Meiirbek Islamov
Currently, I am pursuing a Ph.D. degree in Chemical Engineering at the University of Pittsburgh with an expected completion date of January 2024. My current research at Pitt focuses on understanding nanoscale thermal transport physics in Metal-Organic Frameworks (MOFs), a class of porous materials, which have been heralded as revolutionary materials for gas adsorption applications. In my research, I use high-performance computing, deep learning, and computational materials science/chemistry techniques.
Sessions
Metal-Organic Frameworks (MOFs) have vast potential for gas adsorption, but their practical use hinges on their ability to dissipate thermal energy generated during adsorption. Here, we performed the first high-throughput screening of thermal conductivity in over 10,000 MOFs using molecular dynamics simulations. Next, we developed a graph neural network (GNN) based model to swiftly predict the diagonal components of the thermal conductivity tensor for accelerated materials discovery. Attendees will gain insights into how GNNs can be trained to predict material tensor properties, benefiting both the materials science and machine learning communities.