journal article·2024-07-17

Particle Size-Tunable Polydopamine Nanoparticles for Optical and Electrochemical Imaging of Latent Fingerprints on Various Surfaces

Lu Liu, Hui Zhou, Hongyu Chen, Zhiming Wang, Rongliang Ma, Xin Du, Meiqin Zhang

ACS Applied Materials & Interfaces· Volume 16· Issue 28
Publisher page

Abstract

Powder dusting method is the most widely used approach due to its low cost, simplicity, minimal instrument dependence, and extensive applicability for developing latent fingerprints (LFPs). Herein, a novel optical and electrochemical dual-mode method for high-resolution LFP enhancement has been explored based on size-tunable polydopamine (PDA) nanoparticles (NPs) and scanning electrochemical microscopy (SECM). Dark PDAs rich in functional groups and negative charges can combine with the residues of LFPs on various surfaces with high sensitivity and selectivity to realize high-resolution visual fingerprint physical patterns on various porous and nonporous substrates with light color. However, optical visualization is not feasible for LFPs on dark or multicolored surfaces. Fortunately, based on the differences in electrochemical reactivity between ridges and furrows caused by the conductivity and reducibility of PDA powders, SECM can serve as a powerful supplement to optical methods to effectively overcome background color interference and distinctly display fingerprint patterns. Intriguingly, it is noteworthy that the binding amount and particle size of PDA powder significantly affected the optical and electrochemical visualization of LFPs: more powder binding amounts provided darker ridges in optical, and more surface reaction sites (larger powder binding mass at the same particle size or smaller particle size at the same mass) provided higher currents of ridges in electrochemical imaging. It demonstrates that the PDA powder as a dual-mode developer for LFPs offers a promising method for individual identification in forensics.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Forensic Fingerprint Detection Methods · Forensic and Genetic Research · Digital and Cyber Forensics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Beijing Key Laboratory for Bioengineering and Sensing Technology, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, P. R. China

Institute of Forensic Science, Ministry of Public Security, Beijing 100038, P. R. China

Funding

Beijing Municipal Science and Technology Commission, Adminitrative Commission of Zhongguancun Science Park · National Natural Science Foundation of China · Intelligent Policing Key Laboratory of Sichuan Province

References (49)

Show source-provided references
1. 10.1002/anie.20120381510.1002/anie.201203815 ↗
2. 10.1038/022605a010.1038/022605a0 ↗
3. 10.1002/adfm.20160624310.1002/adfm.201606243 ↗
4. 10.1039/C6AN01121G10.1039/C6AN01121G ↗
5. 10.1109/MC.2010.3810.1109/MC.2010.38 ↗
6. 10.1039/D2AN01940J10.1039/D2AN01940J ↗
7. 10.1109/TPAMI.2007.25059610.1109/TPAMI.2007.250596 ↗
8. 10.1039/D3AN00511A10.1039/D3AN00511A ↗
9. 10.1039/D1CC01910D10.1039/D1CC01910D ↗
10. 10.1002/slct.20220225210.1002/slct.202202252 ↗
11. 10.1021/acs.jchemed.9b0035710.1021/acs.jchemed.9b00357 ↗
12. 10.1016/j.electacta.2021.13879810.1016/j.electacta.2021.138798 ↗
13. 10.1002/anie.20080434810.1002/anie.200804348 ↗
14. 10.1111/1556-4029.1377310.1111/1556-4029.13773 ↗
15. 10.1039/C8RA03808B10.1039/C8RA03808B ↗
16. 10.1039/C7TC00852J10.1039/C7TC00852J ↗
17. 10.1016/j.forsciint.2016.07.02410.1016/j.forsciint.2016.07.024 ↗
18. 10.1021/acs.analchem.0c0422210.1021/acs.analchem.0c04222 ↗
19. 10.1016/j.ccr.2022.21452310.1016/j.ccr.2022.214523 ↗
20. 10.1021/acsami.7b0977410.1021/acsami.7b09774 ↗
21. 10.1016/j.ijbiomac.2022.01.03110.1016/j.ijbiomac.2022.01.031 ↗
22. 10.1039/c1nr10969c10.1039/c1nr10969c ↗
23. 10.1016/j.dyepig.2023.11159710.1016/j.dyepig.2023.111597 ↗
24. 10.1021/acsami.7b1561210.1021/acsami.7b15612 ↗
25. 10.1016/j.mtsust.2023.10062910.1016/j.mtsust.2023.100629 ↗
26. 10.1021/acsanm.1c0390110.1021/acsanm.1c03901 ↗
27. 10.1021/acsami.0c0197210.1021/acsami.0c01972 ↗
28. 10.1088/1361-6528/ab93ee10.1088/1361-6528/ab93ee ↗
29. 10.1016/j.ceramint.2022.03.04410.1016/j.ceramint.2022.03.044 ↗
30. 10.1016/j.snb.2018.03.08410.1016/j.snb.2018.03.084 ↗
31. 10.1021/acsanm.9b0089010.1021/acsanm.9b00890 ↗
32. 10.1016/j.trac.2021.11637810.1016/j.trac.2021.116378 ↗
33. 10.1021/jacs.0c0012410.1021/jacs.0c00124 ↗
34. 10.1021/acs.chemrev.6b0006710.1021/acs.chemrev.6b00067 ↗
35. 10.1039/b710947d10.1039/b710947d ↗
36. 10.1039/B815336A10.1039/B815336A ↗
37. 10.1002/elan.20110069410.1002/elan.201100694 ↗
38. 10.1016/j.electacta.2020.13637310.1016/j.electacta.2020.136373 ↗
39. 10.1021/acs.analchem.2c0342710.1021/acs.analchem.2c03427 ↗
40. 10.1016/j.electacta.2022.14050210.1016/j.electacta.2022.140502 ↗
41. 10.1016/j.jelechem.2023.11738710.1016/j.jelechem.2023.117387 ↗
42. 10.1002/adma.20190750510.1002/adma.201907505 ↗
43. 10.1002/smll.20220557610.1002/smll.202205576 ↗
44. 10.1002/adma.20120392310.1002/adma.201203923 ↗
45. 10.1016/j.jflm.2011.06.00510.1016/j.jflm.2011.06.005 ↗
46. 10.1039/D1AY01508G10.1039/D1AY01508G ↗
47. 10.1002/anie.20110431310.1002/anie.201104313 ↗
48. 10.1016/S0379-0738(00)00465-510.1016/S0379-0738(00)00465-5 ↗
49. 10.1039/D0AN01423K10.1039/D0AN01423K ↗