Predictive Modeling and Bioinspired Strategies for Stabilizing Hydrophilic Perovskite Quantum Dots in Multiplexed Biomedical Diagnostics

Hydrophilic perovskite quantum dots (PQDs) have emerged as promising materials for biomedical diagnostics due to their exceptional optical tunability and high photoluminescence quantum yield. However, their instability, toxicity, and degradation in aqueous and biological environments remain critical barriers to practical applications. This review integrates predictive modeling and bioinspired stabilization strategies to provide a comprehensive understanding of the mechanisms governing PQD instability and the design of robust, biocompatible nanostructures. Multiscale computational approaches-including density functional theory, molecular dynamics, and machine learning-are analyzed to elucidate degradation pathways and forecast material performance under physiological conditions. In parallel, bioinspired and hybrid stabilization strategies, such as ligand engineering, polymer/silica encapsulations, and adaptive coating design, are critically evaluated for enhancing aqueous stability and biosafety. The stabilized PQDs are further discussed in multiplexed biomedical diagnostics, highlighting their potential for precision sensing of multiple biomarkers. This is the comprehensive review that bridges predictive modeling with bioinspired stabilization to advance hydrophilic PQDs toward intelligent and multiplexed diagnostic platforms.

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