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FROG:在道尔顿的量子力学/分子力学极化嵌入方案中利用全原子分子动力学轨迹计算分子液体的线性和非线性光学响应。

FROG: Exploiting all-atom molecular dynamics trajectories to calculate linear and non-linear optical responses of molecular liquids within Dalton's QM/MM polarizable embedding scheme.

作者信息

Le Breton Guillaume, Bonhomme Oriane, Benichou Emmanuel, Loison Claire

机构信息

Universite Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, UMR5306, F-69100, Villeurbanne, France.

出版信息

J Chem Phys. 2024 May 21;160(19). doi: 10.1063/5.0203424.

Abstract

Quantum mechanical/molecular mechanics (QM/MM) methods are interesting to model the impact of a complex environment on the spectroscopic properties of a molecule. In this context, a FROm molecular dynamics to second harmonic Generation (FROG) code is a tool to exploit molecular dynamics trajectories to perform QM/MM calculations of molecular optical properties. FROG stands for "FROm molecular dynamics to second harmonic Generation" since it was developed for the calculations of hyperpolarizabilities. These are relevant to model non-linear optical intensities and compare them with those obtained from second harmonic scattering or second harmonic generation experiments. FROG's specificity is that it is designed to study simple molecular liquids, including solvents or mixtures, from the bulk to the surface. For the QM/MM calculations, FROG relies on the Dalton package: its electronic-structure models, response theory, and polarizable embedding schemes. FROG helps with the global workflow needed to deal with numerous QM/MM calculations: it permits the user to separate the system into QM and MM fragments, to write Dalton's inputs, to manage the submission of QM/MM calculations, to check whether Dalton's calculation finished successfully, and finally to perform averages on relevant QM observables. All molecules within the simulation box and several time steps are tackled within the same workflow. The platform is written in Python and installed as a package. Intermediate data such as local electric fields or individual molecular properties are accessible to the users in the form of Python object arrays. The resulting data are easily extracted, analyzed, and visualized using Python scripts that are provided in tutorials.

摘要

量子力学/分子力学(QM/MM)方法对于模拟复杂环境对分子光谱性质的影响很有意义。在此背景下,从分子动力学到二次谐波产生(FROG)代码是一种利用分子动力学轨迹来进行分子光学性质的QM/MM计算的工具。FROG代表“从分子动力学到二次谐波产生”,因为它是为超极化率的计算而开发的。这些对于模拟非线性光学强度并将其与从二次谐波散射或二次谐波产生实验中获得的强度进行比较很重要。FROG的独特之处在于它旨在研究从本体到表面的简单分子液体,包括溶剂或混合物。对于QM/MM计算,FROG依赖于Dalton软件包:其电子结构模型、响应理论和可极化嵌入方案。FROG有助于处理大量QM/MM计算所需的整体工作流程:它允许用户将系统分离为QM和MM片段,编写Dalton的输入文件,管理QM/MM计算的提交,检查Dalton的计算是否成功完成,最后对相关的QM可观测量进行平均。模拟盒内的所有分子以及几个时间步长都在同一工作流程中处理。该平台用Python编写并作为一个软件包安装。诸如局部电场或单个分子性质等中间数据以Python对象数组的形式供用户使用。使用教程中提供的Python脚本可以轻松提取、分析和可视化所得数据。

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