Department of Mechanical Engineering, Keio University, Yokohama 223-8522, Japan.
J Chem Inf Model. 2024 Jun 24;64(12):4673-4686. doi: 10.1021/acs.jcim.4c00078. Epub 2024 Mar 25.
The phenomenon of hysteresis in simulations, in which a system's current state is correlated to previous states and inhibits the transition to a more stable phase, may often lead to misleading results in physical chemistry. In this study, in addition to the replica exchange method (REM), a novel approach was taken by combining an evolution strategy based on the evolutionary principles of nature to predict phase transitions for the Hess-Su liquid-crystal model. In this model, an anisotropy term is added to the simple 6-12 Lennard-Jones model to intuitively reproduce the behavior of liquid crystals. We first applied the pressure-temperature REM to the Hess-Su model and optimized the replica spacing for the energy distribution to gain the maximum advantage from the REM. We then used the same approach as for the Hamiltonian REM, seeking to optimize the replica spacing in the same way. Based on both results, we attempted to predict this coarse-grained liquid-crystal model's exact phase transition point. In the Hamiltonian REM, replicas were prepared with different molecular aspect ratios corresponding to the values of the anisotropy terms in the potential function. The Hess-Su liquid-crystal model, which undergoes a direct transition from the nematic to the solid phase without going through a smectic phase, is a challenging research target for understanding phase transitions. Despite the tremendous computational difficulty in overcoming the strong hysteresis present in this system, our method could predict the phase transition point clearly and significantly reduce the extent of hysteresis. Our approach is beneficial when simulating more complex systems and, above all, shows great potential for more accurate and efficient phase transition predictions in the field of molecular simulation in the future.
模拟中的滞后现象是指系统的当前状态与先前状态相关联,并抑制向更稳定相的转变,这种现象在物理化学中常常导致误导性的结果。在这项研究中,除了 replica exchange 方法(REM)之外,还采用了一种新的方法,即将基于自然进化原理的进化策略与 Hess-Su 液晶模型的相转变预测相结合。在该模型中,向简单的 6-12 Lennard-Jones 模型中添加各向异性项,以直观地再现液晶的行为。我们首先将压力-温度 REM 应用于 Hess-Su 模型,并优化 replica 间距以最大程度地利用 REM 的优势。然后,我们采用与 Hamiltonian REM 相同的方法,寻求以相同的方式优化 replica 间距。基于这两个结果,我们试图预测这个粗粒化液晶模型的确切相转变点。在 Hamiltonian REM 中,通过制备具有不同分子纵横比的副本来对应于势能函数中各向异性项的值。Hess-Su 液晶模型从向列相到固体相的直接转变,而不经过近晶相,是理解相转变的一个具有挑战性的研究目标。尽管克服系统中存在的强烈滞后性存在巨大的计算困难,但我们的方法可以清楚地预测相转变点,并显著减少滞后性的程度。当模拟更复杂的系统时,我们的方法是有益的,尤其是在未来的分子模拟领域,它显示出了更准确和高效的相转变预测的巨大潜力。