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首页> 外文期刊>Journal of chemical theory and computation: JCTC >Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction II: Nonplanar Molecules
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Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction II: Nonplanar Molecules

机译:Exchange-Hole偶极散分散模型用于分子晶体结构预测中的精度排名II:非平面分子

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摘要

The crystal structure prediction (CSP) of a given compound from its molecular diagram is a fundamental challenge in computational chemistry with implications in relevant technological fields. A key component of CSP is the method to calculate the lattice energy of a crystal, which allows the ranking of candidate structures. This work is the second part of our investigation to assess the potential of the exchange hole dipole moment (XDM) dispersion model for crystal structure prediction. In this article, we study the relatively large, nonplanar, mostly flexible molecules in the first five blind tests held by the Cambridge Crystallographic Data Centre. Four of the seven experimental structures are predicted as the energy minimum, and thermal effects are demonstrated to have a large impact on the ranking of at least another compound. As in the first part of this series, delocalization error affects the results for a single crystal (compound X), in this case by detrimentally overstabilizing the pi-conjugated conformation of the monomer. Overall, B86bPBE-XDM correctly predicts 16 of the 21 compounds in the five blind tests, a result similar to the one obtained using the best CSP method available to date (dispersion corrected PW91 by Neumann et al.). Perhaps more importantly, the systems for which B86bPBE-XDM fails to predict the experimental structure as the energy minimum are mostly the same as with Neumann's method, which suggests that similar difficulties (absence of vibrational free energy corrections, delocalization error,...) are not limited to B86bPBE-XDM but affect GGA-based DFT-methods in general. Our work confirms B86bPBE-XDM as an excellent option for crystal energy ranking in CSP and offers a guide to identify crystals (organic salts, conjugated flexible systems) where difficulties may appear.
机译:来自其分子图的给定化合物的晶体结构预测(CSP)是计算化学的基本挑战,具有相关技术领域的影响。 CSP的一个关键组分是计算晶体的晶格能量的方法,这允许候选结构的排名。这项工作是我们调查的第二部分,以评估晶体结构预测的交换孔偶极力矩(XDM)分散模型的电位。在本文中,我们研究了剑桥晶体数据中心持有的前五个盲试验中的相对较大的非平面,主要是灵活的分子。七个实验结构中的四种预测为能量最小,并且对至少另一种化合物的排名产生热影响。与本系列的第一部分一样,临床化误差会影响单晶(化合物X)的结果,在这种情况下,通过不利地覆盖单体的pi缀合的构象。总体而言,B86BPBE-XDM在五个盲试验中正确预测21个化合物中的16个化合物中的16个,其结果类似于使用迄今为止可用的最佳CSP方法获得的结果(通过Neumann等人的分散校正PW91。)。或许更重要的是,B86BPBE-XDM无法预测实验结构的系统,因为能量最小值大多与Neumann的方法相同,这表明类似的困难(没有振动的自由能校正,删除误差,......)不限于B86BPBE-XDM,而是影响基于GGA的DFT-方法。我们的工作确认B86BPBE-XDM作为CSP中晶体能量排名的一个优秀选择,并提供识别晶体(有机盐,共轭柔性系统)的指南,可能出现困难。

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