Challenges in Operating a Microbial Electrolysis Cell (MEC): Translating Biofilm Activity to Electron Flow and Hydrogen

Microbial electrolysis cells (MECs) are bioreactors that utilize electroactive microorganisms to catalyze the oxidation of organic substrates in wastewater, generating electron flow for hydrogen production. Despite the concept, a persistent performance gap exists where metabolically active anodic biofilms frequently fail to achieve expected current densities by the flow of electrons to produce hydrogen. This review examines the multiple causes that lead to the disconnect between robust biofilm development, electron transfer, and hydrogen production. Factors affecting biofilm generation (formation, substrate selection, thickness, conductivity, and heterogeneity) are discussed. Moreover, factors affecting electron transfer (electrode configuration, mass transfer constraints, key electroactive species, and metabolic pathways) are discussed. Also, substrate diffusion limitations, proton accumulation causing inhibitory pH gradients in stratified biofilms, elevated internal resistance, electron diversion to competing processes like hydrogenotrophic methanogenesis consuming H 2 , and detrimental biofilm aging, impacting hydrogen production, are studied. The critical roles of electrode materials, reactor configuration, and biofilm electroactivity are analyzed, emphasizing advanced electrochemical (CV, EIS, LSV), imaging (CLSM, SEM, AFM), and omics (metagenomics, transcriptomics, proteomics) techniques essential for diagnosing bottlenecks. Strategies to enhance extracellular electron transfer (EET) (advanced nanomaterials, redox mediators, conductive polymers, bioaugmentation, and pulsed electrical operation) are evaluated for bridging this performance gap and improving energy recovery. The review presents an integrated framework connecting biofilm electroactivity, EET kinetics, and hydrogen evolution efficiency. It highlights that conventional biofilm metrics may not reflect actual electron flow. Combining electrochemical, microelectrode, and omics insights allows precise evaluation of EET efficiency and supports sustainable MEC optimization for enhanced hydrogen generation.