Harnessing the Influence of Pressure and Nutrients on Biological CO2 Methanation Using Response Surface Methodology and Artificial Neural Network—Genetic Algorithm Approaches

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  • January 28, 2025

Authors: Alexandros Chatzis, Konstantinos N. Kontogiannopoulos, Nikolaos Dimitrakakis, Anastasios Zouboulis, Panagiotis G. Kougias

This study investigates the combined effects of trace element concentrations (Fe(II), Ni(II), Co(II)) and applied pressure on biological CO2 methanation performance. The ANN-GA optimization indicated 97.9% methane production efficiency at 1.5 bar pressure and trace metal concentrations of 25.0 mg/L Fe(II), 0.20 mg/L Ni(II), and 0.02 mg/L Co(II). Validation experiments confirmed predictions with deviations below 5%, underscoring the robustness of the combined RSM and ANN-GA modelling approach.

Read the full article: https://doi.org/10.3390/fermentation11010043

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