Project: Modeling and Data Analysis for Designing Photocatalytic Degradation

Figure: Proposed μLED packed bed photoreactor is made up of coated wirelessly powered UV-LEDs. Beer-Lambert calculation of penetration depth shows need for sub-millimeter lengthscales (ε=1300 cm-1 M-1).
In the pharmaceutical, water and wastewater industries, photocatalyzed reactions have piqued interest as potentially transformative alternatives to heavy-metal catalysis or toxic oxidation reagent chemistry. While the conventional mercury lamp UV technology has been used industrially (i.e., water disinfection a resurgence in recent years has emerged due to the advent of highly tunable, low-power light emitting diodes (LEDs). To harness the power of photochemical reactions with such diodes, substantial modeling, data analysis, and scientific advances are needed in reaction engineering and design of UV systems to achieve efficient light transmission for chemical transformations.

In this proposed work, a new reactor technology (Figure G) will be enabled through scientific advancements in photocatalytic material coating, machine learning, modeling of physical processes, and wireless powered electrical microcircuits. The physical and data science
advances will be coupled with new reaction engineering concepts including photochemistry and packed beds, transitioning away from classical UV flow systems. The proposed approach will aim to leverage recent advances in deep learning, wireless power, and medical devices (optogenetics) to deliver light in spatially distributed reactor with elevated photonic flux without sacrificing hydrodynamic benefits realized in packed beds.

Researchers:   Dr. Teixeira,  Chem. Eng. & Data Science faculty, TBD.