In Silico Discovery of High Deliverable Capacity Metal Organic Frameworks
In Silico Discovery of High Deliverable Capacity Metal Organic Frameworks
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DOI：
10.1021/jp5123486
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发表时间：
2015-01-08
影响因子：
3.7
通讯作者：
Deem, Michael W.
中科院分区：
文献类型：
--
作者：
Bao, Yi;Martin, Richard L.;Deem, Michael W.
金属有机框架（MOFs）正在积极探索作为小型车辆的潜在吸附天然气储存材料。对潜在材料的实验探索受到合成化学通量的限制。我们在这里描述了一种计算方法来补充和指导这些实验工作。该方法使用已知的计算机化学转化来鉴定具有高甲烷输送能力的M0 F。该程序明确考虑了有机连接体的几何要求的合成性。我们有效地搜索了9个MOF网络的有机连接体的组成和构象空间，在9个网络中的4个中找到了48种具有比MOF-5更高的预测可传递能力（在65 bar存储，5.8 bar耗尽和298 K下）的材料。最好的材料具有比MOF-5高8%的预测可交付能力。
Metal-organic frameworks (MOFs) are actively being explored as potential adsorbed natural gas storage materials for small vehicles. Experimental exploration of potential materials is limited by the throughput of synthetic chemistry. We here describe a computational methodology to complement and guide these experimental efforts. The method uses known chemical transformations in silico to identify MOFs with high methane deliverable capacity. The procedure explicitly considers synthesizability with geometric requirements on organic linkers. We efficiently search the composition and conformation space of organic linkers for 9 MOF networks, finding 48 materials with higher predicted deliverable capacity (at 65 bar storage, 5.8 bar depletion, and 298 K) than MOF-5 in 4 of the 9 networks. The best material has a predicted deliverable capacity 8% higher than that of MOF-5.