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A review on synthesis and studies on CoMn2O4/ nanocomposite (metal oxide/metal sulphide/carbon material) based electrodes in view of supercapacitor applications

  • Chitra Ravi ORCID logo , Saranya Amirtharajan ORCID logo , Esakki Muthu Sankaran and Prithivikumaran Natarajan ORCID logo EMAIL logo
Published/Copyright: November 14, 2025

Abstract

Binary metal oxide nanoparticles have huge attention nowadays because of their capability for use in energy saving systems. Typically, these compounds have an AxB3-xO4 structure, here A and B stands for two dissimilar metals such as Co, Ni, Mn, Fe, and Mo etc., This combination of metal cations (NiCo2O4, CoMn2O4, MnCo2O4, CoFe2O4, NiFe2O4, CoNi2O4,etc.) provides a wide range of redox reactions and intensify electronic conductivity, which upgrades the electrochemical performance. Binary transition metal oxides provide combined effect of the monometallic oxides, which can enhance conductivity, more active sites, stability and storage capacity. Among binary metal oxides, Cobalt Manganese Oxide (CoMn2O4) has outstanding capacitive performance as a result of greater tendency of cobalt to gain electrons and strong electron transport property of manganese. Due to these factors, researchers focus on cobalt manganese oxide-based supercapacitor electrodes. Hence a detailed and exhaustive review of works on CoMn2O4 and its composites as potential candidates for supercapacitor electrode materials is carried out in this article.


Corresponding author: Prithivikumaran Natarajan, PG and Research Department of Physics, Virudhunagar Hindu Nadars’ Senthikumara Nadar College(Autonomous), Virudhunagar, Tamil Nadu, India; and Affiliated to Madurai Kamaraj University, Madurai, Tamil Nadu, India, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Chitra Ravi: Conceptualization- Writing—Original Draft Preparation. Saranya Amirtharajan: Data analysis and interpretation – Writing—Review & Editing. Esakki muthu Sankaran: Investigation – Data Analysis – validation – Prithivikumaran Natarajan: Supervision – Writing— Review & Editing.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

  6. Research funding: None declared.

  7. Data availability: Data will be made available on request.

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Received: 2025-06-25
Accepted: 2025-10-15
Published Online: 2025-11-14

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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