Speaker: Nishamol Kuriakose
Title: Machine Learning-Based Prediction of Hydrogen Adsorption Capacity of Nanoporous MOF materials
Abstract: Metal-organic frameworks (MOFs) have been extensively studied as promising materials for hydrogen storage. In this presentation, I will discuss our computational screening procedures and the application of machine learning techniques to predict MOF materials with high H2 adsorption capacity under room temperature conditions.