Potential and challenge in accelerating high-value conversion of CO₂ in microbial electrosynthesis system via...

Area of Science:

• Biotechnology and Bioengineering
• Chemical Engineering
• Environmental Science

Background:

• Microbial electrosynthesis for CO2 utilization (MESCU) is a promising technology for producing high-energy-density chemicals.
• MESCU offers long-term stability and high coulombic efficiency, attracting significant research interest.
• Data-driven approaches present a novel strategy to optimize MESCU processes.

Purpose of the Study:

• To review the potential of data-driven approaches in enhancing CO2 conversion via MESCU.
• To identify critical challenges in MESCU advancement.
• To discuss how data analytics can address these challenges and guide future research.

Main Methods:

• Literature review focusing on data-driven strategies applied to MESCU.
• Analysis of challenges in reactor configuration, cathode design, and microbial community analysis.
• Exploration of data-driven methods for parameter identification and omics data interpretation.

Main Results:

• Data-driven approaches can identify key parameters for reactor setup and cathode design.
• These methods aid in deciphering complex omics data from microbial communities in MESCU.
• The review highlights the potential to accelerate MESCU research and industrialization.

Conclusions:

• Data-driven approaches are crucial for overcoming MESCU limitations.
• Leveraging data analytics will enhance the efficiency and applicability of CO2 utilization technologies.
• This review provides a roadmap for future data-driven applications in MESCU.