Adaptive acoustic streaming microbial system for oxytetracycline removal

Area of Science:

• Environmental Microbiology
• Biotechnology
• Acoustic Engineering

Background:

• Microalgae-bacteria symbiosis effectively removes antibiotics from water.
• Microbial granulation is crucial for enhancing system performance in water treatment.
• Existing granulation methods lack rapid, controlled assembly.

Purpose of the Study:

• To develop an adaptive acoustic streaming microbial system (AMS) for rapid, quantitative microbial granulation.
• To enable closed-loop modulation of acoustic streaming for dynamic granulation control.
• To investigate the potential of AMS for antibiotic removal from wastewater.

Main Methods:

• Utilized adaptive acoustic streaming with granular phase detection feedback for granulation control.
• Employed convolutional neural networks for real-time recognition of granular processes.
• Integrated channel-excited acoustic streaming and vortex potential wells for microbial adhesion and aggregation.
• Implemented periodic array structures for parallelized microbial consortia fabrication.

Main Results:

• Achieved shear stress of 1500 s⁻¹ and completed microbial system assembly within five minutes.
• Demonstrated 84% removal efficiency for oxytetracycline in wastewater.
• Validated the system's ability for dynamic monitoring and control of granulation.

Conclusions:

• The adaptive acoustic streaming microbial system (AMS) enables rapid and controlled microbial granulation.
• AMS shows significant potential for efficient antibiotic removal in wastewater treatment.
• Customized and automated acoustic vortex methods offer a promising strategy for microbial granulation.