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Redox flow batteries (RFBs) offer a promising pathway for scalable and long-duration energy storage. Among emerging chemistries, the iron–manganese (Fe/Mn) system stands out due to its low cost, environmental compatibility, and favorable redox potentials. Mathematical models for Iron–Manganese style redox flow batteries (RFBs) employ the same multi-scale electrochemical, transport and fluid-dynamic frameworks used across RFB research, but the existing literature shows few dedicated iron–manganese based RFBs studies. Major trends include pore-scale and continuum multi-physics, reduced-order stack models, and emerging physics-informed ML and topology-optimization tools. This chapter provides an extensive investigation of mathematical modeling approaches pertinent to iron–manganese (Fe-Mn) redox flow batteries, with a highlighting on the detailed explanation of electrochemical performance via computational design and optimization strategies. We explore foundational electrochemical principles, governing equations, and modeling methodologies that encompass the fluid dynamics, state of charge (SoC), impact of pressure, equations essential for measuring performance and multidimensional battery electrode simulations. The chapter also addresses critical challenges inherent in Fe-Mn systems, encompassing iron-manganese speciation stability, precipitation kinetics, and transport phenomena, while accentuating recent advancements in computational techniques and their applications for performance enhancement. Practical case studies illustrate the manner in which mathematical modeling informs electrode design, electrolyte formulation, and the selection of operational conditions to optimize energy efficiency and extend cycle life.

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Single-Cell Mathematical Modeling of an Iron–Manganese Redox Flow Battery for Enhanced Electrochemical Performance

  • 会议论文

  • 发表日期：

    2026年

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  • Mohammad Jakir Hossain Khan,
  • Audrius Senulis,
  • Zilvinas Kryzevicius,
  • Arturas Tadzijevas,
  • Jochen Uebe,
  • Reza Afshar Ghotli,
  • Barun Kumar Chakrabarti,
  • Yashar Hajimolana

摘要

Redox flow batteries (RFBs) offer a promising pathway for scalable and long-duration energy storage. Among emerging chemistries, the iron–manganese (Fe/Mn) system stands out due to its low cost, environmental compatibility, and favorable redox potentials. Mathematical models for Iron–Manganese style redox flow batteries (RFBs) employ the same multi-scale electrochemical, transport and fluid-dynamic frameworks used across RFB research, but the existing literature shows few dedicated iron–manganese based RFBs studies. Major trends include pore-scale and continuum multi-physics, reduced-order stack models, and emerging physics-informed ML and topology-optimization tools. This chapter provides an extensive investigation of mathematical modeling approaches pertinent to iron–manganese (Fe-Mn) redox flow batteries, with a highlighting on the detailed explanation of electrochemical performance via computational design and optimization strategies. We explore foundational electrochemical principles, governing equations, and modeling methodologies that encompass the fluid dynamics, state of charge (SoC), impact of pressure, equations essential for measuring performance and multidimensional battery electrode simulations. The chapter also addresses critical challenges inherent in Fe-Mn systems, encompassing iron-manganese speciation stability, precipitation kinetics, and transport phenomena, while accentuating recent advancements in computational techniques and their applications for performance enhancement. Practical case studies illustrate the manner in which mathematical modeling informs electrode design, electrolyte formulation, and the selection of operational conditions to optimize energy efficiency and extend cycle life.