08/13/2025
By Danielle Fretwell

The Francis College of Engineering, Department of Electrical and Computer Engineering, invites you to attend a Doctoral Dissertation Proposal defense by Guoqiang Cui on: "Real-Time Multi-Parameter Distributed Optical Sensing System for Online Monitoring in Bioprocessing'"

Candidate Name: Guoqiang Cui
Degree: Doctoral
Defense Date: Wednesday, Aug. 27, 2025
Time: 9 -11 a.m.
Location: Perry Hall 215

Committee:

  • Advisor: Xingwei Wang, Professor, Electrical & Computer Engineering, University of Massachusetts Lowell
  • Xuejun Lu, Professor, Electrical & Computer Engineering, University of Massachusetts Lowell
  • Seongkyu Yoon, Professor, Chemical Engineering, University of Massachusetts Lowell

Brief Abstract:
In modern biopharmaceutical manufacturing, maintaining consistent product quality and process efficiency depends on real-time monitoring of multiple critical quality attributes (CQAs) such as pH, dissolved oxygen (DO), temperature, glucose, and lactate. Existing sensing technologies, however, face significant limitations. Conventional electrochemical and optical probes often require dedicated sampling ports, introduce contamination risks, and lack compatibility with small-scale culture systems such as milliliter-scale shake flasks. This creates a critical gap between early-stage process development and large-scale manufacturing.

Optical fiber sensors offer unique advantages, including miniature size, immunity to electromagnetic interference, compatibility with harsh or aseptic environments, and the ability to integrate multiple sensing modalities along a single fiber. Their distributed sensing capability enables spatially resolved measurements at any location inside a bioreactor, without requiring invasive probes or sample extraction.

This proposal presents the design, fabrication, and validation of a 125 μm-diameter, multi-parameter optical fiber sensor capable of simultaneously monitoring pH, temperature, DO, glucose, and lactate. The proposal first characterizes individual sensing structures and optimizes their sensitivity through tailored coating and structural modifications. Then, multi-parameter integration strategies are explored configurations for parameter decoupling. Controlled laboratory experiments are conducted to evaluate sensitivity, resolution, stability, and cross-sensitivity in simulated media. Next, validation studies are performed in small-scale shake flasks, followed by scale-up tests in pilot bioreactors to demonstrate seamless scalability. Finally, data processing algorithms for spectral analysis and multi-parameter signal separation are developed to enable real-time, closed-loop, data-driven control.