ERI: Integrated Molecular Simulation and Artificial Intelligence Framework for the Design of Task-Specific Ionic Liquids

This project focuses on designing ionic liquids (ILs), which are chemical compounds with customizable properties. They can be used in a variety of applications including energy storage, carbon capture, water treatment, and advanced manufacturing. Designing new ILs is challenging because there are many possible compositions. This project uses advanced computer simulations, machine learning, and artificial intelligence to predict IL properties and design new ones efficiently. It creates a comprehensive IL database and tools for designing task-specific ILs, such as those for refrigerant separation and resource recovery. The research outcomes support sustainable chemical processes, reduce pollution, advance environmentally friendly technologies, and foster educational opportunities for students. This project leverages molecular simulations, machine learning (ML), and generative artificial intelligence (AI) to accelerate the design and discovery of ionic liquids - versatile, tunable salts with applications in energy storage, carbon capture, water treatment, and chemical separations. By developing accurate force fields, an IL-specific molecular transformer for property prediction, and a generative AI framework to expand the IL chemical space, the research enables scalable IL discovery and task-specific design for applications like refrigerant separation and critical material recovery. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2549832 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Ning Wang | Institution: University of Texas at Tyler, TYLER, TX | Award Amount: $199,995 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2549832 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2549832.html