McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, USA.
J Chem Phys. 2019 Sep 14;151(10):104104. doi: 10.1063/1.5112766.
Isotropic pairwise interactions that promote the self-assembly of complex particle morphologies have been discovered by inverse design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of self-assembly of a given target structure and providing multiple assembly routes for its realization. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.
通过源自分子粗粒化文献的反设计策略，发现了促进复杂颗粒形态自组装的各向同性成对相互作用。虽然这些方法为重现结构相关性提供了途径，但在自组装应用中，通常不考虑压力等热力学量。在这项工作中，我们证明了相对熵优化可用于发现当在等温等压系综中进行迭代模拟时，能够自组装成具有规定压力的目标团簇形态的势。这种方法有两个优点。首先，可以同时控制优化相互作用的结构和热力学。其次，通过在优化中改变压力，可以系统地发现一系列能够自组装相同结构的粒子间势，从而更深入地了解给定目标结构的自组装，并为其实现提供多种组装途径。选择适当的模拟系综来控制感兴趣的热力学性质是一种通用的设计策略，也可用于发现能够自组装具有特定化学势的结构的相互作用势。
