Haast en spoed in detectie en gas scheidingen wel goed? Transport diffusie in metaal-organische rooster

Nanoporous materials hold significant promise in moving from energy-intensive distillation and absorption processes to more sustainable adsorption-based separations. These materials are predominantly assessed based on their equilibrium properties, yet mass transfer fundamentally governs the maximum production rates in all adsorption-based processes. Consequently, selecting adsorbents based solely on thermodynamic properties can lead to suboptimal and unforeseen outcomes. In this Ph.D. thesis, the role of mass transfer is explored, along with the limitations and challenges associated with measuring this property, from powder forms to shaped adsorbents. A diverse range of nanoporous materials has been investigated for applications in separation and purification processes, including metal-organic frameworks (MOFs). MOFs represent a rapidly expanding class of crystalline solids, composed of inorganic nodes linked by organic molecules. Their exceptional properties, e.g., high surface area, tunable pore sizes, structural flexibility, chemical versatility, make them highly versatile and valuable for various applications, including gas storage, adsorption, molecular sieving, catalysis, and sensing. Under well-defined conditions, gravimetric uptake experiments prove an efficient technique for studying the mass transfer behavior of guest molecules in nanoporous materials. This Ph.D. thesis outlines a step-by-step methodology for reliably determining the intrinsic transport diffusion in these materials. The approach addresses key factors, including sample constraints, the requirements of linear and isothermal models, the effects of heat and bed dynamics, and the influence of surface barriers. Using this methodology, the intracrystalline diffusion of various alcohols, alkanes, and ketones is systematically studied over a wide concentration range in the prototypical MOF, zeolitic imidazolate framework-8 (ZIF-8). Due to its flexible aperture, ZIF-8 is an intriguing candidate for kinetic separations. In this context, the vapor-phase modification of ZIF-8 with trimethylaluminum is investigated. The resulting material, Al-ZIF-8, exhibits robust equilibrium uptake while demonstrating altered transport properties that depend on the intensity of the modification. These characteristics make Al-ZIF-8 a particularly promising candidate for separation applications. The selective detection of volatile organic compounds (VOCs) is crucial for a wide range of applications, including breath analysis for disease diagnosis, monitoring air pollution, assessing food freshness, and detecting chemical leaks. However, the low concentrations of VOCs and the presence of many interfering compounds make it a challenging task. Current miniature sensors frequently produce unreliable data and lack the necessary selectivity. The high internal surface area and tunable properties make MOFs highly attractive for sensing applications. To date, MOF-based sensors have relied exclusively on equilibrium adsorption to achieve selectivity. This Ph.D. thesis introduces a novel sensing concept, kinetic sensing. This approach leverages the differences in mass transfer rates of guest molecules within the MOF framework to achieve selectivity. For the first time, kinetic selectivity in nanoporous crystals is applied to the field of chemical sensors, offering a new paradigm for enhancing sensor performance. Even in sensors capable of kinetically differentiating between guest molecules, a multivariate approach is essential to achieve the required selectivity for detecting specific VOCs in complex environments. This Ph.D. thesis demonstrates the potential of the kinetic sensing platform using ZIF-8 and an efficiently fabricated hybrid material, ZIF-8-90. 98% of the VOCs were correctly classified considering pure and (humid) binary mixtures in nitrogen. These findings highlight the promise of kinetic-based electronic noses in addressing complex sensing challenges and advancing the field of selective VOC detection.