Quantum dot-infused nanocomposites: revolutionizing diagnostic sensitivity

Abstract

Quantum dot-doped nanocomposites (QDNCs) represent an innovative breakthrough in diagnostic medicine, enabling ultra-sensitive and accurate detection at disease onset. Utilizing the size-tunable optical properties, high quantum yield, and photostability of quantum dots (QDs), these materials enable the highly sensitive identification of biomarkers at femtomolar concentrations in complex biological environments. The incorporation of QDs into nanocomposites enables them to achieve better diagnostic modes such as targeted delivery, signal amplification, and multifunctionality, with numerous applications in cancer diagnosis, infectious disease diagnosis, and real-time glucometry. Core–shell and hybrid architectures of advanced materials also enhance the stability and biocompatibility of the QDs. Surface functionalization enhancements and green synthesis approaches have alleviated the issues of toxicity and scalability, with the material now being fit for use in the clinical arena. Furthermore, the amalgamation of QDNCs with machine learning is promising for intelligent diagnostic tools capable of real-time analysis and personalized medicine. This review investigates the engineering of QDNCs, their transformative role in healthcare diagnostics, and their potential to revolutionize point-of-care devices. The capability to address significant translational challenges concerning biocompatibility, toxicity, and scalability will enable QD-based technologies to set a new standard for precision diagnostics, ushering in new advancements in global healthcare.

Graphical abstract: Quantum dot-infused nanocomposites: revolutionizing diagnostic sensitivity

Supplementary files

Article information

Article type
Review Article
Submitted
30 jan 2025
Accepted
09 jun 2025
First published
25 jun 2025

Nanoscale, 2025, Advance Article

Quantum dot-infused nanocomposites: revolutionizing diagnostic sensitivity

Z. Amiri, P. Taromi, K. Alavi, P. Ghahramani, W. C. Cho, M. Ramezani Farani and Y. S. Huh, Nanoscale, 2025, Advance Article , DOI: 10.1039/D5NR00440C

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