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Li DW, Zhang XF, Zhang XT, Lv XS, You N. Nanocomposites of nitrogen-doped carbon dots/hydrotalcite with enhanced solid-state fluorescence for the recognition of latent fingerprints. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:1297-1305. [PMID: 36804549 DOI: 10.1039/d2ay01952c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
In this work, a green emissive nanocomposite was synthesized by embedding nitrogen-doped carbon dots into hydrotalcite (N-CD/hydrotalcite) via a hydrothermal process for the recognition of latent fingerprints (LFPs). Good dispersion of the nano-sized N-CD on the surface of hydrotalcite overcomes the fluorescence quenching of N-CD in the solid state and can enhance solid-state fluorescence. N-CD/hydrotalcite emits stable strong green fluorescence even at different excitation wavelengths and exhibits good selectivity and sensitivity for the visualization of LFPs on various substrates such as glass slides, tiles, leather, aluminum foil, printing paper, colored surfaces of plastic packing, copper foil, planks, leaves, currencies, and bar codes. The high-level details of the ridge patterns of both fresh and aged LFPs can be clearly identified with good clarity and high contrast without background interferences under the excitation of a 450 nm light source. There is no significant difference in the LFP image visualized by N-CD/hydrotalcite and commercial fluorescent powders, indicating that the effectiveness of N-CD/hydrotalcite for the visualization of LFPs is equivalent to that of commercial fluorescent powders. These observations illustrate that N-CD/hydrotalcite has great potential in the recognition of LFPs.
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Affiliation(s)
- Da-Wu Li
- College of Forensic Science, Criminal Investigation Police University of China, Shenyang, Liaoning, 110035, China.
- Key Laboratory of Impression Evidence Examination and Identification Technology, Ministry of Public Security, Shenyang, Liaoning, 110035, China
| | - Xing-Fu Zhang
- College of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, 113001, China.
| | - Xiao-Tong Zhang
- College of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, 113001, China.
| | - Xiao-Sen Lv
- College of Forensic Science, Criminal Investigation Police University of China, Shenyang, Liaoning, 110035, China.
- Key Laboratory of Impression Evidence Examination and Identification Technology, Ministry of Public Security, Shenyang, Liaoning, 110035, China
| | - Nan You
- College of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, 113001, China.
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Chen H, Ma R, Zhang M. Recent Progress in Visualization and Analysis of Fingerprint Level 3 Features. ChemistryOpen 2022; 11:e202200091. [PMID: 35896949 PMCID: PMC9630047 DOI: 10.1002/open.202200091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/01/2022] [Indexed: 01/31/2023] Open
Abstract
Fingerprints provide sufficient and reliable discriminative characteristics which have been considered one of the most robust evidence for individualization. The limitation of current minutiae-based fingerprint technology seems to be solved with the development of level 3 features since they can offer additional information for problematic fingerprint recognition and even donor profiling. So far, tremendous efforts have been devoted to detecting and analysing the third-level details. This review summarizes the advances in level 3 details with an emphasis on their reliability assessment, visualization methods based on physical interaction, residue-response, mass spectrometry and electrochemical techniques, as well as the potentiality for individualization, donor profiling and even other application scenarios. In the end, we also give a personal perspective on the future direction and the remaining challenges in the third-level-detail-related field. We believe that the new exciting progress is expected in the development of level 3 detail detection and analysis with continued interest and attention to this field.
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Affiliation(s)
- Hongyu Chen
- Beijing Key Laboratory for Bioengineering and Sensing TechnologySchool of Chemistry and Biological EngineeringUniversity of Science and Technology Beijing30 Xueyuan RoadBeijing100083P.R. China
| | - Rongliang Ma
- Institute of Forensic ScienceMinistry of Public SecurityBeijing100038P. R. China
| | - Meiqin Zhang
- Beijing Key Laboratory for Bioengineering and Sensing TechnologySchool of Chemistry and Biological EngineeringUniversity of Science and Technology Beijing30 Xueyuan RoadBeijing100083P.R. China
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Gülekçi Y, Tülek A, Şener H, Küçüker H. Fingermark development on living and dead subjects: analysis of thermal paper transfers with different methods. AUST J FORENSIC SCI 2022. [DOI: 10.1080/00450618.2022.2117412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Affiliation(s)
- Yakup Gülekçi
- Department of Forensic Sciences, Faculty of Engineering and Natural Sciences, Kütahya University of Health Sciences, Kütahya, Turkey
| | - Ahmet Tülek
- Department of Bioengineering, Faculty of Engineering, Gebze Technical University, Kocaeli, Turkey
| | - Harun Şener
- Department of Forensic Sciences, Faculty of Engineering and Natural Sciences, Kütahya University of Health Sciences, Kütahya, Turkey
| | - Hüdaverdi Küçüker
- Department of Forensic Medicine, Faculty of Medicine, Kütahya University of Health Sciences, Kütahya, Turkey
