Fine-tuning membrane filters for optimal performance
Membrane filters are thin sheets of porous material that remove particles from a fluid that passes through them. They’re also part of a multibillion-dollar industry.
They’re used, for example, to purify water, treat radioactive sludge and remove cloudiness from beer during brewing.
But a membrane filter’s characteristics — its behavior and performance — are not constant. Over time, particles foul and degrade the filter’s performance.
To mitigate this costly problem, NJIT researchers Linda Cummings and Lou Kondic, math professors in NJIT’s College of Science and Liberal Arts, are developing mathematical models and simulations that enable membrane designs to be finely tuned for optimal performance.
Funded by the National Science Foundation (NSF), the team is also collaborating with an industrial partner to maximize the chances of translating their theories into real-world applications.