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While multiple external stimuli (e.g., temperature, light, pressure) have been reported to regulate gas adsorption, limited studies have been conducted on controlling molecular admission in nanopores through the application of electric fields (E-field). Here we show gas adsorption capacity and selectivity in zeolite molecular sieves can be regulated by an external E-field. Through E-field pre-activation during degassing, several zeolites exhibited enhanced CO2 adsorption and decreased CH4 and N2 adsorptions, improving the CO2/CH4 and CO2/N2 separation selectivity by at least 25%. The enhanced separation performance of the zeolites pre-activated by E-field was maintained in multiple adsorption/desorption cycles. Powder X-ray diffraction analysis and ab initio computational studies revealed that the cation relocation and framework expansion induced by the E-field accounted for the changes in gas adsorption capacities. These findings demonstrate a regulation approach to sharpen the molecular sieving capability by E-fields and open new avenues for carbon capture and molecular separations. The gas adsorption capacity and selectivity in zeolite molecular sieves can be regulated by an external electric field through the electric field-induced cation relocation and framework expansion. [ABSTRACT FROM AUTHOR]

Adsorption hysteresis is a phenomenon related to phase transitions that can impact applications such as gas storage and separations in porous materials. Computational approaches can greatly facilitate the understanding of phase transitions and phase equilibria in porous materials. In this work, adsorption isotherms for methane, ethane, propane, and n-hexane were calculated from atomistic grand canonical Monte Carlo (GCMC) simulations in a metal-organic framework having both micropores and mesopores to better understand hysteresis and phase equilibria between connected pores of different size and the external bulk fluid. At low temperatures, the calculated isotherms exhibit sharp steps accompanied by hysteresis. As a complementary simulation method, canonical (NVT) ensemble simulations with Widom test particle insertions are demonstrated to provide additional information about these systems. The NVT+Widom simulations provide the full van der Waals loop associated with the sharp steps and hysteresis, including the locations of the spinodal points and points within the metastable and unstable regions that are inaccessible to GCMC simulations. The simulations provide molecular-level insight into pore filling and equilibria between high- and low-density states within individual pores. The effect of framework flexibility on adsorption hysteresis is also investigated for methane in IRMOF-1. Developing computational tools to study the phase behaviour of adsorbate molecules in complex pore architectures can greatly facilitate our understanding of phase transitions and phase equilibria in porous materials. Here, molecular simulations are used to study the hysteresis and phase equilibria of n-alkane adsorbate molecules in a metal–organic framework with both micropores and mesopores, and simulations in the canonical ensemble with Widom insertions are shown to be a powerful complementary approach to grand canonical Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for electronic, optoelectronic, and energy storage applications, we present a dataset of predicted electronic structure properties for thousands of MOFs carried out using multiple density functional approximations. Compared to more accurate hybrid functionals, we find that the widely used PBE generalized gradient approximation (GGA) functional severely underpredicts MOF band gaps in a largely systematic manner for semi-conductors and insulators without magnetic character. However, an even larger and less predictable disparity in the band gap prediction is present for MOFs with open-shell 3d transition metal cations. With regards to partial atomic charges, we find that different density functional approximations predict similar charges overall, although hybrid functionals tend to shift electron density away from the metal centers and onto the ligand environments compared to the GGA point of reference. Much more significant differences in partial atomic charges are observed when comparing different charge partitioning schemes. We conclude by using the dataset of computed MOF properties to train machine-learning models that can rapidly predict MOF band gaps for all four density functional approximations considered in this work, paving the way for future high-throughput screening studies. To encourage exploration and reuse of the theoretical calculations presented in this work, the curated data is made publicly available via an interactive and user-friendly web application on the Materials Project. [ABSTRACT FROM AUTHOR]

Nanoporous solids are ubiquitous in chemical, energy, and environmental processes, where controlled transport of molecules through the pores plays a crucial role. They are used as sorbents, chromatographic or membrane materials for separations, and as catalysts and catalyst supports. Defined as materials where confinement effects lead to substantial deviations from bulk diffusion, nanoporous materials include crystalline microporous zeotypes and metal–organic frameworks (MOFs), and a number of semi-crystalline and amorphous mesoporous solids, as well as hierarchically structured materials, containing both nanopores and wider meso- or macropores to facilitate transport over macroscopic distances. The ranges of pore sizes, shapes, and topologies spanned by these materials represent a considerable challenge for predicting molecular diffusivities, but fundamental understanding also provides an opportunity to guide the design of new nanoporous materials to increase the performance of transport limited processes. Remarkable progress in synthesis increasingly allows these designs to be put into practice. Molecular simulation techniques have been used in conjunction with experimental measurements to examine in detail the fundamental diffusion processes within nanoporous solids, to provide insight into the free energy landscape navigated by adsorbates, and to better understand nano-confinement effects. Pore network models, discrete particle models and synthesis-mimicking atomistic models allow to tackle diffusion in mesoporous and hierarchically structured porous materials, where multiscale approaches benefit from ever cheaper parallel computing and higher resolution imaging. Here, we discuss synergistic combinations of simulation and experiment to showcase theoretical progress and computational techniques that have been successful in predicting guest diffusion and providing insights. We also outline where new fundamental developments and experimental techniques are needed to enable more accurate predictions for complex systems. [ABSTRACT FROM AUTHOR]

Molecules of heavy water contain the deuterium isotope of hydrogen and have been impossible to separate from ordinary water. Nanoporous materials with flexible apertures in their structures point the way to a solution.A material that preferentially adsorbs one isotopic analogue of water. [ABSTRACT FROM AUTHOR]