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Updated: Oct 2, 2026

Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity
Published on: March 11, 2015
Microbiologically influenced corrosion in extreme environments caused by problematic microbial biofilms
Lingjun Xu1, Di Wang2, Adnan Khan3
1Department of Chemical and Biomolecular Engineering, Institute for Corrosion and Multiphase Technology, Ohio University, OH 45701, USA.
Abstract:
Microbiologically influenced corrosion (MIC) caused by microbial biofilms poses significant challenges to industrial systems. MIC and MIC mitigation cost billions of dollars each year in the US alone. Although most microbes flourish under mild conditions, increasing evidence demonstrates that in extreme environments such as high temperature, pressure, salinity, and low pH, extremophiles including thermophiles, barophiles, halophiles, and acidophiles can still form resilient biofilms and contribute to corrosion and biofouling. This review summarizes recent advances in understanding the formation, adaptation, and persistence of microbial biofilms in extreme environments and their roles in MIC. Key corrosion mechanisms such as extracellular electron transfer-MIC (EET-MIC) and metabolite-MIC (M-MIC) are discussed with environmental stressors and microbial physiology. Existing studies reveal that extreme environmental conditions do not necessarily suppress MIC, as extremophiles can adapt to environmental stresses and maintain corrosive activities. Different environmental stressors affect MIC through various pathways such as microbial metabolism and corrosion kinetics. Representative case studies highlight MIC behaviors under deep-sea, geothermal, hypersaline, and acidic conditions that are relevant to industrial operations. Current detection and monitoring approaches are evaluated along with mitigation strategies. The major limitation is that they are mostly developed and validated under mild conditions. Future work should focus on testing their reliability under extreme conditions. Emerging approaches including advanced corrosion resistant materials, bifunctional chemical inhibitors, and AI-assisted data integration are discussed as promising strategies for closing this gap as well as improving MIC prediction and mitigation under extreme conditions.
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