Research Opportunity Number: MAE-04

Project Title: Machine learning and molecular dynamic simulations of high-pressure combustion for green power generation and propulsion using H2/NH3

Project Summary: Hydrogen and ammonia are green fuels for advanced propulsion. The goal of this project is to use quantum chemistry database of reactions and machine learning to obtain optimized energy potentials for reaction molecular dynamics. The optimized molecular dynamics model will be used to calculate high pressure fuel oxidations such as hydrogen and ammonia and to understand the effect of pressure (multi-body collisions) and intermolecular force on low temperature fuel oxidations for hydrogen and ammonia powered propulsion engines. The work will be conducted under the supervision of a research staff and a graduate student.

Student Roles and Responsibilities: The student(s) will perform experimental support, data analysis, computation modeling, literature review, and create a presentation

Additional Considerations:  Participation of at least 4 weeks is required.

Department/Institute: Mechanical and Aerospace Engineering

Faculty Sponsor:   Yiguang Ju

Participation Dates:  6/1/2024 to 8/15/2024

Stipend Offered:  $0

Number of Internships Available: 0-2

Application Deadline: March 15, 2024, midnight eastern daylight time