Heterogeneous catalyst engineering ⇒ from stable and deactivation resistant to viable technical catalyst


Problem Statement

Advances in heterogeneous catalyst “structure” are driven to improve their “function” or performance, i.e., activity, selectivity, and stability. Cooperative research is required to understand the structure and function relationships: developing new synthesis protocols for heterogeneous catalysts with unique surface properties, defined porosity, identification and understanding of catalytically active sites, reaction mechanisms, and finally, prediction and analysis of the processes using various computational tools.

Our group focuses on developing new catalyst formulations using innovative synthesis routes for various important heterogeneous catalysts. That includes thermal, electro, and bio-electro catalysis.

The active phase cannot be used directly in its final application or reactor for various reasons, including poor mechanical resistance, heat or mass transport, and fluidization features. We must mix the active phase with other ingredients in a matrix of binder and filler, while we shape it into a technical catalyst. We investigate new synthetic protocols for technical catalysis using spray drying and fluidized beds to cover the whole range of sizes. At the same time, we incorporate additional (unconventional) ingredients such as SiC to improve some features even further.

Goals

  • Technical catalyst I ⇒ spray drying and extrusion
  • Technical catalyst II ⇒ spray fluidized bed reactor
  • Technical catalyst III ⇒ electrospinning
  • Zeolite catalysts ⇒ with defined structure/porosity
  • Multi-metal (high entropy) alloy catalysts
  • MXene catalysts ⇒ single and multi-dimensional
  • Perovskite catalysts
  • Metal-organic framework (MOFs) catalysts
  • Supported metal/metal-oxide catalysts
  • Aerogel catalyst

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Related Publications

Aggregation Kinetics of Technical Catalysts in a Spray-Fluidized Bed

by Alkadhem, Al Majed, Mohamed, Tsotsas, Castaño
Particuology Year: 2026 DOI: https://doi.org/10.1016/j.partic.2026.01.005

Abstract

Size enlargement control and modeling in fluidized beds are crucial in the pharmaceutical and food industries but remain underdeveloped for technical catalyst formulation and shaping. This work uses different modeling approaches to understand aggregation kinetics: single- and two-pathway population balance equation (PBE) modeling and machine learning. These models are trained on a large dataset of experimental results from a bottom spray-fluidized bed, using realistic technical catalyst conditions and ingredients: ZSM-5 zeolite, bentonite, and alumina. Our optimized model is based on a two-pathway PBE with two distinct collision efficiencies for early- and late-stage growth dynamics across nucleation, seed formation, seed aggregation, and layered growth. With this model, we discuss the granulation and agglomeration dynamics of realistic technical catalysts and study the controlled shaping of several case studies with tailored morphologies (50, 100, and 200 μm pellets) under optimized conditions (i.e., maximum yield within the desired particle range) as validation.

Keywords

HCE MKM