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Computer-aided discovery of a metal-organic framework with superior oxygen uptake.


ABSTRACT: Current advances in materials science have resulted in the rapid emergence of thousands of functional adsorbent materials in recent years. This clearly creates multiple opportunities for their potential application, but it also creates the following challenge: how does one identify the most promising structures, among the thousands of possibilities, for a particular application? Here, we present a case of computer-aided material discovery, in which we complete the full cycle from computational screening of metal-organic framework materials for oxygen storage, to identification, synthesis and measurement of oxygen adsorption in the top-ranked structure. We introduce an interactive visualization concept to analyze over 1000 unique structure-property plots in five dimensions and delimit the relationships between structural properties and oxygen adsorption performance at different pressures for 2932 already-synthesized structures. We also report a world-record holding material for oxygen storage, UMCM-152, which delivers 22.5% more oxygen than the best known material to date, to the best of our knowledge.

SUBMITTER: Moghadam PZ 

PROVIDER: S-EPMC5895810 | biostudies-other | 2018 Apr

REPOSITORIES: biostudies-other

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Computer-aided discovery of a metal-organic framework with superior oxygen uptake.

Moghadam Peyman Z PZ   Islamoglu Timur T   Goswami Subhadip S   Exley Jason J   Fantham Marcus M   Kaminski Clemens F CF   Snurr Randall Q RQ   Farha Omar K OK   Fairen-Jimenez David D  

Nature communications 20180411 1


Current advances in materials science have resulted in the rapid emergence of thousands of functional adsorbent materials in recent years. This clearly creates multiple opportunities for their potential application, but it also creates the following challenge: how does one identify the most promising structures, among the thousands of possibilities, for a particular application? Here, we present a case of computer-aided material discovery, in which we complete the full cycle from computational s  ...[more]

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