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Enhancing Blood Fingerprints with Multicolored Conjugated Polymers: A Fluorescent Strategy with Python-Based
Zimin Zhang1, Yuhao Zhang2, Xuelian Jiang1
1Chongqing Institutes of Higher Education Key Forensic Science Laboratory, Criminal Investigation School, Southwest University of Political Science and Law, Chongqing, 401120, China.
Journal of Fluorescence
|January 16, 2026
Summary
Novel fluorescent conjugated polymers enhance blood fingerprint detection. This cost-effective method offers high contrast and selectivity for forensic applications, surpassing traditional reagents.
Area of Science:
- Materials Science
- Forensic Science
- Polymer Chemistry
Background:
- Fluorescent conjugated polymers offer stability, biocompatibility, and tunable conductivity for advanced materials.
- These polymers are valuable in fabricating multifunctional materials due to their processability and optical properties.
Purpose of the Study:
- To synthesize and characterize novel fluorescent conjugated polymers for blood fingerprint enhancement.
- To evaluate the effectiveness of these polymers in visualizing latent and visible blood fingerprints on non-porous substrates.
Main Methods:
- Synthesis and characterization of three fluorescent conjugated polymers: PF-SO10 (blue), PF-SO10-BT1 (green), and PF-SO10-DTBT1 (red).
- Application of these polymers via powder dusting for blood fingerprint development.
- Visualization under 365 nm irradiation.
- Comparative analysis with conventional reagents like Amido Black 10B and TMB.
- Development of a Python-based quantitative evaluation framework.
Main Results:
- Developed fingerprints exhibited strong fluorescence under 365 nm irradiation, revealing third-level details on six non-porous substrates.
- The novel polymer method outperformed conventional reagents in fingerprint visualization.
- The Python framework provided quantitative metrics for objective assessment.
Conclusions:
- The fluorescent conjugated polymers provide a promising, low-cost, high-contrast, and selective method for blood fingerprint detection.
- This approach minimizes background interference, offering reliable visualization for forensic applications.
- The quantitative evaluation framework enhances objectivity in analyzing fingerprint quality.

