Post-doc, University of Cambridge
Computer simulations discover a new world-record material for oxygen storage
Current advances in materials science have resulted in the rapid emergence of thousands of functional 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? Due to practical constraints, experimental trial-and-error discovery is simply not fast enough, and therefore more efficient alternatives must be developed to accelarate the discovery and deployment of new adsorbent materials. This work presents a rare case of computer-aided material discovery, in which we complete the full cycle from computational screening of porous materials for oxygen storage (application in the development of oxygen tanks for patients with respiratory problems), to identification, synthesis and measurement of oxygen adsorption in the top-ranked structure. We introduce an interactive visualisation concept to analyse over a 1000 unique structure-property plots in 4 dimensions and delimit – for the first time – the relationships between structural properties and oxygen adsorption performance at different pressures for 2,932 already-synthesised porous materials. We also report a new world-record holding material for oxygen storage, UMCM-152, which delivers 22.5% more oxygen than the best known material to date. All of the graphs presented in this work can be reproduced online at http://aam.ceb.cam.ac.uk/mof-explorer.
Abstract: Metal–organic frameworks (MOFs) can exhibit exceptionally high surface areas, which are experimentally estimated by applying the BET theory to measured nitrogen isotherms. The Brunauer, Emmett, and Teller (BET)-estimated nitrogen monolayer loading is thus converted to a “BET area,” but the meaning of MOF BET areas remains under debate. Recent emphasis has been placed on the usage of four so-called “BET consistency criteria.” Using these criteria and simulated nitrogen isotherms for perfect crystals, we calculated BET areas for graphene and 25 MOFs having different pore-size distributions. BET areas were compared with their corresponding geometrically calculated, nitrogen-accessible surface areas (NASAs). Analysis of simulation snapshots elucidated the contributions of “pore-filling” and “monolayer-formation” to the nitrogen adsorption loadings in different MOF pores, revealing the origin of inaccuracies in BET-calculated monolayer loadings, which largely explain discrepancies between BET areas and NASAs. We also find that even if all consistency criteria are satisfied, the BET calculation can significantly overestimate the true monolayer loading, especially in MOFs combining mesopores (d ≥ 20 Å) and large micropores (d = 10–20 Å), due to the overlap of pore-filling and monolayer-formation regimes of these two kinds of pores. While it is not always possible to satisfy all consistency criteria, it is critical to minimize the deviation from these criteria during BET range selection to consistently compare BET areas of different MOFs and for comparing simulated and experimental BET areas of a given MOF. To accurately assess the quality of a MOF sample, it is best to compare experimental BET areas with simulated BET areas rather than with calculated NASAs.
Pub.: 11 Dec '15, Pinned: 29 Jun '17
Abstract: Metal-organic frameworks (MOFs) are known to facilitate energy-efficient separations of important industrial chemical feedstocks. Here, we report how a class of green MOFs-namely CD-MOFs-exhibits high shape selectivity toward aromatic hydrocarbons. CD-MOFs, which consist of an extended porous network of γ-cyclodextrins (γ-CDs) and alkali metal cations, can separate a wide range of benzenoid compounds as a result of their relative orientation and packing within the transverse channels formed from linking (γ-CD)6 body-centered cuboids in three dimensions. Adsorption isotherms and liquid-phase chromatographic measurements indicate a retention order of ortho- > meta- > para-xylene. The persistence of this regioselectivity is also observed during the liquid-phase chromatography of the ethyltoluene and cymene regioisomers. In addition, molecular shape-sorting within CD-MOFs facilitates the separation of the industrially relevant BTEX (benzene, toluene, ethylbenzene, and xylene isomers) mixture. The high resolution and large separation factors exhibited by CD-MOFs for benzene and these alkylaromatics provide an efficient, reliable, and green alternative to current isolation protocols. Furthermore, the isolation of the regioisomers of (i) ethyltoluene and (ii) cymene, together with the purification of (iii) cumene from its major impurities (benzene, n-propylbenzene, and diisopropylbenzene) highlight the specificity of the shape selectivity exhibited by CD-MOFs. Grand canonical Monte Carlo simulations and single component static vapor adsorption isotherms and kinetics reveal the origin of the shape selectivity and provide insight into the capability of CD-MOFs to serve as versatile separation platforms derived from renewable sources.
Pub.: 26 Mar '15, Pinned: 29 Jun '17
Abstract: An isoreticular series of metal-organic frameworks (MOFs) with the ftw topology based on zirconium oxoclusters and tetracarboxylate linkers with a planar core (NU-1101 through NU-1104) has been synthesized employing a linker expansion approach. In this series, NU-1103 has a pore volume of 2.91 cc g(-1) and a geometrically calculated surface area of 5646 m(2) g(-1), which is the highest value reported to date for a zirconium-based MOF and among the largest that have been reported for any porous material. Successful activation of the MOFs was proven based on the agreement of pore volumes and BET areas obtained from simulated and experimental isotherms. Critical for practical applications, NU-1103 combines for the first time ultrahigh surface area and water stability, where this material retained complete structural integrity after soaking in water. Pressure range selection for the BET calculations on these materials was guided by the four so-called "consistency criteria". The experimental BET area of NU-1103 was 6550 m(2) g(-1). Insights obtained from molecular simulation suggest that, as a consequence of pore-filling contamination, the BET method overestimates the monolayer loading of NU-1103 by ∼16%.
Pub.: 28 Feb '15, Pinned: 29 Jun '17
Abstract: We report the generation and characterization of the most complete collection of metal–organic frameworks (MOFs) maintained and updated, for the first time, by the Cambridge Crystallographic Data Centre (CCDC). To set up this subset, we asked the question “what is a MOF?” and implemented a number of “look-for-MOF” criteria embedded within a bespoke Cambridge Structural Database (CSD) Python API workflow to identify and extract information on 69 666 MOF materials. The CSD MOF subset is updated regularly with subsequent MOF additions to the CSD, bringing a unique record for all researchers working in the area of porous materials around the world, whether to perform high-throughput computational screening for materials discovery or to have a global view over the existing structures in a single resource. Using this resource, we then developed and used an array of computational tools to remove residual solvent molecules from the framework pores of all the MOFs identified and went on to analyze geometrical and physical properties of nondisordered structures.
Pub.: 14 Mar '17, Pinned: 29 Jun '17
Abstract: Metal-organic frameworks (MOFs) are porous materials constructed from modular molecular building blocks, typically metal clusters and organic linkers. These can, in principle, be assembled to form an almost unlimited number of MOFs, yet materials reported to date represent only a tiny fraction of the possible combinations. Here, we demonstrate a computational approach to generate all conceivable MOFs from a given chemical library of building blocks (based on the structures of known MOFs) and rapidly screen them to find the best candidates for a specific application. From a library of 102 building blocks we generated 137,953 hypothetical MOFs and for each one calculated the pore-size distribution, surface area and methane-storage capacity. We identified over 300 MOFs with a predicted methane-storage capacity better than that of any known material, and this approach also revealed structure-property relationships. Methyl-functionalized MOFs were frequently top performers, so we selected one such promising MOF and experimentally confirmed its predicted capacity.
Pub.: 25 Jan '12, Pinned: 29 Jun '17