2022 Annual Meeting

Session: Molecular and Data Science Modeling of Adsorption I

Chair

Gor, G., New Jersey Institute of Technology

Co-Chairs

Presentations

03:30 PM

(572a) Active Learning for Efficient Navigation of Adsorption Landscapes in MOFs

03:45 PM

(572b) Adsorption Isotherms of Argon, Nitrogen, Carbon Dioxide, n-Butane, and Water for Pore Characterization of Chromatographic Particles

04:00 PM

(572c) Mofdb: An Accessible Online Database of Computational Adsorption Data for Nanoporous Materials

04:15 PM

(572d) A Combined Deep Learning and Classical Potential Approach for Modeling Diffusion in Uio-66

04:30 PM

(572e) Machine Learned Disposable Force Fields for Fluid-Solid Simulations: Application to Water Transport in Carbon and Boron-Nitride Nanotubes

04:45 PM

(645e) Molecular Simulation of Compressibility of Water in Carbon Nanopores

05:00 PM

(572g) Understanding and Virtual Design of Low-Volatility Ionic Liquid Solvents for Spacecraft CO2 Separations

05:15 PM

(572h) Machine Learning Approach for Construction of Fingerprint Kernels for Pore Structure Characterization of Metal-Organic Frameworks

05:30 PM

(572i) High-Throughput Screening of Hypothetical Functionalized-Irmofs for Separation of Alkanes

05:45 PM

(572j) Efficiently Exploring the Adsorption Space of Molecules in MOFs Combining the Use of Molecular Simulations, Machine Learning, and IAST