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呋喃簇中非共价相互作用的QTAIM分析数据集。

QTAIM analysis dataset for non-covalent interactions in furan clusters.

作者信息

Malloum Alhadji, Conradie Jeanet

机构信息

Department of Chemistry, University of the Free State, PO BOX 339, Bloemfontein 9300, South Africa.

Department of Physics, Faculty of Science, University of Maroua, PO BOX 46, Maroua, Cameroon.

出版信息

Data Brief. 2021 Dec 24;40:107766. doi: 10.1016/j.dib.2021.107766. eCollection 2022 Feb.

DOI:10.1016/j.dib.2021.107766
PMID:35005152
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8718740/
Abstract

Furan clusters are very important to understand the dynamics and properties of the furan solvent. They can be used combined with quantum cluster equilibrium theory to theoretically determine the thermodynamics properties of the furan solvent. To understand the structures of the furan clusters, one needs to understand the non-covalent interactions that hold the furan molecules together. In this paper, we have provided the data necessary to understand the non-covalent interactions in furan clusters. Firstly, the structures of the furan clusters have been generated using classical molecular dynamics as implemented in the ABCluster code. Secondly, the generated structures have been fully optimized at the MP2/aug-cc-pVDZ level of theory. The optimized Cartesian coordinates of all the investigated structures are reported in this work to enable further investigations of the furan clusters. These Cartesian coordinates will save computational time for all further investigations involving the furan clusters. Thirdly, to understand the nature of the non-covalent interactions in furan clusters, we have performed a quantum theory of atoms in molecule (QTAIM) analysis using AIMAll program. Using QTAIM, we have provided the critical points, bond paths and their related properties for all the investigated structures. These data can be used to identify and classify the non-covalent interactions in furan clusters. The reader can refer to the original article for further information and discussion of the data provided herein Malloum and Conradie (2022) [1].

摘要

呋喃团簇对于理解呋喃溶剂的动力学和性质非常重要。它们可以与量子团簇平衡理论结合使用,从理论上确定呋喃溶剂的热力学性质。为了理解呋喃团簇的结构,需要了解将呋喃分子结合在一起的非共价相互作用。在本文中,我们提供了理解呋喃团簇中非共价相互作用所需的数据。首先,使用ABCluster代码中实现的经典分子动力学生成了呋喃团簇的结构。其次,在MP2/aug-cc-pVDZ理论水平上对生成的结构进行了完全优化。本文报告了所有研究结构的优化笛卡尔坐标,以便对呋喃团簇进行进一步研究。这些笛卡尔坐标将为所有涉及呋喃团簇的进一步研究节省计算时间。第三,为了理解呋喃团簇中非共价相互作用的本质,我们使用AIMAll程序进行了分子中的原子量子理论(QTAIM)分析。使用QTAIM,我们提供了所有研究结构的临界点、键径及其相关性质。这些数据可用于识别和分类呋喃团簇中的非共价相互作用。读者可参考原始文章以获取关于本文所提供数据的更多信息和讨论(Malloum和Conradie,(2022年)[1])。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c23e/8718740/bbbff64c83d2/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c23e/8718740/bbbff64c83d2/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c23e/8718740/bbbff64c83d2/gr1.jpg

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本文引用的文献

1
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J Mol Graph Model. 2022 Mar;111:108102. doi: 10.1016/j.jmgm.2021.108102. Epub 2021 Dec 8.
2
Exploration of the potential energy surfaces of small ethanol clusters.小乙醇团簇势能面的探索
Phys Chem Chem Phys. 2020 Jun 21;22(23):13201-13213. doi: 10.1039/d0cp01393e. Epub 2020 Jun 5.
3
Global optimization of clusters of rigid molecules using the artificial bee colony algorithm.使用人工蜂群算法对刚性分子簇进行全局优化。
Phys Chem Chem Phys. 2016 Jan 28;18(4):3003-10. doi: 10.1039/c5cp06313b.
4
ABCluster: the artificial bee colony algorithm for cluster global optimization.ABCluster:用于聚类全局优化的人工蜂群算法
Phys Chem Chem Phys. 2015 Oct 7;17(37):24173-81. doi: 10.1039/c5cp04060d. Epub 2015 Sep 1.
5
What is the covalency of hydrogen bonding?氢键的共价性是什么?
Chem Rev. 2011 Apr 13;111(4):2597-625. doi: 10.1021/cr800346f. Epub 2011 Feb 15.
6
Hydrogen bonding without borders: an atoms-in-molecules perspective.无边界的氢键:分子中原子视角
J Phys Chem A. 2006 Mar 16;110(10):3349-51. doi: 10.1021/jp060571z.