Goals
Leverage advances in machine learning and data analytics to enable faster and more accurate calculations of chemical properties using quantum-mechanical techniques such as density functional theory (DFT).
Students will learn about applications of quantum-mechanical simulations in photocatalysis and electrocatalysis, with particular focus on nitrogen fixation and water oxidation. These reactions have the potential to help alleviate global hunger by enabling distributed fertilizer production and helping to provide clean energy based on hydrogen fuel derived from water.
Issues Involved or Addressed
Methods and Technologies
Academic Majors of Interest
- Computing›Computational Science and Engineering
- Computing›OMSCS synchronous, case-by-case
- Engineering›Chemical and Biomolecular Engineering
- Engineering›Computer Engineering
- Engineering›Materials Science and Engineering
- Other
- Sciences›Chemistry
- Sciences›Mathematics
- Sciences›Physics
- Sciences›Statistics
Preferred Interests and Preparation
ChBE, Chem, MSE, Physics – Background/interest in quantum mechanics, computational materials science, computational chemistry. Curiosity about machine learning, data science, and big data. Programming skills would be helpful but are not required.
CS, Applied Math, Stats, CSE – Background/interest in machine learning, uncertainty quantification, data-driven methods. Interest in the intersection of machine learning and physics. Programming skills encouraged but not required.
CS – Interest in software architecture, database design, schema-free data models, functional programming, interactive visualization. Programming experience and skills are strongly encouraged.
Meeting Schedule & Location
Team Advisors
- Chemical and Biomolecular Engineering
- Chemical and Biomolecular Engineering