Lighvan, Vahid AshrafiArsalani, NasserGulcan, MehmetAytin, Rahel Yildirim2026-01-302026-01-3020260026-36721436-507310.1007/s00604-025-07804-82-s2.0-105027285041https://doi.org/10.1007/s00604-025-07804-8https://hdl.handle.net/20.500.14720/29648There is an urgent need for strategies that enable the rapid synthesis of long-wavelength fluorescent carbon dots (CDs). In forensic science, the development and analysis of latent fingerprints (LFPs) are vital for criminal investigations. This process involves two steps: enhancing LFP visualization for better detectability and using digital processing techniques for accurate database comparisons. Long-wavelength-emitting CDs can significantly improve LFP visualization by enhancing contrast and minimizing background interference. This study focuses on synthesizing dual green/red-emissive nitrogen and iron co-doped carbon dots (N, Fe-CD (green/red)) using microwave-assisted methods. These N, Fe-CD (green/red) were integrated into a plaster and starch composite, resulting in N, Fe-CD (green/red) @plaster-starch phosphors. The phosphors effectively enhanced LFP development through dusting techniques. Under blue/green light excitation, the emitted green/red fluorescence from the N, Fe-CD (green/red) significantly improved LFP visualization, proving their usefulness in forensic applications. Additionally, artificial intelligence (AI) algorithms were utilized to analyze fluorescence images of developed LFPs, achieving match scores exceeding 73.0%, which indicates a high similarity to control references. These findings highlight the AI algorithms' effectiveness in reliably identifying and comparing fingerprint features.eninfo:eu-repo/semantics/closedAccessLatent Fingerprints (LFPs)Fluorescence DetectionN, Fe-Cd (Green/Red)N, Fe-Cd (Green/Red) Plaster-Starch PhosphorsArtificial IntelligenceArticle