Impact of Aggregation-Induced Emission on Latent Fingerprint Revelation Based on Surface Energy Differences

lingjie Guo; Shuhui Gao

doi:10.3788/LOP231752

Laser & Optoelectronics Progress, Volume. 61, Issue 15, 1530004(2024)

Impact of Aggregation-Induced Emission on Latent Fingerprint Revelation Based on Surface Energy Differences

lingjie Guo¹ and Shuhui Gao^1,2、*

Author Affiliations

¹Beijing Key Laboratory of Forensic Science, People's Public Security University of China, Beijing 100038, China

²School of Investigation, People's Public Security University of China, Beijing 100038, China

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Abstract Get PDF(in Chinese)

Figures & Tables(10)

Fig. 1. Dissipation diagram of Jablonsk energy^[18]

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Fig. 2. AIE visualization revelation method, equipment, and revelation results. (a) Schematic diagram of the revelation method; (b) main equipment and accessories; (c) revelation results

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Fig. 3. The latent oil print revelation effect and average scores on metal surfaces and smooth surfaces (the left image shows the original appearance, and the right image shows the resulting manifestation). (a) Yellow can; (b) green can; (c) red can; (d) blue can; (e) stainless steel; (f) glass; (g) ceramic; (h) enamel; (i) ceramic tile

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Fig. 4. The latent sweat print revelation effect and average scores on metal surfaces and smooth surfaces (the left image shows the original appearance, and the right image shows the resulting manifestation). (a) Yellow can; (b) green can; (c) red can; (d) blue can; (e) stainless steel; (f) glass; (g) ceramic; (h) enamel; (i) ceramic tile

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Fig. 5. The latent oil print extraction effect and average scores on semi-glossy and non-glossy objects (the left image shows the original appearance, and the right image shows the resulting manifestation). (a) Plastic; (b) leather; (c) A4 paper; (d) natural wood; (e) cardboard; (f) cloth

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Fig. 6. The latent sweat print extraction effect and average scores on semi-glossy and non-glossy objects (the left image shows the original appearance, and the right image shows the resulting manifestation). (a) Plastic; (b) leather; (c) A4 paper; (d) natural wood; (e) cardboard; (f) cloth

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Fig. 7. Comparison of latent fingerprint average mass scores on various types of objects

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Table 1. Evaluation criteria for fingerprint^[27-28]

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Table 1. Evaluation criteria for fingerprint^[27-28]

Score	Level of detail
0	No evidence of mark
1	Weak development；evidence of contact but no ridge details
2	Limited development；about 1/3 of ridge details are present but probably（cannot be used for identification purposes）
3	Strong development；between 1/3 and 2/3 of ridge details（identifiable fingerprint）
4	Very strong development；full ridge details（identifiable fingerprint）

Table 2. The scoring table for latent fingerprints on various objects

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Table 2. The scoring table for latent fingerprints on various objects

Surface property	Trace carrier	Color	Oil fingerprint score	Sweat fingerprint score
Metal surface	Can	Yellow	3.57	3.27
		Green	3.07	1.85
		Red	2.13	1.53
		Blue	2.93	2.63
	Stainless steel	White	3.93	4.00
Smooth surface	Glass	Colorless	3.65	3.97
	Ceramic	White	2.63	2.93
	Enamel	Colorless	3.93	4.00
	Ceramic tiles	White	3.73	3.50
Semi-smooth surface	Plastic	Black	3.95	3.23
	Leather	White	3.38	2.73
	A4 paper	Yellow	3.55	1.05
	Genuine wood	Black	0.33	0.35
Rough surface	Cardboard	Yellow	2.07	0.63
Rough surface	Cloth	Black	0	0

Table 3. Surface energies of different substances^[31-32]

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Table 3. Surface energies of different substances^[31-32]

Type	Object	Surface energy /（mJ/m²）
Fingerprint substance	Water	72.8
Fingerprint substance	Oil	30‒40
Trace carrier	Al	30‒75
	Stainless steel	30‒150
	Glass	70‒300
	Ceramic	70‒150
	Enamel	70‒150
	Plastic	30‒35
	Leather	25‒50
	Paper	20‒40
	Genuine wood	20‒30
	Cloth	30‒40

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lingjie Guo, Shuhui Gao. Impact of Aggregation-Induced Emission on Latent Fingerprint Revelation Based on Surface Energy Differences[J]. Laser & Optoelectronics Progress, 2024, 61(15): 1530004

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