PFI-TT: Inline Particle Monitoring in Sterile Liquid Filtration Systems via Holographic Imaging

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The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to detect contamination in filter systems used in the food and beverage sector. The project will develop an inline monitoring system for detecting particle contaminants (e.g., bacteria, fungi) in the sterile liquid filtration systems of food & beverage product lines to provide timely process analysis, which prevents unplanned excursions and downtime while maintaining 24/7 compliance. The method can be readily adapted for applications in the pharmaceutical industry, as well as air quality monitoring in surgical operation/organ transplant rooms, asbestos monitoring at construction sites, etc. The envisioned system is a low-cost, compact setup requiring minimal maintenance as it can remain calibrated for years. Entrepreneurship training will be provided to underrepresented students, including native Americans and women.The proposed project advances digital holographic image sensing to capture diffracted patterns of particles in a three-dimensional sample volume and machine learning-based image processing to characterize them (e.g., concentration, type, viability) with single particle sensitivity. The method can achieve real-time, high-throughput analysis of contaminants, particularly spoilage microbes, impossible with existing inline monitoring techniques using microscopic imaging. It can be used as an alternative rapid label-free microbial test to the conventional offline cultivation methods which take several days. Moreover, this approach can distinguish between a number of microorganisms and test the viability, which other rapid tests, such as polymerase chain reaction, cannot.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.