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能量-结构-功能图谱:材料发现的制图学。

Energy-Structure-Function Maps: Cartography for Materials Discovery.

机构信息

Computational Systems Chemistry, School of Chemistry, University of Southampton, Southampton, SO17 1BJ, UK.

Department of Chemistry and Materials Innovation Factory, Leverhulme Centre for Functional Materials Design, 51 Oxford Street, Liverpool, L7 3NY, UK.

出版信息

Adv Mater. 2018 Sep;30(37):e1704944. doi: 10.1002/adma.201704944. Epub 2017 Dec 4.

Abstract

Some of the most successful approaches to structural design in materials chemistry have exploited strong directional bonds, whose geometric reliability lends predictability to solid-state assembly. For example, metal-organic frameworks are an important design platform in materials chemistry. By contrast, the structure of molecular crystals is defined by a balance of weaker intermolecular forces, and small changes to the molecular building blocks can lead to large changes in crystal packing. Hence, empirical rules are inherently less reliable for engineering the structures of molecular solids. Energy-structure-function (ESF) maps are a new approach for the discovery of functional organic crystals. These maps fuse crystal-structure prediction with the computation of physical properties to allow researchers to choose the most promising molecule for a given application, prior to its synthesis. ESF maps were used recently to discover a highly porous molecular crystal that has a high methane deliverable capacity and the lowest density molecular crystal reported to date (r = 0.41 g cm , SA = 3425 m g ). Progress in this field is reviewed, with emphasis on the future opportunities and challenges for a design strategy based on computed ESF maps.

摘要

一些在材料化学领域中最成功的结构设计方法都利用了强方向性键,这些键的几何可靠性使得固态组装具有可预测性。例如,金属有机骨架是材料化学中的一个重要设计平台。相比之下,分子晶体的结构是由较弱的分子间力平衡决定的,分子构建块的微小变化可能导致晶体堆积的巨大变化。因此,对于工程化分子固体的结构,经验规则本质上不太可靠。能量-结构-功能 (ESF) 图谱是发现功能有机晶体的一种新方法。这些图谱将晶体结构预测与物理性质的计算融合在一起,使研究人员能够在合成之前为给定的应用选择最有前途的分子。最近,ESF 图谱被用于发现一种具有高甲烷输送能力和迄今为止报道的最低密度分子晶体(r = 0.41 g cm ,SA = 3425 m g )的高多孔分子晶体。本文综述了这一领域的进展,重点介绍了基于计算 ESF 图谱的设计策略的未来机遇和挑战。

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