Vilhena J G, Greff da Silveira Leandro, Livotto Paolo Roberto, Cacelli Ivo, Prampolini Giacomo
Department of Physics, University of Basel, Klingelbergstrasse 82, 4056 Basel, Switzerland.
Instituto de Química, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves 9500, CEP 91501-970 Porto Alegre, Brazil.
J Chem Theory Comput. 2021 Jul 13;17(7):4449-4464. doi: 10.1021/acs.jctc.1c00213. Epub 2021 Jun 29.
The reliability of molecular dynamics (MD) simulations in predicting macroscopic properties of complex fluids and soft materials, such as liquid crystals, colloidal suspensions, or polymers, relies on the accuracy of the adopted force field (FF). We present an automated protocol to derive specific and accurate FFs, fully based on ab initio quantum mechanical (QM) data. The integration of the Joyce and Picky procedures, recently proposed by our group to provide an accurate description of simple liquids, is here extended to larger molecules, capable of exhibiting more complex fluid phases. While the standard Joyce protocol is employed to parameterize the intramolecular FF term, a new automated procedure is here proposed to handle the computational cost of the QM calculations required for the parameterization of the intermolecular FF term. The latter is thus obtained by integrating the old Picky procedure with a fragmentation reconstruction method (FRM) that allows for a reliable, yet computationally feasible sampling of the intermolecular energy surface at the QM level. The whole FF parameterization protocol is tested on a benchmark liquid crystal, and the performances of the resulting quantum mechanically derived (QMD) FF were compared with those delivered by a general-purpose, transferable one, and by the third, "hybrid" FF, where only the bonded terms were refined against QM data. Lengthy atomistic MD simulations are carried out with each FF on extended 5CB systems in both isotropic and nematic phases, eventually validating the proposed protocol by comparing the resulting macroscopic properties with other computational models and with experiments. The QMD-FF yields the best performances, reproducing both phases in the correct range of temperatures and well describing their structure, dynamics, and thermodynamic properties, thus providing a clear protocol that may be explored to predict such properties on other complex fluids or soft materials.
分子动力学（MD）模拟在预测复杂流体和软材料（如液晶、胶体悬浮液或聚合物）的宏观性质方面的可靠性，取决于所采用的力场（FF）的准确性。我们提出了一种完全基于从头算量子力学（QM）数据来推导特定且准确的力场的自动化方案。我们团队最近提出的用于准确描述简单液体的乔伊斯（Joyce）和皮基（Picky）程序的整合，在此扩展到了能够呈现更复杂流体相的更大分子。虽然采用标准的乔伊斯程序来参数化分子内力场项，但这里提出了一种新的自动化程序来处理分子间力场项参数化所需的量子力学计算的计算成本。后者是通过将旧的皮基程序与一种碎片重建方法（FRM）相结合而获得的，该方法允许在量子力学水平上对分子间能量表面进行可靠且计算上可行的采样。整个力场参数化方案在一种基准液晶上进行了测试，并将由此得到的量子力学推导（QMD）力场的性能与一种通用的、可转移的力场以及第三种“混合”力场（其中仅键合项根据量子力学数据进行了优化）的性能进行了比较。使用每个力场在各向同性和向列相的扩展5CB系统上进行了长时间的原子分子动力学模拟，最终通过将得到的宏观性质与其他计算模型以及实验结果进行比较，验证了所提出的方案。QMD力场表现出最佳性能，在正确的温度范围内重现了两个相，并很好地描述了它们的结构、动力学和热力学性质，从而提供了一个清晰的方案，可用于预测其他复杂流体或软材料的此类性质。
