School of Chemistry, University of Southampton, Southampton SO17 1BJ, U.K.
J Chem Theory Comput. 2021 Mar 9;17(3):1988-1999. doi: 10.1021/acs.jctc.0c01101. Epub 2021 Feb 2.
We describe the implementation of a Monte Carlo basin hopping (BH) global optimization procedure for the prediction of molecular crystal structures. The BH method is combined with quasi-random (QR) structure generation in a hybrid method for crystal structure prediction, QR-BH, which combines the low-discrepancy sampling provided by QR sequences with BH efficiency at locating low energy structures. Through tests on a set of single-component molecular crystals and co-crystals, we demonstrate that QR-BH provides faster location of low energy structures than pure QR sampling, while maintaining the efficient location of higher energy structures that are important for identifying important polymorphs.
我们描述了一种用于预测分子晶体结构的蒙特卡罗（Monte Carlo） basin hopping（BH）全局优化程序的实现。BH 方法与准随机（quasi-random，QR）结构生成相结合，形成了一种晶体结构预测的混合方法，即 QR-BH，它结合了 QR 序列提供的低差异采样和 BH 在定位低能结构方面的效率。通过对一组单组分分子晶体和共晶的测试，我们证明 QR-BH 比纯 QR 采样更快地定位低能结构，同时保持了对识别重要多晶型体至关重要的高能结构的高效定位。
