2025 AIChE Annual Meeting

(628c) Machine-Learned Force Field Development for Molecular Simulation of CO2 Adsorption/Desorption in Uio-66 Metal-Organic Frameworks in a Magnetic Field

Authors

Bassam Rabihavi, University of Tehran
Mehdi Vaez Allaei, University of Tehran
Muhammad Sahimi, University of Southern California
Fateme Rezaei, Missouri S&T
Efficient CO2 capture combined with effective desorption strategies is essential to enhance the performance of adsorption-based carbon capture technologies. While many sorbents can capture CO2, the problem is much more difficult when CO2 to be captured directly from air. In addition, desorption of CO2 for storage or alternative usage is also a challenging problem. This study proposes a novel concept, namely, applying a magnetic field to facilitate targeted regional CO2 desorption in UiO-66, a zirconium-based metal-organic framework well-known for its substantial CO2 adsorption capacity. We describe an approach that integrates molecular dynamics simulations guided by newly developed force fields to explore how adsorbed CO2 molecules might respond to an external magnetic field. Investigating this magnetic field-assisted approach could yield valuable insights for optimizing adsorption-desorption cycles, potentially paving the way for increased efficiency and reduced energy consumption in carbon capture applications.