A collection of forcefield precursors for metal-organic frameworks.

A collection of forcefield precursors for metal-organic frameworks.
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DOI:
10.1039/c9ra07327b
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发表时间:
2019-11-11
期刊:
影响因子:
3.9
通讯作者:
Manz, Thomas A.
Manz, Thomas A.
中科院分区:
化学3区
文献类型:
--
作者:
Chen, Taoyi;Manz, Thomas A.

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金属有机框架(MOFs)和其他复杂材料的许多重要性能可以通过建模统计系综来计算。主要的挑战是为这些模拟开发准确和计算效率高的交互模型。两种主要方法是(i)从头算分子动力学,其中相互作用模型由交换相关理论提供(例如,DFT +色散泛函)和(ii)分子力学中的相互作用模型是一个参数化的经典力场。第一种方法需要进一步开发以提高计算速度。第二种方法需要进一步发展,以自动化精确的力场参数化。由于数千种MOF结构的极端化学多样性,这个问题今天仍然没有得到解决。例如,在这里,我们展示了2014年CoRE MOF数据库中的结构,其中包含基于第一和第二邻居的8000多种不同的原子类型。我们的研究结果表明,原子类型的基础上的第一和第二邻居充分捕获的化学环境,但原子类型的基础上,只有第一邻居没有。对于3056个MOFs,我们使用密度泛函理论(DFT),然后进行DDEC 6原子布居分析,以提取大量重要的力场前体:部分原子电荷;材料中原子(AIM)C6,C8和C10色散系数; AIM偶极子和四极矩;各种AIM极化率;量子Drude振荡器参数; AIM电子云参数;静电参数通过与DFT计算的静电势的比较进行了验证。这些力场前体应该在开发MOF力场中找到广泛的应用。材料中原子(AIM)部分电荷、偶极和四极、色散系数(C6、C8、C10)、极化率、电子云参数、径向矩和原子类型从>3000个MOF的量子化学计算中提取。
A host of important performance properties for metal–organic frameworks (MOFs) and other complex materials can be calculated by modeling statistical ensembles. The principle challenge is to develop accurate and computationally efficient interaction models for these simulations. Two major approaches are (i) ab initio molecular dynamics in which the interaction model is provided by an exchange–correlation theory (e.g., DFT + dispersion functional) and (ii) molecular mechanics in which the interaction model is a parameterized classical force field. The first approach requires further development to improve computational speed. The second approach requires further development to automate accurate forcefield parameterization. Because of the extreme chemical diversity across thousands of MOF structures, this problem is still mostly unsolved today. For example, here we show structures in the 2014 CoRE MOF database contain more than 8 thousand different atom types based on first and second neighbors. Our results showed that atom types based on both first and second neighbors adequately capture the chemical environment, but atom types based on only first neighbors do not. For 3056 MOFs, we used density functional theory (DFT) followed by DDEC6 atomic population analysis to extract a host of important forcefield precursors: partial atomic charges; atom-in-material (AIM) C6, C8, and C10 dispersion coefficients; AIM dipole and quadrupole moments; various AIM polarizabilities; quantum Drude oscillator parameters; AIM electron cloud parameters; etc. Electrostatic parameters were validated through comparisons to the DFT-computed electrostatic potential. These forcefield precursors should find widespread applications to developing MOF force fields. Atom-in-material (AIM) partial charges, dipoles and quadrupoles, dispersion coefficients (C6, C8, C10), polarizabilities, electron cloud parameters, radial moments, and atom types were extracted from quantum chemistry calculations for >3000 MOFs.
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