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Machine learning for inverse problems in reaction engineering

Consider a chemical reactor like a PFR. In the usual, forward problem, taught in CRE courses, you are given the input flow rate and reactant concentration, along with kinetic reaction-rate information, and asked to predict the output concentration or conversion. But suppose, instead, that the conversion is measured experimentally and you are asked to use a model to estimate the input flow rate or input concentration. This is an inverse problem. Such problems arise when using specialized research reactors to determine chemical kinetics information.

Redox flow batteries

With increased penetration of renewable electricity from wind and solar, that modern electricity grid is expected to be more dynamic as it actively responds to supply and demand of renewable electricity. In this scenario, redox flow batteries are seen as a key technology for longer-term energy storage (time ≥ 4 hours). This SLP is an opportunity to perform a review of various chemistries for flow batteries, compute the levelized cost of storage and determine the key limiting factors that prevent widespread commercialization of this technology.

How do cells react to microplastic pollution?

BTP
Developing an understanding the effect of microplastics on cellular function is important. This project will involve preparing microplastics from common commercial polymers (such as polyethylene, polypropylene, polystyrene and polyesters) and their thorough characterization. One aspect of this project will be to come up with a protocol to generate fluorescently tagged microplastics to allow them to be tracked as they are ingested by cells. Subsequently, cells will be exposed to these microplastics and their response will be studied.