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用于分子晶体结构预测中精确能量排序的交换孔偶极色散模型II:非平面分子

Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction II: Nonplanar Molecules.

作者信息

Whittleton Sarah R, Otero-de-la-Roza A, Johnson Erin R

机构信息

Department of Chemistry, Dalhousie University , 6274 Coburg Road, Halifax, Nova Scotia, Canada B3H 4R2.

Department of Chemistry, University of British Columbia , Okanagan, 3247 University Way, Kelowna, British Columbia, Canada VIV 1V7.

出版信息

J Chem Theory Comput. 2017 Nov 14;13(11):5332-5342. doi: 10.1021/acs.jctc.7b00715. Epub 2017 Oct 3.

Abstract

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 π-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.

摘要

从分子图预测给定化合物的晶体结构(CSP)是计算化学中的一项基本挑战,在相关技术领域具有重要意义。CSP的一个关键组成部分是计算晶体晶格能的方法,该方法可以对候选结构进行排序。这项工作是我们评估交换空穴偶极矩(XDM)色散模型用于晶体结构预测潜力的研究的第二部分。在本文中,我们研究了剑桥晶体学数据中心进行的前五次盲测中相对较大、非平面且大多具有柔性的分子。七个实验结构中的四个被预测为能量最低结构,并且热效应被证明对至少另一种化合物的排序有很大影响。与本系列的第一部分一样,离域误差影响单晶(化合物X)的结果,在这种情况下,它会过度稳定单体的π共轭构象,从而产生不利影响。总体而言,B86bPBE-XDM在五次盲测中正确预测了21种化合物中的16种,这一结果与使用迄今为止可用的最佳CSP方法(Neumann等人的色散校正PW91)得到的结果相似。也许更重要的是,B86bPBE-XDM未能将实验结构预测为能量最低结构的系统与Neumann方法的情况基本相同,这表明类似的困难(缺乏振动自由能校正、离域误差……)不仅限于B86bPBE-XDM,而是普遍影响基于广义梯度近似(GGA)的密度泛函理论(DFT)方法。我们的工作证实了B86bPBE-XDM是CSP中晶体能量排序的一个优秀选择,并为识别可能出现困难的晶体(有机盐、共轭柔性系统)提供了指导。

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