Abstract Silver nanoparticles (AgNPs) have garnered considerable attention due to their remarkable antimicrobial and biomedical properties. This review offers a comprehensive overview of AgNP synthesis methods, stability factors, toxicity concerns, and future research directions, including advancements driven by artificial intelligence (AI). Various synthesis approaches, including physical, chemical, electrochemical, photochemical, and biological methods, are explored, with particular emphasis on sustainable alternatives such as plant-based synthesis, as well as bacterial, fungal, and algal-mediated methods. Key factors influencing AgNP stability, such as size, shape, and surface modifications, are examined to assess their impact on functionality and overall performance. The biomedical applications of AgNPs, including their roles in antimicrobial treatments, wound healing, drug delivery, and cancer therapy, are reviewed alongside concerns about cytotoxicity and environmental implications. Nonetheless, we still have gaps in our understanding of the long-term biological impacts and our capacity to build consistent synthesis procedures. Challenges in AgNP synthesis, such as scalability, reproducibility, and controlled functionalization, are also discussed. Additionally, the integration of AI in AgNP research is highlighted, showcasing its potential in optimizing synthesis parameters, predicting stability, and enhancing material performance. This review aims to provide a thorough understanding of AgNP synthesis, stability, and biomedical applications while addressing toxicity issues and emphasizing the AI role in advancing nanoparticle research. This integration is a unique feature of the current article, as it has rarely been explored in previous studies. Finally, future perspectives and research directions are outlined to address existing challenges and drive further innovation in AgNP development with an emphasis on applying AI technology to overcome existing synthesis restrictions, improve repeatability, and promote intelligent AgNP-based medicinal platform design.
Hosny et al. (Sat,) studied this question.
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