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首页> 外文期刊>The Journal of Chemical Physics >Communication: Inverse design for self-assembly via on-the-fly optimization
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Communication: Inverse design for self-assembly via on-the-fly optimization

机译：通信：通过在线优化进行自组装的逆设计

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摘要

Inverse methods of statistical mechanics have facilitated the discovery of pair potentials that stabilize a wide variety of targeted lattices at zero temperature. However, such methods are complicated by the need to compare, within the optimization framework, the energy of the desired lattice to all possibly relevant competing structures, which are not generally known in advance. Furthermore, ground-state stability does not guarantee that the target will readily assemble from the fluid upon cooling from higher temperature. Here, we introduce a molecular dynamics simulation-based, optimization design strategy that iteratively and systematically refines the pair interaction according to the fluid and crystalline structural ensembles encountered during the assembly process. We successfully apply this probabilistic, machine-learning approach to the design of repulsive, isotropic pair potentials that assemble into honeycomb, kagome, square, rectangular, truncated square, and truncated hexagonal lattices. Published by AIP Publishing.
机译：统计力学的逆方法促进了对零温度稳定各种靶标晶格的对电位的发现。然而，这种方法对于在优化框架内比较，所需格子的能量与所有可能相关的竞争结构的能量相比复杂，这通常是预先已知的。此外，地状态稳定性不保证在从较高温度冷却时靶将容易地从流体组装。在这里，我们介绍了一种基于分子动力学的仿真，优化设计策略，其迭代地和系统地改进了在组装过程中遇到的流体和晶体结构集合的对相互作用。我们成功地应用了这种概率，机器学习方法来设计了令人厌恶的各向同性对势的设计，这些方法组装成蜂窝，kagome，正方形，矩形，截短的方形和截短的六边形格子。通过AIP发布发布。

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