Our group investigates nanoporous materials, which are well-known for their extremely small pore sizes in angstroms. These materials are gaining prominence for their applications in gas storage, adsorption separations and catalytic reactions.
Employing cutting-edge computational techniques, our group explores and studies various nanoporous materials, including zeolites, metal-organic frameworks, covalent-organic frameworks, and porous organic polymers. We explore the unique properties of these materials and harness their potential for energy and environmental applications.
Matter, 8, 102140 (2025)
Adv. Mater., 36, 2401739, (2024)
J. Mater. Chem. A., 10(46), 24802 - 24812 (2022)
Adv. Sci., 8(11), 2004940, (2021)
At the intersection of artificial intelligence (AI), chemistry, and chemical engineering, our research group employs multi-faceted approaches to solve complex energy and environmental challenges. We explore new possibilities for material design, reaction optimization, and process efficiency by integrating AI algorithms with chemical and process engineering principles. We develop data-driven methods to predict molecular properties and optimize chemical processes.
J. Am. Chem. Soc., in press
Matter, 8, 102140 (2025)
ACS App. Mater. & Int., 16, 45, (2024)
J. Chem. Theo. Comp., 20, 12, 5352 - 5367 (2024)
J. Phys. Chem. A., 128(12), 2399 - 2408, (2024)
Ind. Eng. Chem. Res., 62(37), 15176 - 15189, (2023)
Adv. Sci., 9(21), 2201559, (2022)
J. Phys. Chem. Lett., 11(14), 5412 - 5417, (2020)
Sci. Adv., 2(10), e1600909, (2016)
Our research group focuses on the modeling, optimization, and techno-economic analysis of adsorption-based separation processes, including vacuum swing adsorption (VSA), pressure swing adsorption (PSA), and temperature swing adsorption (TSA). We combine rigorous process modeling, which includes heat, momentum, and mass balances, with advanced optimization techniques to maximize separation performance, reduce energy consumption, and enhance operational efficiency. Our work also integrates scheduling and scale-up strategies to enable flexible, large-scale deployment of adsorption technologies for applications in carbon capture, hydrogen purification, and other critical energy and environmental processes.
Sep. Purif. Tech, 378, 3, 134786 (2025)
Matter, 8, 102140 (2025)
Chem. Eng. J., 496, 154166 (2024)
Ind. Eng. Chem. Res., 62(37), 15176 - 15189, (2023)
Chem. Eng. J., 426, 131787, (2021)
ACS Sus. Chem. & Eng., 7(13), 11529 - 11539, (2019)
We believe that scientific progress is accelerated when research is open, transparent, and reproducible. Our group develops computational workflows, datasets, and software tools that can be freely accessed, examined, and reused by the broader scientific community.
By integrating open-source workflows, we minimize barriers to research problems we work on. Our recent efforts (1, 2) demonstrate how reproducible science can be embedded into large-scale computational materials screening and data-driven discovery.
https://github.com/Chung-Research-Group/reproducible-workflows