-bonded (H$_2$O)$_n^+$ chains (with $n>3$), the proton-transfer probability attains a maximum, becoming comparable to that predicted by hybrid functionals. This is because the formation of hemibonded-type geometries is largely suppressed in extended H-bonded structures. We also show how the degree of localization of the initial photo-hole is connected to the probability of a proton-transfer reaction, as well as to the separation between electronic and nuclear charge. These results are compared to those obtained with adiabatic dynamics where the initial wavefunction is allowed to relax to the ground state of the ion cluster, explaining why different functionals and dynamical approaches lead to quantitatively different results.

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