Modular and predictable assembly of porous organic molecular crystals
Modular and predictable assembly of porous organic molecular crystals
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DOI：
10.1038/nature10125
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发表时间：
2011-06-16
期刊：
影响因子：
64.8
通讯作者：
Cooper, Andrew I.
中科院分区：
文献类型：
--
作者：
Jones, James T. A.;Hasell, Tom;Cooper, Andrew I.
纳米多孔分子框架（1-7）在诸如分离、储存和催化的应用中是重要的。经验规则存在的组装，但它仍然是具有挑战性的放置和隔离功能在三维多孔固体中以可预测的方式。事实上，最近对混合晶体框架的研究表明，优先考虑官能团在整个孔中的统计分布（7），而不是例如在酶的反应位点中发现的官能团定位（8）。这是从简单起始材料“一锅法”化学合成多孔框架的潜在限制。另一种策略是从合成预组织的分子孔制备多孔固体（9-15）。原则上，功能性有机孔模块可以共价预制，然后组装以产生具有特定性质的材料。然而，这种混搭组装的愿景还远未实现，尤其是因为在可靠地预测分子晶体的三维结构方面存在挑战，因为分子晶体缺乏网络中发现的强定向键合。在这里，我们表明，高度多孔的结晶固体可以通过混合不同的有机笼模块，自组装通过手性识别。所得材料的结构可以通过计算预测（16，17），从而允许计算机材料设计策略（18）。在一步反应中以高收率在克级上合成组成孔模块。多孔共晶的组装与在溶液中组合模块并去除溶剂一样简单。在某些情况下，可以利用模块之间的手性识别来产生多孔有机纳米颗粒。我们表明，该方法是有效的四个不同的笼模块，并在原则上可以推广的计算可预测的方式的基础上，模块之间的锁和钥匙组装。
Nanoporous molecular frameworks(1-7) are important in applications such as separation, storage and catalysis. Empirical rules exist for their assembly but it is still challenging to place and segregate functionality in three-dimensional porous solids in a predictable way. Indeed, recent studies of mixed crystalline frameworks suggest a preference for the statistical distribution of functionalities throughout the pores(7) rather than, for example, the functional group localization found in the reactive sites of enzymes(8). This is a potential limitation for 'one-pot' chemical syntheses of porous frameworks from simple starting materials. An alternative strategy is to prepare porous solids from synthetically preorganized molecular pores(9-15). In principle, functional organic pore modules could be covalently prefabricated and then assembled to produce materials with specific properties. However, this vision of mix-and-match assembly is far from being realized, not least because of the challenge in reliably predicting three-dimensional structures for molecular crystals, which lack the strong directional bonding found in networks. Here we show that highly porous crystalline solids can be produced by mixing different organic cage modules that self-assemble by means of chiral recognition. The structures of the resulting materials can be predicted computationally(16,17), allowing in silico materials design strategies(18). The constituent pore modules are synthesized in high yields on gram scales in a one-step reaction. Assembly of the porous co-crystals is as simple as combining the modules in solution and removing the solvent. In some cases, the chiral recognition between modules can be exploited to produce porous organic nanoparticles. We show that the method is valid for four different cage modules and can in principle be generalized in a computationally predictable manner based on a lock-and-key assembly between modules.