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Colorimetric Visualization and SECM Imaging of Latent Fingerprints on Food Surfaces. Electrochim Acta 2022. [DOI: 10.1016/j.electacta.2022.140502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Shi M, Zhao L, Chen H, Tian L, Ma R, Zhang X, Zhang M. Fast and quantitative analysis of level 3 details for latent fingerprints. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2021; 13:5564-5572. [PMID: 34780584 DOI: 10.1039/d1ay01508g] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Level 3 details play essential roles in practical latent fingerprint (LFP) identification. To reliably extract reproducible and identifiable level 3 features, high-resolution images of fingerprints with adequate quality are required. Conventional methods for acquiring level 3 details often involve specific pretreatment, intricate peripheral, leading to time-consuming analysis. Herein, we simply used water to develop the sebaceous LFPs deposited on nitrocellulose (NC) membranes with only one step, and then the high-resolution (2048 pixels per inch) optical micrographs were captured to reflect the live fingertip with high fidelity. From the pictures, level 3 features, including all dimensional attributes of the ridges and pores such as number, size, location, shape, and edge contour can be extracted accurately and reproducibly. Among them, qualitative features (the structures of ridge edges) and several quantitative characteristics (the number and the relative location of sweat pores) exhibit good reproducibility. Remarkably, we proposed a new parameter termed "frequency distribution of the distance between adjacent sweat pores", short form "FDDasp", which was further proved highly identifiable in different individuals, enabling the successful distinguishment between two fragmentary fingerprints with similar level 2 structures. We believe that this methodology provides a fast and quantitative analytical paradigm for latent fingerprint identification at level 3 details.
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Affiliation(s)
- Mi Shi
- University of Science and Technology, Beijing School of Chemistry and Biological Engineering, China.
| | | | - Hongyu Chen
- University of Science and Technology, Beijing School of Chemistry and Biological Engineering, China.
| | - Lu Tian
- University of Science and Technology, Beijing School of Chemistry and Biological Engineering, China.
| | - Rongliang Ma
- Institute of Forensic Science, Ministry of Public Security, China.
| | - Xueji Zhang
- School of Biomedical Engineering, Health Science Centre, China.
| | - Meiqin Zhang
- University of Science and Technology, Beijing School of Chemistry and Biological Engineering, China.
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Abstract
Fingermarks have long been recognized as one of the most reliable and valuable evidence for personal identification. In practice, fingerprint analysis primarily concentrates on latent fingerprint visualization. However, fingerprint visualization techniques do not always enable individualization when fingermarks collected in crime scenes are fragmentary, ambiguous, or deformed. Age determination techniques based on physical and chemical composition changes in fingerprints over time have attracted researchers' attention in recent years. Nevertheless, the components of fingerprints are liable to factors including donor features, deposition conditions, substrate properties, environmental conditions and revealing methods. All the influences mainly contribute to unreliable outcomes of age estimation. Recent developments in fingermark age determination have moved forward to more precise approaches. The advanced methods can be classified into two categories including techniques based on the modifications of physical characteristics and chemical composition characteristics. Herein, the review includes the five types of variables that influence the aging process. The methodologies are subsequently highlighted along with their advantages and disadvantages. Furthermore, photography, optical, microscopy and electrochemical methods, and vibrational spectroscopy and mass spectrometry (MS) techniques are summarized in detail, with an emphasis on their utilization.
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Affiliation(s)
- Hongyu Chen
- Research Center for Bioengineering and Sensing Technology, Beijing Key Laboratory for Bioengineering and Sensing Technology, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China.
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Bécue A, Eldridge H, Champod C. Interpol review of fingermarks and other body impressions 2016-2019. Forensic Sci Int Synerg 2020; 2:442-480. [PMID: 33385142 PMCID: PMC7770454 DOI: 10.1016/j.fsisyn.2020.01.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 01/16/2020] [Indexed: 12/17/2022]
Abstract
This review paper covers the forensic-relevant literature in fingerprint and bodily impression sciences from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20 Review%20 Papers%202019. pdf.
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Affiliation(s)
- Andy Bécue
- École des Sciences Criminelles, Faculté de Droit, des Sciences criminelles et d’Administration publique, Quartier Sorge, Building Batochime, University of Lausanne, CH-1015, Lausanne, Dorigny, Switzerland
| | - Heidi Eldridge
- École des Sciences Criminelles, Faculté de Droit, des Sciences criminelles et d’Administration publique, Quartier Sorge, Building Batochime, University of Lausanne, CH-1015, Lausanne, Dorigny, Switzerland
| | - Christophe Champod
- École des Sciences Criminelles, Faculté de Droit, des Sciences criminelles et d’Administration publique, Quartier Sorge, Building Batochime, University of Lausanne, CH-1015, Lausanne, Dorigny, Switzerland
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A rapid and operator-safe powder approach for latent fingerprint detection using hydrophilic Fe3O4@SiO2-CdTe nanoparticles. Sci China Chem 2019. [DOI: 10.1007/s11426-019-9460-0] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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