Enhanced replica exchange reactive Monte Carlo simulations for constructing zeolite frameworks

The use of collective variables and enhanced sampling in the simulations of existing and emerging microporous materials

Microporous materials, including zeolites, metal-organic frameworks, and cage compounds, offer diverse functionalities due to their unique dynamics and guest confinement properties. These materials play a significant role in separation, catalysis, and sensing, but their complexity hinders exploration using traditional atomistic simulations. This review explores collective variables (CVs) paired with enhanced sampling as a powerful approach to enable efficient investigation of key features in microporous materials. We highlight successful applications of CVs in studying adsorption, diffusion, phase transitions, and mechanical properties, demonstrating their crucial role in guiding material design and optimisation. The future of CVs lies in integration with techniques like machine learning, allowing for enhanced efficiency and accuracy. By tailoring CVs to specific materials and developing multi-scale approaches we can further unlock the intricacies of these fascinating materials. Simulations are a cornerstone in unravelling the complexities of microporous materials and are crucial for our future understanding.

Monte carlo simulations and experiments of all-silica zeolite LTA assembly combining structure directing agents that match cage sizes

We investigated the influence of organic structure-directing agents (OSDAs) on the formation rates of all-silica zeolite LTA using both simulations and experiments, to shed light on the crystallization process. We compared syntheses using one OSDA with a diameter close to the size of the large cavity in LTA, and two OSDAs of diameters matching the sizes of both the small and large LTA cavities. Reaction-ensemble Monte Carlo (RxMC) simulations predict a speed up of LTA formation using two OSDAs matching the LTA pore sizes; this qualitative result is confirmed by experimental studies of crystallization kinetics, which find a speedup in all-silica LTA crystallization of a factor of 3. Analyses of simulated rings and their Si-O-Si angular energies during RxMC crystallizations show that all ring sizes in the faster crystallization exhibit lower angular energies, on average, than in the slower crystallization, explaining the origin of the speedup through packing effects.

Modeling the Role of Excluded Volume in Zeolite Structure Direction

We investigate the formation of zeolite structures in replica-exchange Monte Carlo simulations of a reactive model of silica polymerization. The simulations incorporate hard spheres to model the effect of excluded volume caused by structure-directing agents (SDAs). We focus on modeling the formation of cage-type zeolite frameworks SOD and LTA. Our model predicts that a relatively wide range of SDA sizes could be used to construct SOD, whereas a narrower range will work for constructing LTA. We also predict that there is potential benefit of including multiple SDAs in each zeolite unit cell, and in the case of LTA with both small and large cavities, there is a strong potential benefit using both small and large SDAs that match the cavities' sizes. We hypothesize that the volume exclusion reduces the configuration space available to the assembling silica units, making it easier for the system to find ordered structures with quasi-spherical cavities.