Rational design of patchy colloids via landscape engineering,Molecular Systems Design & Engineering

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Rational design of patchy colloids via landscape engineering
Molecular Systems Design & Engineering ( IF 3.2 ) Pub Date : 2017-10-17 00:00:00 , DOI: 10.1039/c7me00077d
Andrew W. Long _{1,

2,

3,

4} , Andrew L. Ferguson _{1,

2,

3,

4,

5}

Affiliation

We present a new data-driven inverse design platform for self-assembling materials that we term “landscape engineering”. The essence of the approach is to sculpt the self-assembly free energy landscape to favor the formation of target aggregates by rational manipulation of building block properties. The approach integrates nonlinear manifold learning with hybrid Monte Carlo techniques to efficiently recover self-assembly landscapes, which we subsequently optimize using the covariance matrix adaptation evolutionary strategy (CMA-ES). We demonstrate the effectiveness of this technique in the design of anisotropic patchy colloids to form hollow polyhedral capsids. In the case of icosahedral capsids, our approach discovers a building block possessing a 76% improvement in the assembly rate over an initial expert-designed building block. In the case of octahedral clusters, our platform produces a building block with a 60% yield despite being challenged with a poor initial building block design incapable of forming stable octahedra.

中文翻译：

通过景观工程合理设计斑片状胶体

我们为自组装材料提供了一个新的数据驱动的逆向设计平台，我们称之为“景观工程”。该方法的本质是雕刻自组装自由能景观，以通过对积木属性的合理操纵来促进目标聚集体的形成。该方法将非线性流形学习与混合蒙特卡洛技术相结合，以有效地恢复自组装景观，随后我们使用协方差矩阵适应进化策略（CMA-ES）对其进行优化。我们证明了该技术在各向异性斑片状胶体形成空心多面体衣壳的设计中的有效性。对于二十面体衣壳，我们的方法发现，与最初的专家设计的构件相比，该构件的装配率提高了76％。

更新日期：2017-10-21

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