Forensic Differentiation of Automotive Coatings with Multiple Spectroscopic Methods: Comprehensive Spectral Information Analysis for More Accurate Identification

Keywords: Fourier transform infrared microscope; Raman; scanning electron microscope energy dispersive spectrometer; coating; automotive coatings; automotive paint; forensic automotive paint analysis

Abstract

To minimize judgment errors, it is essential to employ diverse analytical methods to evaluate the same evidence, especially when the suspected objects share similar chemical structures. In this study, three-layered complex coatings, relevant to forensic analysis of automotive coatings involved in a hit-and-run case, were investigated using Fourier transform infrared (FT-IR) spectroscopy to determine their organic compositions. The functional groups and organic structures of the coating samples were discussed. Thorough investigations were conducted on subtle, yet distinctive spectroscopic peaks of two commonly used paints: alkyd amino paint and acrylic amino paint, utilized in the first and second layers of the coatings in this case. Key differences in third-layer coatings of the samples were also identified. A portable Raman spectroscope provided complementary data to reinforce FT-IR findings. Additionally, elemental composition analysis using a scanning electron microscope combined with energy dispersive X-ray spectrometer (SEM-EDS) produced results consistent with spectroscopic analyses. Through comprehensive instrumental analysis, the suspect was excluded, leading to the successful apprehension of the offender. The findings from this case highlight that employing multiple scientific methods delivers more precise and reliable outcomes in real-world forensic investigations.

Introduction

As early as 1910, French criminologist Dr. Edmond Locard astutely asserted that "every contact leaves a trace," underscoring the critical importance of trace evidence in investigations and identification processes.¹ In accordance with homeland security mandates, the United States manages a substantial volume of CBRNE materials (chemicals, biological samples, radiological substances, nuclear materials, and explosives), necessitating robust detection measures for these threats. To address these challenges, specialized departments dedicated to trace evidence analysis have become indispensable. The FBI established a specialized "Trace Evidence Unit," highlighting the essential role of trace evidence in criminal investigations.² Trace evidence analysis, an emerging discipline within forensic science, was first introduced in China during the 1970s. Initially focusing on the testing of oil residues, gunshot residues, and explosive residues, the field experienced substantial advancements by the early 1980s, leading to the establishment of dedicated institutions for trace evidence analysis.³ Over the past four decades, China's trace evidence testing has evolved from its formative stage into a comprehensive discipline with distinct theories, techniques, and methodologies. Today, it holds a pivotal place in the nation's forensic science landscape.^4,5

Paint, also known as coating, is a solid film applied to the surface of an object through various construction techniques, resulting in a firmly adhered, durable, and continuous layer.^6,7 This layer is referred to as a coating film or a paint film. As organic chemical polymer materials, coatings fall under the category of polymer compounds. According to the modern classification of chemical products, coatings are categorized as fine chemicals. In the contemporary chemical industry, modern coatings have evolved into multifunctional engineering materials.^8,9 Coatings possess properties that resist corrosion, water, oil, chemicals, light, and temperature fluctuations. Objects exposed to atmospheric conditions are susceptible to erosion caused by oxygen, moisture, and other factors, leading to adverse effects such as metal corrosion, wood decay, and cement weathering. The application of a protective paint film to an object's surface can prevent or slow the onset and progression of these destructive phenomena, thereby extending the lifespan of various materials. Protection is one of the main functions of coatings. Additionally, coatings can enhance objects by providing color, luster, pattern, and smoothness.^10,11

Coatings typically comprise two components when manufactured directly in the factory: non-volatile components and volatile components. The volatile components, known as diluents, gradually evaporate after the coating is applied to a surface. This evaporation causes the non-volatile components, referred to as solids, to dry and form a film. Film-forming substances are categorized into three types: primary film-forming substances, secondary film-forming substances, and auxiliary film-forming substances.¹²

In forensic science, paint is a vital form of trace evidence. In numerous traffic accident cases, comparing samples left at the scene or scraped off surfaces with those from a suspected vehicle often helps quickly eliminate or confirm the suspected vehicle.^13,14 According to China's national standard for the classification and nomenclature of coating products, coatings are divided into two main categories: architectural coatings and other coatings. The "Other coatings" category further includes 16 subcategories, approximately eight of which are widely used in automotive applications.¹⁵

Paint smears represent a challenging type of automotive paint sample for forensic examiners to analyze, as no reference materials exist in automotive paint databases to generate hit lists of potential suspect vehicles. The spectral analysis of paints, which consist of organic compounds, fillers, and pigments, further complicates the process. Comprehensive research is required to identify characteristic spectral peaks, differentiate samples based on these peaks, and accurately attribute the peaks to specific chemical structures, given their complex compositions.^16–18 Raman spectroscopy offers complementary insights by detecting molecular vibrations that may be inactive in the infrared region. Its sensitivity to pigments and inorganic fillers proves invaluable when infrared spectra lack distinct features due to pigment interference.

