Outputs (2)

A systematic review of machine-learning solutions in anaerobic digestion (2023)
Journal Article
Rutland, H., You, J., Liu, H., Bull, L., & Reynolds, D. (2023). A systematic review of machine-learning solutions in anaerobic digestion. Bioengineering, 10(12), Article 1410. https://doi.org/10.3390/bioengineering10121410

The use of machine learning (ML) in anaerobic digestion (AD) is growing in popularity and improves the interpretation of complex system parameters for better operation and optimisation. This systematic literature review aims to explore how ML is curr... Read More about A systematic review of machine-learning solutions in anaerobic digestion.

Impact of feedstock dilution on the performance of urine-fed ceramic and membrane-less microbial fuel cell cascades designs (2023)
Journal Article
Walter, X. A., You, J., Gajda, I., Greenman, J., & Ieropoulos, I. (2023). Impact of feedstock dilution on the performance of urine-fed ceramic and membrane-less microbial fuel cell cascades designs. Journal of Power Sources, 561(30), 232708. https://doi.org/10.1016/j.jpowsour.2023.232708

Recent advancements in the microbial fuel cell (MFC) field have led to the deployment of pilot-scale autonomous sanitation systems converting the organic content of urine into electricity to power lights in decentralised areas. Two designs have been... Read More about Impact of feedstock dilution on the performance of urine-fed ceramic and membrane-less microbial fuel cell cascades designs.