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Optical Fiber pH and Dissolved Oxygen Sensors for Bioreactor Monitoring: A Review
Guoqiang Cui1, Rui Wu1, Lidan Cao1
1Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA.
Optical fiber sensors offer advanced in situ monitoring for bioreactors, overcoming limitations of conventional methods. This technology enables precise real-time measurement of critical parameters like pH and dissolved oxygen (DO) for improved bioprocessing.
Area of Science:
- Biotechnology and Bioprocessing
- Sensor Technology
- Chemical Engineering
Background:
- Real-time monitoring is crucial for bioprocessing efficiency and product quality.
- Conventional bioreactor sensors face challenges like calibration drift and limited spatial coverage.
- Optical fiber sensors present a viable alternative due to their sensitivity, remote capabilities, and compact size.
Purpose of the Study:
- To review advancements in optical fiber sensors for bioreactor monitoring.
- To focus on pH and dissolved oxygen (DO) sensing, with brief coverage of temperature and pressure.
- To compare different sensing mechanisms, materials, and architectures for bioreactor applications.
Main Methods:
- Literature review of recent progress in optical fiber sensing for bioprocessing.
- Comparison of various sensing mechanisms (e.g., fluorescence, absorption) and materials.
- Analysis of fiber architectures and integration strategies for laboratory and industrial bioreactors.
Main Results:
- Optical fiber sensors demonstrate high sensitivity, fast response times, and good stability for key parameters.
- Various materials and architectures are suitable for different bioreactor environments and scales.
- Successful integration strategies for in situ monitoring have been developed.
Conclusions:
- Optical fiber sensors are a promising technology for advanced bioreactor monitoring.
- Future trends include multi-parameter sensing, enhanced long-term reliability, and integration with Process Analytical Technology (PAT).
- These advancements pave the way for intelligent bioprocessing through data-driven control.
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