Molecular dynamics (MD) and transition state theory (TST) methods are becoming efficient tools for predicting diffusion of molecules in nanoporous materials. The accuracy of predictions, however, often depends upon a major assumption that the framework of the material is rigid. This saves a considerable amount of computational time and is often the only method applicable to materials for which accurate force fields to model framework flexibility are not available. In this study, we systematically characterize the effect of framework flexibility on diffusion in four model zeolites (LTA, CHA, ERI, and BIK) that exhibit different patterns of window flexibility. We show that for molecules with kinetic diameters comparable to (or larger than) the size of the window the rigid framework approximation can produce order(s) of magnitude difference in diffusivities as compared to the simulations performed with a fully flexible framework. We also show that simple recipes to include the effect of framework flexibility are not generally accurate. To account for framework flexibility effects efficiently and reliably, we introduce two new methods in which the flexible structure is approximated as a set of discrete rigid snapshots obtained from simulations of dynamics of an empty framework, using either classical or, in principle, ab initio methods. In the first method, we perform MD simulations of diffusion in a usual manner but replace the rigid structure with a new random snapshot at a certain characteristic frequency corresponding to the breathing motion of the window, while keeping positions of adsorbate molecules constant. In the second method, we directly compute cage to cage hopping rates in each rigid snapshot using TST and average over a distribution of snapshots. Excellent agreement is obtained between diffusivities predicted with these two new methods and direct MD simulations using fully flexible structures. Both methods are orders of magnitude more efficient than the simulations with the fully flexible structure. The new methods are broadly applicable for fast and accurate predictions of both infinite dilution and finite loading diffusivities of simple molecules in zeolites and other nanoporous materials, generally without the need for an accurate flexible force field.

Solid porous materials such as cationic zeolites have shown great potential in energy-efficient separation processes. Conventional adsorbent design involves ad-hoc and inefficient experimental evaluation of a large structural and compositional space. We developed a computational methodology to screen cationic zeolites for CO2 separation processes with quantitative accuracy, and identified a number of novel high-performing materials. This study enabled us to develop an intuitive design workflow for selecting optimal materials and dramatically accelerate the development of industrially relevant separation processes.

Most previous studies on development of force fields for molecules in porous materials focus on prediction of adsorption properties. However, accurately reproducing adsorption data is not sufficient to guarantee the accuracy of other properties, such as diffusivities. We demonstrate an approach to develop force fields based on periodic first-principles calculations that can accurately predict both adsorption and diffusion properties in crystalline nanoporous materials using CH4 in siliceous zeolites as an example. First, multiple dispersion-corrected density functional theory (DFT) methods were tested for describing CH4 in siliceous chabazite, and the two configurations (CH4 interacting with a framework all and an eight-ring window) that are relevant to CH4 adsorption and diffusion were investigated. By comparing with the results from high-level random phase approximation calculations, DFT/CC (coupled cluster) was found to be the optimum method for force field development. DFT/CC-derived force fields that accurately predict both adsorption and diffusion of CH4 in several commonly studied siliceous zeolites are then developed.

While it has long been known that some highly adsorbing microporous materials suddenly become inaccessible to guest molecules below certain temperatures, previous attempts to explain this phenomenon have failed. Here we show that this anomalous sorption behaviour is a temperature-regulated guest admission process, where the pore-keeping group's thermal fluctuations are influenced by interactions with guest molecules. A physical model is presented to explain the atomic-level chemistry and structure of these thermally regulated micropores, which is crucial to systematic engineering of new functional materials such as tunable molecular sieves, gated membranes and controlled-release nanocontainers. The model was validated experimentally with H2, N2, Ar and CH4 on three classes of microporous materials: trapdoor zeolites, supramolecular host calixarenes and metal-organic frameworks. We demonstrate how temperature can be exploited to achieve appreciable hydrogen and methane storage in such materials without sustained pressure. These findings also open new avenues for gas sensing and isotope separation.

We use two methods, the changing snapshot method and transition state theory (TST)/snapshot method, to characterize the effects of zeolite framework flexibility on diffusion of spherical molecules in 8MR zeolites. These methods are applied to noble gases (Ne, Ar, Kr, Xe, and Rn) and CF 4 . We demonstrate the effect of the zeolite framework flexibility on diffusion by considering the size and loading of adsorbates and temperature. In both the methods, we approximate flexible structures as a set of discrete rigid snapshots obtained from molecular dynamics simulations of an empty framework. We show that the diffusivities predicted with these two efficient methods agree with direct MD simulations in the fully flexible structures. We studied in detail how the framework flexibility affects the loading dependence of diffusion. By looking at the computational costs, we demonstrated that both the methods are orders of magnitude more efficient than the fully flexible simulations. We then apply the changing snapshot method to binary mixtures of adsorbates to obtain accurate binary diffusivities and binary selectivities.