Total mentored projects: 13
Studying the dye filtration properties of composite nanofibers composed of polymers encapsulating MOF particles will help understand their performance qualities.
Studying the filtration properties of ultra-porous membranes will help create more environmentally friendly ways to treat industrial waste.
Writing a graphical user interface with text mining code will help our chemical engineering lab get information from articles more efficiently.
A cost-effective, sustainable ammonia detection sensor can be designed using metal organic frameworks by relying on measurable conductivity changes from gas adsorption.
Developing porous membranes that can separate mixtures will help with progress in issues such as climate change and renewable energy.
Developing machine learning algorithms to search large databases will help autonomously discover new crystalline material structures.
Studying the filtration capabilities of a composite material will help make more cost-efficient emissions filtration systems.
Developing electrospun precursors to mixed matrix membranes will improve chemical separations capabilities.
Metal-organic frameworks display detectable changes in electrical resistance after adsorption which will allow for use in ammonia detection in industry.
Studying thermal annealing with mixed matrix membranes will improve gas separation when nanoparticles are embedded in the membrane for carbon dioxide capture.
Optimizing the exfoliation step for copper 2D metal organic frameworks will improve the performance of gas separation processes via mixed matrix membranes.