(455l) High-Throughput Simulations and Machine Learning for Adsorption Processes

The combination of high-throughput simulations and machine learning (HTS/ML) is a powerful tool that can aid in the discovery of nanoporous materials for gas storage and chemical separations. This talk will highlight applications of HTS/ML to (i) search for adsorbents with high temperature of maximum capacity for gas storage, (ii) optimize the desorptive drying conditions for water/alkanediol mixtures, and (iii) predict the spatial distribution of adsorbate molecules from three-dimensional energy grids of the adsorbent.