(313b) Enhancing Sorption Kinetics Via Intracrystalline Diffusivity Tuning for High-Density Thermochemical Energy Storage

Thermochemical energy storage (TCES) technologies offer the potential for long-duration, lossless energy storage by reversibly storing heat through water sorption in solid materials. Achieving both high energy density and high-power density in these systems requires sorbents that not only store large amounts of water but also allow for rapid uptake and release. However, the rate of water sorption in microporous materials is often limited by slow intracrystalline mass transport, particularly under low humidity conditions where water diffusivity becomes strongly dependent on local concentration.

In this work, we investigate the water concentration-dependent intracrystalline diffusivity in two benchmark materials: MOF-303 and AQSOA Z02, a commercial zeolite. We employ a combination of infrared (IR) microscopy and interference microscopy to visualize and quantify the spatial and temporal evolution of water content within individual crystals. These imaging techniques provide direct insight into the movement of sorption fronts and reveal marked differences in water uptake dynamics between the two materials. Specifically, we observe sharp sorption fronts in MOF-303 and more diffuse, gradient-driven uptake in AQSOA Z02, indicating fundamentally different transport regimes.

To interpret these observations, we develop an analytical diffusion model that incorporates the material-specific water isotherm shape, capturing the strong dependence of diffusivity on local water concentration. The model predicts the evolution of spatial concentration profiles over time and is validated against the experimental imaging data. Our results highlight the importance of isotherm shape in governing transport behavior and demonstrate how tailoring the intracrystalline diffusivity through material design or modification can enhance both the energy and power density of TCES systems. This work establishes a robust experimental-modeling framework for characterizing and optimizing sorbents and provides key insights into the coupled roles of thermodynamics and transport in heat-driven energy storage.