A portable Raman spectroscope enables efficient on-site analysis by targeting small areas of interest, capturing Raman shift signals, referencing a spectral library, and delivering detection results within minutes. Despite limited application of portable Raman spectroscopy in paint analysis, as highlighted by previous studies, its exceptional portability has proven to play a significant complementary role in distinguishing samples in this research.^19,20

The analysis of paints has long posed a challenge, necessitating the use of multiple devices and techniques to accurately characterize them and minimize risks associated with judgment errors.^21,22 In this study, we highlight the unique advantages of integrating FT-IR, Raman, and EDS spectroscopy for forensic paint analysis. This tri-modal approach delivers complementary insights into chemical structures (FT-IR), molecular vibrations (Raman), and elemental composition (EDS), enabling more precise and comprehensive "chemical fingerprint" identification of trace and complex samples. By addressing the limitations of single-technique methodologies, this strategy significantly enhances the discriminatory power and evidential reliability of analytical results. Particularly noteworthy is the utilization of portable Raman spectroscopy, which facilitates rapid, field-ready analysis while augmenting infrared spectroscopy data. The cross-verification capability provided by the complementary datasets within this multi-technique framework (FT-IR-Raman-EDS) markedly bolsters the forensic reliability of analytical conclusions, representing a major advancement over current single-method approaches.

Materials and Methods

All paint specimens were collected from a hit-and-run traffic accident case. Scene sample: A silver paint fragment (5 cm × 5 cm) scraped from the lower front-right corner of the bumper of the impacted vehicle. Suspect sample 1: A silver paint fragment (5 cm × 5 cm) collected from the left-side rocker panel of suspect vehicle 1. Suspect sample 2: A silver paint fragment (5 cm × 5 cm) obtained from the left front door of suspect vehicle 2.

A systematic layer-by-layer separation was meticulously conducted on all three samples (including both scene and suspect samples) under 50× magnification microscopy. Micro-flakes were extracted from each coating layer using a surgical lancet meticulously rinsed with acetone and deionized water to prevent cross-contamination. All samples exhibited a three-layer structure with comparable color and transparency characteristics across corresponding layers. The isolated micro-flakes were directly subjected to spectroscopic analysis.

A segment of the sample was excised using a surgical blade for FT-IR and SEM-EDS analyses. For Raman analysis, the equipment was directly focused on the sample surface for testing. FT-IR spectroscopy was performed in transmission mode using a PerkinElmer Spotlight 200i system equipped with both mercury cadmium telluride (MCT) and deuterated triglycine sulfate (DTGS) detectors. The spectral range spanned 400–4000 cm^-1, with a resolution of 4 cm^-1. Background subtraction was applied prior to each measurement. Raman spectroscopy was conducted using a Jianzheng portable Raman system with 785 nm laser excitation. The spectral range was 100–4000 cm^-1, and the laser power was 1–5%. Instrument calibration was performed before each analysis, and spectra were collected using specialized workstation software.

EDS microanalysis was performed using an Oxford X-MAX detector coupled to an FEI Quanta 600 SEM operating in high vacuum mode with a secondary electron detector. The operational parameters were as follows: working distance of 10 mm, accelerating voltage of 20 kV, acquisition time of 100 seconds, and a probe size of 5.0–7.0 µm.

Results and Discussion

FT-IR

All three paint samples consisted of three distinct layers, as shown in the microscope image in Figure 1. The first layers were transparent, the second layers were silver, and the third layers were white. Microscopic observation alone was insufficient to differentiate the samples. Figure 1 presents the infrared (IR) spectra of the first and the second layers across all three paint samples. The first and the second layers exhibited identical IR spectra. Spectral analysis revealed that the first layer was acrylic amino paint, while the second layer was alkyd amino paint. The two types of paints displayed similarity in Figure 1.

Figure 1. The IR spectra of the (a) first and (b) second layers of the three paint samples.

