ERI: Fundamental Study of Multiscale Dynamics of Molecular Mixing and Chemical Reactions in Multiphase Systems

NSF Award Search · 01002627DB NSF RESEARCH & RELATED ACTIVIT · $200,000 · view on nsf.gov ↗

Abstract

This project will examine how different substances mix and react in flowing mixtures of liquids and gases. When fluids mix and undergo chemical reactions, tiny random swirls of turbulence control how well molecules mix and react. Understanding these processes is very important because they affect the efficiently of energy production, how pollutants spread in the environment, and how chemicals, materials, and medicines are manufactured. However, predicting and controlling mixing and reactions in such chaotic flows is a big challenge because small changes at the microscopic level can lead to very different outcomes. To address this challenge, the project will develop new computer models that more accurately represent mixing and chemical reactions in complex flows at the molecular scale. Better simulation of these processes will help engineers design cleaner engines, more efficient chemical reactors, and processes to create materials with less waste and pollution. The project will also emphasize education and accessibility by training students in advanced simulation techniques, releasing new software tools as open source to the public, and engaging students through outreach activities. Through these efforts, the project will advance scientific knowledge while contributing to national prosperity, environmental protection, and public health. The research will develop a new bounded Langevin micromixing model to simulate molecular-scale mixing in turbulent multiphase flows. The stochastic model enforces physical bounds on scalar concentrations and provides improved predictions of how mixing fluctuations decay over time. Chemical reaction kinetics will be tightly coupled with the mixing process through Jacobian matrix analysis, allowing the model to adjust local mixing rates based on relevant reaction time scales. In addition, the model will adapt to local flow conditions using the Damköhler number, ensuring accurate treatment across regimes ranging from mixing-limited t

Key facts

NSF award ID
2549901
Awardee
California State University-Long Beach Foundation (CA)
SAM.gov UEI
P2TDH1JCJD31
PI
Ehsan Madadi
Primary program
01002627DB NSF RESEARCH & RELATED ACTIVIT
All programs
Estimated total
$200,000
Funds obligated
$200,000
Transaction type
Standard Grant
Period
07/01/2026 → 06/30/2028