2025 AIChE Annual Meeting

Session: Molecular and Data Science Modeling of Adsorption

This session focuses on the studies of adsorption in materials via molecular simulations and/or through data-science approaches.

Chair

Gennady Gor, New Jersey Institute of Technology

Co-Chairs

N. Scott Bobbitt, Northwestern University

Presentations

03:30 PM

(628a) Data-Driven Design of Polymeric Adsorbent Materials for Ion-Selective Separations
Wylie Kau, Kristen Abels, Michael Baird, Uran Iwata, William A. Tarpeh

03:45 PM

(628b) Poronet: An Interpretable Pore Graph Neural Network for Prediction of Gas Adsorption in Metal-Organic Frameworks
Chao Zheng, Arun Gopalan, Kaihang Shi

04:00 PM

(628c) Machine-Learned Force Field Development for Molecular Simulation of CO2 Adsorption/Desorption in Uio-66 Metal-Organic Frameworks in a Magnetic Field
Shayan Jalalmanesh, Bassam Rabihavi, Mehdi Vaez Allaei, Muhammad Sahimi, Fateme Rezaei

04:15 PM

(628d) Molecular Dynamics Study to Evaluate Transport Diffusivities and Assess Membrane Performance for CO2 Gas Mixture Separations in Carbon Molecular Sieves
Prince Kumar, Subhadeep Dasgupta, Prabal K. Maiti, K Ganapathy Ayappa

04:30 PM

(628h) Metal-Organic Frameworks for Water Harvesting: Large-Scale Molecular Simulations and Predictive Machine-Learning Models
Li-Chiang Lin, Shiue-Min Shih, Zhi-Xun Xu, Yi-Ming Wang, I-Ting Sung

04:45 PM

(628f) Molecular Simulations Study on the Stiffening of Zeolites Induced By Gas Adsorption
Santiago Flores Roman, Alina Emelianova, Gennady Gor

05:00 PM

(628g) Machine Learning Predictions for Evaluating Organic Acid Separation Technologies
Michiel Wessels