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Turkish Journal of Biology

Abstract

Background/aim: Green carbon dots (GCDs) are a rapidly developing class of nanomaterials that are revolutionizing various scientific disciplines due to their unique optical properties, low toxicity, and sustainable synthesis. This review offers a comprehensive roadmap for the field, emphasizing the synergy between GCDs and artificial intelligence (AI).

Materials and methods: We begin by detailing the sustainable synthesis of GCDs, highlighting green chemistry principles and the transformative role of AI in optimizing their production. Subsequently, we explore the critical characterization of GCDs, including their structural, optical, and biocompatibility assessment. The core of this study explores the diverse biomedical applications of GCDs, including their integration into intelligent drug delivery systems enhanced by AI, utility in advanced diagnostics and biosensing, and contribution to state-of-the-art bioimaging techniques by deep learning (DL).

Results: Analysis of the literature confirms that AI-driven optimization is crucial for enhancing the scalability and reproducibility of GCD production. Furthermore, the integration of DL models significantly boosts the analytical precision and real-time capabilities of these platforms, validating the profound convergence of the fields.

Conclusion: This review provides a holistic roadmap, concluding that the AI– GCD synergy is indispensable for developing the next generation of smart nanomedicines. Future efforts must prioritize addressing scalability, standardization, and regulatory pathways to accelerate successful clinical translation.

Author ORCID Identifier

EMİNE SEZER: 0000-0003-4776-6436

FULDEN ULUCAN KARNAK: 0000-0001-5567-0261

SİNAN AKGÖL: 0000-0002-8528-1854

DOI

10.55730/1300-0152.2762

Keywords

Green carbon dots, artificial intelligence, machine learning, deep learning, drug delivery, diagnostics

First Page

498

Last Page

533

Publisher

The Scientific and Technological Research Council of Türkiye (TÜBİTAK)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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