Figure 2 illustrates the chain chemical structures of the first and second layers of the paint samples (alkyd amino paint and acrylic amino paint). A coating composed of amino resin as a crosslinking agent, combined with polymer-based resins such as alkyd resin, acrylic resin, polyester resin, or epoxy resin, is referred to as amino resin paint or simply amino paint. Amino resins are thermosetting polymers synthesized through a condensation reaction between amino-functional compounds (for example, melamine) and aldehydes (primarily formaldehyde). Melamine-formaldehyde resin is a prominent example. Due to their high hydroxyl content, amino resins are insoluble in organic solvents and require modification with alcohols (usually n-butanol) to form etherified amino resins. These modified resins exhibit solubility in organic solvents and good compatibility with matrix resins like alkyd and acrylic resins. The etherification of hydroxymethyl melamine resin with n-butanol produces n-butanol-etherified methoxy melamine amino resin.

The coating film obtained by heating and curing amino resin alone is hard and brittle, with poor adhesion, making it unsuitable as a standalone coating. Consequently, amino resins are often combined with matrix resins such as alkyd, polyester, epoxy, or acrylic resins to produce amino paints. When used as a crosslinking agent in paint, amino resin enhances the hardness, gloss, chemical resistance, and drying speed of the matrix resin. Simultaneously, the matrix resin compensates for the inherent brittleness of the amino resin and improves adhesion.

Traditionally, "amino paint" refers to alkyd amino paint, which is composed of amino resin as the crosslinking agent and alkyd resin as the matrix resin. Similarly, "thermosetting acrylic paint" or "acrylic paint" denotes acrylic amino paint, consisting of amino resin as the crosslinking agent and acrylic resin as the matrix resin. Amino resin is mainly used in combination with alkyd resin to produce amino baking paint and with acrylic resin to make thermosetting acrylic paint (Figure 2). The presence of amino resin chains can be detected in both types of paints, explaining the similarities observed in their IR spectra.

Figure 2. The chain chemical structures of the first and second layers of the three paint samples (acrylic amino paint and alkyd amino paint).

The first layer of the acrylic amino paint showed a spectrum composed of signals from both acrylic resin and amino resin. Specifically, the spectral bands of acrylic resin include the stretching vibration of OH at around 3404 cm^-1, the stretching vibrations of CH₃ and CH₂ at 2958 cm^-1 and 2873 cm^-1, respectively; and the stretching vibration of C=O at 1731 cm^-1. Additionally, 1237 cm^-1 and 1163 cm^-1 represent the antisymmetric and symmetric stretching vibrations of C-O-C, respectively. In contrast, the spectral band of amino resin (alkoxylated melamine) includes a characteristic peak at 1552 cm^-1 corresponding to the C=N stretching vibration in the triazine ring structure—an indicative feature specific to the triazine ring and amino resin derived from melamine raw material. The absorption bands at 1493 cm^-1 and 1453 cm^-1 correspond to the superimposed antisymmetric angular displacement vibration of CH₃ and the in-plane angular displacement vibration of CH₂. The band at 1376 cm^-1 signifies the out-of-plane oscillation of CH₂. Additionally, a characteristic spectral band of the triazine ring is detected at 815 cm^-1, coexisting with the signature spectral band at 1552 cm^-1, further confirming the presence of amino resin from melamine.²³ More detailed assignments of the acrylic amino paint are listed in Table 1.

Table 1. Detailed assignment of the acrylic amino paint

The absorption peaks at 2931 cm^-1, 1553 cm^-1, 1490 cm^-1, and 815 cm^-1 in the second layer of the alkyd amino paint correspond to the absorption of n-butanol-etherified melamine-formaldehyde resin, which aligns with acrylic amino paints. However, the peaks at 3075 cm^-1, 1730 cm^-1, 1365 cm^-1, 1262 cm^-1, 1122 cm^-1, and 648 cm^-1 can be attributed to the absorption of alkyd resin and serve as distinguishing factors between these two types of paints. The characteristic spectral bands of alkyd amino paint are also mainly at 1553 cm^-1 and 815 cm^-1 , similar to acrylic amino paints. However, additional characteristic spectral bands, including 743 cm^-1, 706 cm^-1, 1262 cm^-1, 1122 cm^-1, and 1069 cm^-1 can provide further discrimination. In this study, noticeable differences at 761 cm^-1 and 743 cm^-1 were observed, enabling precise identification of the paint samples.

