Reductive electrosynthesis of crystalline metal-organic frameworks

Electroreduction of oxoanions affords hydroxide equivalents that induce selective deposition of crystalline metal–organic frameworks (MOFs) on conductive surfaces. The method is illustrated by cathodic electrodeposition of Zn[subscript 4]O(BDC)[subscript 3] (MOF-5; BDC = 1,4-benzenedicarboxylate), which is deposited at room temperature in only 15 min under cathodic potential. Although many crystalline phases are known in the Zn[superscript 2+]/BDCsuperscript 2–] system, MOF-5 is the only observed crystalline MOF phase under these conditions. This fast and mild method of synthesizing MOFs is amenable to direct surface functionalization and could impact applications requiring conformal coatings of microporous MOFs, such as gas separation membranes and electrochemical sensors.Massachusetts Institute of Technology. Energy Initiative (Seed Fund Program)National Science Foundation (U.S.) (Grant CHE-9808061)National Science Foundation (U.S.) (Grant DBI-9729592)National Science Foundation (U.S.) (Grant DMR- 0819762

Diffusion and separation of CO2 and CH4 in Silicalite, C168 schwarzite, and IRMOF-1: A comparative study from molecular dynamics simulation

10.1021/la703434sLangmuir24105474-5484LANG

Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneity

Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using Only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions