Functional materials discovery using energy-structure-function maps.
Functional materials discovery using energy-structure-function maps.
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DOI：
10.1038/nature21419
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发表时间：
2017-03-30
期刊：
影响因子：
64.8
通讯作者：
Day GM
中科院分区：
文献类型：
--
作者：
Pulido A;Chen L;Kaczorowski T;Holden D;Little MA;Chong SY;Slater BJ;McMahon DP;Bonillo B;Stackhouse CJ;Stephenson A;Kane CM;Clowes R;Hasell T;Cooper AI;Day GM
分子晶体不能像宏观物体那样被设计，因为它们不能按照简单直观的规则组装。它们的结构是许多弱相互作用平衡的结果，与金属有机框架和共价有机框架中发现的强且可预测的键合模式不同。因此，假设拓扑或其他结构蓝图的设计策略通常会失败。在这里，我们结合联合收割机计算晶体结构预测和性能预测，建立能量-结构-功能图描述可能的结构和性能的候选分子。使用这些地图，我们确定了一个高度多孔的固体分子晶体的密度最低的报告。晶体结构和物理性质，如甲烷存储容量和客体选择性，预测使用的分子图作为唯一的输入。更一般地说，能量-结构-功能图可以用来指导实验发现具有任何目标功能的材料，这些目标功能可以从预测的晶体结构计算出来，例如电子结构或机械性能。
Molecular crystals cannot be designed like macroscopic objects because they do not assemble according to simple, intuitive rules. Their structure results from the balance of many weak interactions, unlike the strong and predictable bonding patterns found in metal–organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here, we combine computational crystal structure prediction and property prediction to build energy–structure–function maps describing the possible structures and properties available to a candidate molecule. Using these maps, we identify a highly porous solid with the lowest density reported for a molecular crystal. Both crystal structure and physical properties, such as the methane storage capacity and guest selectivity, are predicted using the molecular diagram as the only input. More generally, energy–structure–function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.