| Project Detail |
Metal organic frameworks (MOFs) are advanced porous materials with multifunctional tunable properties offering great potential for energy, environment, and biomedical technologies. The number of MOFs is increasing at an exponential rate. Studying millions of MOFs for different applications by random material selection using iterative experimental testing or brute-force computational simulations is impossible. The full potential of MOFs for target applications can only be unlocked if the storage and transport properties for important chemical and biological guest molecules trapped in the pores of each MOF are known. In this project, I will create a materials intelligence ecosystem for precisely assessing guest storage and transport properties of all MOFs by combining state-of-the-art atomistic calculations, molecular simulations, machine learning, and data science, integrated with past and future experiments. I will focus on ten critical guest molecules to address the key societal challenges of our world: hydrogen and methane to use MOFs for clean energy storage; ammonia, carbon monoxide, carbon dioxide, nitrous oxide to use MOFs for capturing toxic gas and combatting global warming; fluorouracil, methotrexate, nitrogen, oxygen to use MOFs as nanocarriers for anti-cancer drug therapy and biomedicine. The ground-breaking gains of my project will include the creation of the world’s first database for guest storage and transport properties of millions of MOFs; accurate assessments of new technologies by precise MOF-application matching; and generating design guidelines for high-performing MOFs to accelerate discovery of new materials. My novel methodology synergizing theory and data-driven science will greatly extend the reach of current experimental and computational studies by discovering new thermodynamic theories that will be extendible to other material classes and providing atomic-level insights into MOF-guest interactions that determine materials’ performances. |
