Ceramic-separator microbial fuel cells promise a double payoff: they strip pollutants from wastewater while generating electricity, yet their output collapses when substrate concentrations climb too high. A new study tackles this problem statistically, fitting nine kinetic models to experimental data and using a multi-criteria selection framework to identify which mathematical formulation best captures the inhibition behaviour for each response. The work, published in Discover Electrochemistry, establishes precise operating windows for organic carbon and nitrate loadings that keep the reactors running efficiently.
The research team, led by Somdipta Bagchi and Manaswini Behera, operated earthen pot microbial fuel cells with a volume of 100 mL, stainless steel mesh anodes of 42.6 square centimetres, and graphite plate cathodes. The pots themselves, made from locally available lateritic soil, served simultaneously as the anode chamber and as a low-cost separator. Their porous alumina-silicate walls allowed ionic transport while restricting bulk liquid crossover, and the electrodes sat in direct contact with the inner and outer pot surfaces to minimise electrode spacing and ohmic losses.
To map the kinetics, the researchers fed synthetic wastewater at chemical oxygen demand levels ranging from 500 to 5000 mg/L, adjusting sucrose concentration for each reactor. Ten separate MFCs covered the concentration spectrum, each dedicated to a single substrate level. For the nitrate experiments, a similar setup of ten earthen pot MFCs received sodium nitrate concentrations from 50 to 1850 mg/L, with sucrose adjusted to maintain a carbon-to-nitrogen ratio of 5:1. The cells ran for 18 days in six batch cycles of three days each, and steady state was considered reached when operating voltage proved replicable after at least three cycles.
Steady-state datasets from four relationships were analysed: COD versus COD degradation rate, COD versus power density, nitrate versus nitrate degradation rate, and nitrate versus power density. Non-linear regression in MATLAB (R2020a) fitted nine candidate models, including Monod, Haldane, Aiba, Edwards, Luong, Han-Levenspiel, Yano-Koga, Webb and Tseng-Wayman. Rather than relying solely on the coefficient of determination, the team evaluated each fit using R², root mean square error, mean absolute percentage error, corrected Akaike Information Criterion and Bayesian Information Criterion, penalising model complexity to avoid overfitting.
The results show why this matters. For COD degradation, the Edwards model emerged as optimal with an R² of 0.968, outperforming the over-parameterised Han-Levenspiel and Luong models despite their slightly higher R² of 0.972. The classical Monod model, lacking any inhibition term, performed very poorly with an R² of −0.011, confirming that explicit representation of substrate inhibition is required to describe COD removal in this system. The fitted Edwards parameters revealed a maximum volumetric degradation rate of 10 kg/m³·d, a half-saturation constant of 0.96 kg/m³, and an inhibition constant of 2.26 kg/m³, indicating that the biofilm is highly sensitive to organic overloading once substrate loading crosses that threshold.
Experimentally, the maximum volumetric COD degradation rate reached 3.17 kg/m³·d at 1.5 kg/m³ organic loading, after which further increases in COD depressed the rate. The researchers attribute this to accumulation of volatile fatty acids and protons in the anolyte, causing local acidification, metabolic stress and feedback inhibition of key metabolic pathways. For power generation, the volumetric power density peaked at 0.56 W/m³ when COD reached 3.0 kg/m³, then dropped slightly to 0.50 W/m³ at 5.0 kg/m³. The Luong model best described this relationship, yielding a maximum theoretical power output of 1 W/m³ with a substrate affinity constant of 1.56 kg/m³ and a critical inhibitory concentration of 5.25 kg/m³.
The nitrate experiments told a similar story. Nitrate degradation rate rose from 0.24 kg N/m³·d at 0.05 kg N/m³ loading to 0.26 kg N/m³·d at 0.25 kg N/m³, then fell steadily to 0.08 kg N/m³·d at 2 kg N/m³. The Edwards model again proved the parsimonious winner, with parameters indicating high affinity near 0.03 kg/m³ and inhibition onset at 1.52 kg N/m³. For power generation with respect to nitrate, the Edwards model also won, with a maximum theoretical output of 6.45 W/m³, a substrate affinity of 0.672 kg N/m³, and an inhibition constant of 0.777 kg N/m³, suggesting a narrow operational window between affinity and inhibition.
The study establishes precise operating windows to avoid inhibition: COD below 5.25 kg/m³ and nitrate below 0.78 kg N/m³. Substrate affinities of 0.96 to 1.56 kg/m³ for COD and 0.028 to 0.672 kg N/m³ for nitrate highlight the suitability of ceramic MFCs for low-to-moderate strength wastewaters. Compared to literature values, the current systems show comparable affinity but lower inhibition thresholds, confirming that concentration control is critical for optimising performance. The authors note that the multi-criteria approach challenges traditional R²-only model selection for engineering ceramic MFCs, penalising complexity and ensuring more robust interpretation of the chemical and biological interactions at the ceramic-biofilm-electrolyte interface.
The findings align with previous bioelectrochemical studies. Zhang et al. reported that increasing nitrate beyond 2000 mg/L reduced current generation, and Li et al. observed similar inhibition in anodic denitrification MFCs. Raychaudhuri and Behera, working with a ceramic separator MFC treating synthetic rice-mill wastewater, reported Han-Levenspiel and Edwards models as best fits with a critical inhibitory concentration similar to the current study. However, the present work systematically applies nine models and a statistically efficient multi-criteria framework, going beyond previous studies that used smaller subsets of inhibition models or relied entirely on R².
The authors acknowledge limitations. The simultaneous operation of 20 separate MFCs to map ten concentrations, while enabling wide-spectrum analysis, lacked biological and technical replicates, limiting proof of reproducibility. Future studies will prioritise smaller concentration ranges with triplicate reactors. The operating windows established here suit laboratory or pilot-scale reactors, but real-world effluents will add complexity, increasing internal resistance and altering charge transfer kinetics. Validation under real conditions is crucial for moving the technology from laboratory to industrial scale. Future work will also integrate real-time pH and volatile fatty acid monitoring, electrochemical impedance spectroscopy, microbial community sequencing, and long-term studies of biofilm aging and ceramic separator fouling to refine the kinetic constants and understand how extended operation affects performance.
Subject of Research: Kinetic modelling of substrate inhibition in ceramic-separator microbial fuel cells for wastewater treatment and bioelectricity production
Article Title: Development of a multi-criteria selection method of kinetic model for substrate inhibition in ceramic separator microbial fuel cells used for wastewater treatment and bioelectricity production
Article References: Bagchi, S., & Behera, M. (2026). Development of a multi-criteria selection method of kinetic model for substrate inhibition in ceramic separator microbial fuel cells used for wastewater treatment and bioelectricity production. Discover Electrochemistry, 3(1), Article 94. https://doi.org/10.1007/s44373-026-00182-7
Image Credits: AI Generated
DOI: 10.1007/s44373-026-00182-7
Keywords: microbial fuel cells, substrate inhibition, kinetic modelling, wastewater treatment, bioelectricity, ceramic separator, COD degradation, nitrate removal, model selection, operating windows, Development, multi-criteria
News Source: Victoria Harrison. (November 5, 2026). Microbial fuel cells get a statistical tune-up for cleaner wastewater and more power. Scienmag.
