(342v) Toward Data-Driven Approaches to Inverse Design: Fast and Accurate Evaluation of Gas Adsorption and Diffusivity in Nanoporous Materials

The recent advance in data-driven approaches to inverse design has emphasized the importance of accurate and efficient evaluation of the physical properties of materials underpinning their performance. In this poster, we demonstrate recent theoretical developments and high-performance computation rendering new capabilities to generate large-scale high-fidelity data for gas adsorption and diffusivity in nanoporous materials with atomistic models. The efficient computational tools form an important cornerstone for the inverse design of nanoporous materials either as adsorbents or membranes for gas separation.