AIMC Topic: Bioreactors
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Machine learning-based optimization of biogas and methane yields in UASB reactors for treating domestic wastewater.
Biodegradation
Jun 26, 2025
This study aimed to optimize biogas and methane production from Up-flow anaerobic sludge blanket reactors for treating domestic wastewater using advanced machine learning models-namely, eXtreme Gradient Boosting (XGBoost) and its hybridized form, XGB...
Enabling malic acid production from corn-stover hydrolysate in Lipomyces starkeyi via metabolic engineering and bioprocess optimization.
Microbial cell factories
May 21, 2025
BACKGROUND: Lipomyces starkeyi is an oleaginous yeast with a native metabolism well-suited for production of lipids and biofuels from complex lignocellulosic and waste feedstocks. Recent advances in genetic engineering tools have facilitated the deve...
An integrated review on the role of different biocatalysts, process parameters, bioreactor technologies and data-driven predictive models for upgrading biogas.
Journal of environmental management
May 5, 2025
As energy consumption and waste generation from human activities continue to rise, the technology of anaerobic digestion (AD), which converts waste into bioenergy, has gained popularity. Biogas produced from AD commonly contains 60 % CH, 40 % CO and ...
Predicting single-cell protein production from food-processing wastewater in sequencing batch reactors using ensemble learning.
Bioresource technology
Apr 19, 2025
Producing single-cell protein (SCP) from food-processing wastewater offers a sustainable approach to resource recovery, animal feed production, and wastewater treatment. Decision-makers need accurate system performance data under variable influent co...
Machine learning algorithms for predicting membrane bioreactors performance: A review.
Journal of environmental management
Mar 17, 2025
Membrane bioreactors (MBR) are recognized as a sustainable technology for treating polluted effluents. Machine learning (ML) algorithms have emerged as a modeling option to predict pollutant removal and operational variables such as membrane fouling,...
Enhanced nitrogen prediction and mechanistic process analysis in high-salinity wastewater treatment using interpretable machine learning approach.
Bioresource technology
Mar 11, 2025
This study introduces an interpretable machine learning framework to predict nitrogen removal in membrane bioreactor (MBR) treating high-salinity wastewater. By integrating Shapley additive explanations (SHAP) with Categorical Boosting (CatBoost), we...
Development of artificial neural network model for anaerobic digestion-elutriated phase treatment.
Journal of environmental management
Mar 5, 2025
Nonlinear autoregressive exogenous (NARX) neural network models were used to forecast the time-series profiles of anaerobic digestion-elutriated phase treatment (ADEPT). Experimental data from the operation of the pilot plant and lab-scale reactor we...
Harnessing near-infrared and Raman spectral sensing and artificial intelligence for real-time monitoring and precision control of bioprocess.
Bioresource technology
Feb 7, 2025
Effective monitoring and control of bioprocesses are critical for industrial biomanufacturing. This study demonstrates the integration of near-infrared and Raman spectroscopy for real-time monitoring and precise control of gentamicin fermentation. Th...
Graph-based deep learning for predictions on changes in microbiomes and biogas production in anaerobic digestion systems.
Water research
Jan 13, 2025
Anaerobic digestion (AD), which relies on a complex microbial consortium for efficient biogas generation, is a promising avenue for renewable energy production and organic waste treatment. However, understanding and optimising AD processes are challe...
Enhanced prediction of partial nitrification-anammox process in wastewater treatment by developing an attention-based deep learning network.
Journal of environmental management
Jan 9, 2025
In the process of partial nitrification and anaerobic ammonia oxidation (anammox) for nitrogen removal, the process offers simple metabolic pathways, low operating costs, and high nitrogenous loading rates. However, since the partial nitrification-an...
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