Emerging perovskite-based electrochemical biosensors for different biomarkers detection: innovations, applications, and future prospects.

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Title: Emerging perovskite-based electrochemical biosensors for different biomarkers detection: innovations, applications, and future prospects.
Authors: Dehghanipour, M.1 (AUTHOR) masooddehghanipoor@yahoo.com, Kumar, Anjan2 (AUTHOR), Al-hedrewy, Marwea3,4 (AUTHOR), Kanjariya, Prakash5 (AUTHOR), Rajiv, Asha6 (AUTHOR), Shankhyan, Aman7 (AUTHOR), Jayabalan, Karthikeyan8 (AUTHOR), Samal, Satish Kumar9 (AUTHOR)
Source: Microchimica Acta. Aug2025, Vol. 192 Issue 8, p1-20. 20p.
Abstract: Perovskite materials have emerged as highly promising candidates for electrochemical biosensors due to their excellent electrical conductivity, thermal and chemical stability, catalytic activity, and structural tunability. Recent advances in perovskite-based electrochemical biosensors have demonstrated sensitive and accurate detection of clinically relevant biomarkers, including cancer antigens, small molecules, and nucleic acids. The integration of perovskites enhances sensor performance by improving signal response and facilitating effective immobilization of biological receptors on electrode surfaces. Compared to conventional biomarker detection methods, these biosensors offer improved sensitivity, lower costs, and simplified protocols. This review presents a focused overview of perovskite types, synthesis methods, and their specific roles in electrochemical biosensor design. It further highlights recent innovations, addresses current challenges, and outlines future prospects for combining perovskites with emerging technologies to advance rapid, accurate biomarker detection. Continued development in this field holds significant potential for early diagnosis, disease monitoring, and personalized medicine. [ABSTRACT FROM AUTHOR]
Copyright of Microchimica Acta is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Emerging perovskite-based electrochemical biosensors for different biomarkers detection: innovations, applications, and future prospects.
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  Data: <searchLink fieldCode="JN" term="%22Microchimica+Acta%22">Microchimica Acta</searchLink>. Aug2025, Vol. 192 Issue 8, p1-20. 20p.
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  Data: Perovskite materials have emerged as highly promising candidates for electrochemical biosensors due to their excellent electrical conductivity, thermal and chemical stability, catalytic activity, and structural tunability. Recent advances in perovskite-based electrochemical biosensors have demonstrated sensitive and accurate detection of clinically relevant biomarkers, including cancer antigens, small molecules, and nucleic acids. The integration of perovskites enhances sensor performance by improving signal response and facilitating effective immobilization of biological receptors on electrode surfaces. Compared to conventional biomarker detection methods, these biosensors offer improved sensitivity, lower costs, and simplified protocols. This review presents a focused overview of perovskite types, synthesis methods, and their specific roles in electrochemical biosensor design. It further highlights recent innovations, addresses current challenges, and outlines future prospects for combining perovskites with emerging technologies to advance rapid, accurate biomarker detection. Continued development in this field holds significant potential for early diagnosis, disease monitoring, and personalized medicine. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Microchimica Acta is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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