Guanghua Ye

Evaluation of approximations for concentration-dependent micropore diffusion in sorbent with bidisperse pore structure

Average diffusivity linear driving force (AD-LDF) and concentration-dependent diffusivity linear driving force (CDD-LDF) approximations are introduced to simplify the precise model describing the concentration-dependent micropore diffusion in bidisperse sorbents, and are compared with the precise model in predicting the dynamics of a sorption process under two different perturbations (i.e., step change perturbations and sinusoidal wave perturbation) with different concentrations imposed at the exterior surface of the bidisperse sorbent. The performance of the two approximations is validated by the precise model and experiments. The AD-LDF performs better in step adsorption and CDD-LDF does better in step desorption. Under sinusoidal wave perturbation, the CDD-LDF performs better. The different levels of consistency of the two approximations with the precise model are attributed to the different definitions of the diffusivities.

Nature-Inspired Optimization of Transport in Porous Media

Materials combining pore sizes of different length scales are highly important for catalysis and separation processes, where optimization of adsorption and transport properties is required. Nature can be an excellent guide to rational design, as it is full of such “hierarchical” structures that are intrinsically scaling, efficient and robust. In technology, as well as in nature, the performance of the transport systems is significantly affected by their structure over different length scales, which provides abundant room to optimize transport through manipulating the multiscale structure, such as transport channel size and distribution. Following this avenue, the chapter discusses a nature-inspired (chemical) engineering (NICE) approach to optimize mass transport for catalytic systems employing porous media, with particular emphasis on the optimization of porous catalysts and proton exchange membrane (PEM) fuel cells.

Manipulating the mesostructure of silicoaluminophosphate SAPO-11 via tumbling-assisted, oriented assembly crystallization: a pathway to enhance selectivity in hydroisomerization

Controlling the architecture of crystalline materials via a non-classical crystallization pathway provides a versatile route to optimise their properties. It is shown how a designed hierarchical architecture of silicoaluminophosphate SAPO-11 can be obtained by controlling the crystallization process, and how this affects hydroisomerization of n-heptane. Oriented attachment is identified as the main crystallization pathway when pre-fabricated nanocrystallites are used as precursors. Tumbling crystallization facilitates the in-plane alignment of nanocrystallites to afford a house-of-cards architecture, consisting of ca. 300 nm nanosheets along the same crystallographic b axis, while static crystallization only affords randomly oriented agglomerates made up of fused nanocrystallites. Using a growth modifier, cellulose 2-(2-hydroxy-3-(trimethylammonium)propoxy) ethyl ether chloride (polyquaternium-10 or PQ-10), reduces the lateral size of these platelets down to ca. 20 nm, while simultaneously increasing the auxiliary porosity and surface area, as well as the mass transfer properties of the hierarchically structured material. The preparation factors that influence the morphology of the final crystalline products can be associated with changes in interparticle interactions. A suite of characterization techniques, such as XRD, N2 physisorption, Hg porosimetry, SEM, TEM, 28Al, 31P and 29Si MAS NMR, NH3-TPD and Py-IR were employed to elucidate the structure and acidity. Catalytic hydroisomerization tests for n-heptane demonstrate that the selectivity to isomerized components is governed by diffusion properties that rely on a hierarchical architecture. Hydroisomerization is the main reaction pathway only when operated within the diffusion controlled regime. Our findings thus provide more insight into how the hierarchical architecture of a catalyst influences the reaction product distribution.