Porous Organic Crystals: From Prediction to Synthesis and Function

分子晶体结构的从头预测是一个尚未解决的挑战，在制药、生物学和合成功能材料等领域具有中心和根本的重要性。基于我们最近的合作（Nature, 2011, 474, 367），我们将开发晶体结构预测方法，以支持新功能有机材料的发现。我们的重点是“多孔有机笼”，这是英国在国际上领先的多孔材料的一个子类，以及它们在选择性分子分离和离子电导率方面的应用。该方案涉及计算、综合和具体财产测量领域的领导小组的密切结合。因此，更广泛的成果将是开发一种集成的“预测到性能”方法，这将对许多类别的材料产生广泛的影响，正如EPSRC大挑战“具有目标性能的扩展结构的定向组装”所概述的那样。

The de novo prediction of molecular crystal structures is an unmet challenge that has central and fundamental importance in areas such as pharmaceuticals, biology, and synthetic functional materials. Building on our recent collaboration (Nature, 2011, 474, 367), we will develop crystal structure prediction methods to underpin the discovery of new functional organic materials. Our focus is 'porous organic cages', a sub-class of porous materials in which the UK has an international lead, and their use in selective molecular separations and in ionic conductivity. The programme involves the close integration of leading groups in the areas of computation, synthesis, and specific property measurements. Hence, a wider outcome will be the development of an integrated 'prediction-to-properties' approach that will have broad impact across many classes of materials, as outlined in the EPSRC Grand Challenge, "Directed Assembly of Extended Structures with Targeted Properties".