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Graphene Quantum Dots as Advanced Carbon Nanomaterials: Controlled Synthetic Strategies and Multifunctional Biomedical Theranostic Applications

Sep 2026 · ChemistrySelect · 0 citations · 93 references

TL;DR

This work critically evaluates GQDs through a “synthesis–structure–property–biological function–translation” framework, covering bioimaging, biosensing, drug and gene delivery, and photothermal/photodynamic therapy, covering bioimaging, biosensing, drug and gene delivery, and photothermal/photodynamic therapy.

Abstract

Graphene quantum dots (GQDs) are emerging zero‐dimensional carbon nanomaterials with tunable optical, electronic, and surface properties, offering broad opportunities in biomedical theranostics. However, their translation is hindered by substantial heterogeneity in material identity and a disconnect between proof‐of‐concept performance and reproducible biological behavior. Here, we critically evaluate GQDs through a “synthesis–structure–property–biological function–translation” framework, covering bioimaging, biosensing, drug and gene delivery, and photothermal/photodynamic therapy. Top‐down and bottom‐up strategies are compared in terms of structural controllability, purification, reproducibility, and scalability, while the roles of size, edge chemistry, defects, heteroatom states, and surface functionalization in governing photoluminescence, reactive oxygen species generation, colloidal stability, and biological interactions are assessed. Current evidence indicates that high photoluminescence quantum yield, low toxicity, tumor targeting, and scalability are formulation‐ and process‐dependent rather than intrinsic properties of GQDs. Major barriers include poorly resolved synthesis–structure–function relationships, inconsistent purification and characterization, batch variability, and insufficient quantitative pharmacokinetic, biodistribution, and long‐term safety data. Advancing GQDs toward clinical use will require application‐specific material design, standardized critical quality attributes, orthogonal validation, and scalable quality‐by‐design manufacturing, shifting the field from isolated performance optimization toward reproducible, clinically meaningful benefit–risk profiles.

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