Solsona Miguel, Nieuwelink Anne-Eva, Meirer Florian, Abelmann Leon, Odijk Mathieu, Olthuis Wouter, Weckhuysen Bert M, van den Berg Albert
BIOS lab on a chip group, MESA+ Institute for Nanotechnology, University of Twente, Drienerlolaan 5, Enschede, The Netherlands.
Inorganic Chemistry and Catalysis, Debye Institute for Nanomaterials Science, Utrecht University, Universiteitsweg 99, 3584, CG, Utrecht, The Netherlands.
Angew Chem Int Ed Engl. 2018 Aug 13;57(33):10589-10594. doi: 10.1002/anie.201804942. Epub 2018 Jul 13.
A better understanding of the deactivation processes taking place within solid catalysts is vital to design better ones. However, since inter-particle heterogeneities are more a rule than an exception, particle sorting is crucial to analyse single catalyst particles in detail. Microfluidics offers new possibilities to sort catalysts at the single particle level. Herein, we report a first-of-its-kind 3D printed magnetophoretic chip able to sort catalyst particles by their magnetic moment. Fluid catalytic cracking (FCC) particles were separated based on their Fe content. Magnetophoretic sorting shows that large Fe aggregates exist within 20 % of the FCC particles with the highest Fe content. The availability of Brønsted acid sites decreases with increasing Fe content. This work paves the way towards a high-throughput catalyst diagnostics platform to determine why specific catalyst particles perform better than others.
更好地理解固体催化剂内部发生的失活过程对于设计性能更优的催化剂至关重要。然而，由于颗粒间的不均匀性更为常见，对单个催化剂颗粒进行详细分析时，颗粒分选至关重要。微流控技术为在单颗粒水平上分选催化剂提供了新的可能性。在此，我们报道了一种首创的3D打印磁泳芯片，它能够根据催化剂颗粒的磁矩对其进行分选。流化催化裂化（FCC）颗粒基于其铁含量被分离。磁泳分选表明，铁含量最高的FCC颗粒中有20%存在大量铁聚集体。随着铁含量的增加，布朗斯台德酸位点的可用性降低。这项工作为建立一个高通量催化剂诊断平台铺平了道路，以确定特定催化剂颗粒比其他颗粒表现更好的原因。
