Description:

Center for Catalysis and Surface Science (CCSS) Student Seminar Series

Friday, October 17, 2025 | 12-1pm CT
Ryan Hall, 4003 | 2190 Campus Drive

Join the Center for Catalysis and Surface Science (CCSS) for the Student Seminar Series. Hear from graduate students and postdoctoral scholars during two presentations. This month's speakers are Hongjun Park from the Notestein lab and Sai Praneet Batchu from the Broadbelt Lab.

About the Presentations

Speaker: Hongun Park

Title: "Metal-Ion Catalysis for Synthetic Strategies of Zeolite-Templated 3D Graphene-Like Carbon Materials"

Abstract: 

In this talk, recent advancements in energy and catalysis applications utilizing zeolite-templated carbon (ZTC) materials are presented [1]. The ZTC synthesis has been achieved by metal-ion-catalyzed carbonization followed by the removal of zeolite templates [2]. Successful synthesis produces 3D graphene-like ZTC materials with highly ordered microporous structures and high surface areas (~ 3,000 m2/g) and narrow pore size distributions, around 1 nm [1, 2]. This ordered microporous structure finds interesting applications in various energy storage and conversion systems, including supercapacitors, zinc-iodine batteries, and lithium-ion capacitors [3-5]. As reported in the literature, ZTC can serve as an electrode material or electrocatalyst extending beyond traditional gas storage applications.

Speaker: Sai Praneet Batchu

Title: "Microkinetic Modeling of Ethylene Oligomerization on H-BEA Zeolites"

Abstract:

To meet the increasing demand in transportation fuels for the next few decades, shale gas is a potential alternative feedstock to crude oil. Transportation fuels are composed of linear and branched alkanes, cycloalkanes, olefins, aromatics (C5 and above ), and can be produced from shale gas in two steps: 1) coupling of methane or dehydrogenation of ethane/propane to produce ethylene and propylene and, 2) converting ethylene/propylene to higher-C molecules via. oligomerization reactions accompanied by various other reactions such as cyclization, isomerization, aromatization etc. The latter step represents a complex reaction network, entailing myriad of reactions and species, thus making it challenging to construct corresponding microkinetic models and such models are essential to optimize the reaction conditions to obtain maximum yields of desired fuel composition. A way to overcome this challenge is by combining reactions network generation tools, networking pruning rules, and reaction parameterization strategies. 

In this work, we build a complex microkinetic model for ethylene oligomerization on H-BEA catalyst to produce paraffins, olefins, dienes, and aromatics up to C10 compounds. We use NetGen to generate the reaction networks, prune the reaction network using various  reaction rules, parametrize the model using various scaling relationships, and finally, make a predictive model by fitting it to in-house experimental data at various reaction conditions. This model is more complex than the already existing oligomerization models on H-BEA which merely pertain to linear paraffins and olefins and low rank products. Our model can potentially propose optimal reaction conditions that not only maximize the yields of desired fuel composition but also mitigate coke formation reactions. 

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The mission of the Center for Catalysis and Surface Science (CCSS) is to promote interdisciplinary research fundamental to the discovery, synthesis, and understanding of catalysts and catalytic reactions essential to modern society. As a part of the Paula M. Trienens Institute for Sustainability and Energy, CCSS applies fundamental advances in catalysis science towards applications in alternative fuels, abatement of harmful emissions, resource recovery concepts, new processing routes, and many other strategies towards making chemicals more sustainable.

References

H. Nishihara & T. Kyotani, Chem. Commun., 2018, 54, 5648
K. Kim et al., Nature, 2016, 404, 760-770.
H. Park et al, Carbon, 2019, 155, 570-579.
H. Park et al., Adv. Energy Sustainability Res., 2021, 2, 2100076
H. Park et al., ACS Appl. Energy Mater., 2025, 8, 9489-9496.