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In-situ impedance-based diagnostics for electrode degradation in vanadium redox flow batteriesстатья
Статья опубликована в высокорейтинговом журнале
Информация о цитировании статьи получена из
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 4 марта 2026 г.
- Авторы: Buriak N., Khristoforov I., Protasova S., Kondratenko M., Mozhchil R., Pugach M.
- Журнал: Journal of Power Sources
- Том: 665
- Год издания: 2026
- Издательство: Elsevier BV
- Местоположение издательства: Netherlands
- Номер статьи: 239062
- DOI: 10.1016/j.jpowsour.2025.239062
- Аннотация: The performance and lifetime of vanadium redox flow batteries (VRFBs) are strongly affected by the degradation of carbon felt electrodes, which increases internal losses and reduces efficiency. This work presents a diagnostic method based on electrochemical impedance spectroscopy (EIS) for monitoring electrode degradation under practical operating conditions. The approach enables full-cell EIS measurements across a wide current density range (0–500 mA cm− 2), allowing quantitative separation of activation and ohmic losses and their evolution as the electrodes deteriorate. Two carbon felts with distinct fiber morphologies were examined in pristine and oxidatively degraded states. The method’s validity was confirmed by X-ray photoelectron spectroscopy, which revealed degradation-induced changes in surface functional groups. The felt with rough fibers exhibited a twofold increase in positive-electrode charge-transfer resistance at zero load but maintained more stable kinetics at high currents, resulting in a significantly lower voltage loss (≈20 %) after degradation compared with the smooth-fiber felt. These findings demonstrate that the proposed EIS-based framework provides a practical tool for assessing electrode health, identifying kinetic vulnerabilities, and linking electrochemical losses to surface chemistry. The method offers valuable insights for optimizing electrode materials and improving predictive models of VRFB stack degradation in industrial energy-storage applications.
- Добавил в систему: Кондратенко Михаил Сергеевич
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