To identify the specific vehicle involved in the accident, the third layers of paint samples were thoroughly analyzed. Figure 3 displays the IR spectra of the third layer from the "scene sample" and "suspect sample 1." The IR spectrum indicated the presence of epoxy polyester paint containing TiO₂ and BaSO₄. Characteristic peaks corresponding to epoxy resin (Figure 3A) were observed, including benzene ring stretching vibration at 1607 cm^-1 and 1510 cm^-1, as well as out-of-plane angular vibrations of adjacent =CH groups on the para-substituted benzene ring at 1184 cm^-1, 915 cm^-1 and 830 cm^-1. Additionally, TiO₂ exhibited an intense absorption peak at 818 cm^-1 (Figure 3B). Polyester paint displayed characteristic peaks at 1409 cm^-1, 1103 cm^-1, 1020 cm^-1, 874 cm^-1, and a prominent peak at 730 cm^-1, which corresponds to out-of-plane angular vibrations of two adjacent CH groups on a para-substituted benzene ring (Figure 3C). BaSO₄ exhibited broad and strong absorption around 1025–1210 cm^-1, attributed to SO₄^2- antisymmetric stretching vibration, while its antisymmetric angular vibration was noted between 580 cm^-1 and 640 cm^-1. Weak but sharp absorption appeared around 960–1030 cm^-1, corresponding to the symmetric stretching vibration of SO₄^2-, with a specific peak for BaSO₄ observed at 984 cm^-1 (Figure 3D). The IR spectra of the third layer of the "scene sample" and the "suspect sample 1" clearly comprise contributions from the four mentioned substances, confirming that the third layer contains these components. Consequently, the paint types of the two samples were definitively identified.

Figure 3. The IR spectra of the third layer of the "scene sample" and "suspect sample 1" (Epoxy polyester paint with TiO₂ and BaSO₄).

The IR spectra of the third layer of the "suspect sample 2" revealed the presence of alkyd amino paint containing TiO₂ and BaSO₄. The chain chemical structure and the IR peak assignments for alkyd amino paint are illustrated in Figures 1 and 2, respectively. IR spectra of BaSO₄ and TiO₂ can be found in Figure 3. A comparison between Figures 3 and 4 confirmed that "suspect sample 2" could be excluded from further consideration based on FT-IR analysis.

Figure 4. The IR spectra of the third layer of the "suspect sample 2" (Alkyd amino paint with TiO₂ and BaSO₄).

Portable Raman Spectroscopy

The portable Raman spectroscope is mainly designed for identifying and confirming substance compositions, as well as rapid classification, qualitative and quantitative analysis of petroleum products. It also supports on-site analysis and research in geological exploration. The instrument features a simple structure and user-friendly operation and delivers fast, efficient, and accurate measurements. Renowned for its high-speed performance and measurement accuracy, it utilizes a confocal optical path design to enhance resolution, enabling micro-area detection at the micrometer level on sample surfaces. Additionally, it functions as a tool for microscopic image measurement, effectively serving as a compact, mobile laboratory.^24,25

The results of Raman spectroscopy complement those of infrared spectroscopy, offering comprehensive insights into molecular vibrations and structural information, while addressing several limitations inherent to infrared spectroscopy. In this study, Raman spectroscopy was further utilized to verify the FT-IR findings. Figure 5 presents the Raman spectra of the third layers of all three paint samples. The intensity and shape of peaks at 800–900 cm^-1 and 900–1000 cm^-1 were similar between the "scene sample" and "suspect sample 1," whereas these peaks were absent in "suspect sample 2." These findings were consistent with the results obtained from the infrared spectra.

Figure 5. The Raman spectra of the third layer of the three paint samples. (A) Scene sample. (B) Suspect sample 1. (C) Suspect sample 2.

SEM-EDS

Energy dispersive X-ray spectroscopy (EDS) is among the most widely utilized techniques in scanning electron microscopy (SEM). Most SEM instruments are equipped with energy spectrometers, allowing researchers to perform micro-area compositional analysis of samples. The unique characteristic energies of X-rays corresponding to different elements can be detected by energy spectrometers, enabling qualitative or quantitative analysis of the composition of micro-domains.^26,27

The samples were meticulously peeled off layer by layer with a surgical blade, and a portion was cut for further analysis. The obtained samples were then affixed to the conductive adhesive of the sample stage and inserted into the vacuum chamber's sample holder for detailed examination. Figure 6 shows the SEM-EDS results of the third layer from the three paint samples. The third layers of the "scene sample" and "suspect sample 1" contained elements such as C, O, Ti, S, Si, Al, Mg, and Ba. In contrast, the third layer of the "suspect sample 2" revealed only C, O, Ti, Al, and Si, with Mg notably absent. The SEM-EDS results confirmed that the "scene sample" and "suspect sample 1" had similar chemical compositions, whereas "suspect sample 2" displayed no such resemblance. These findings also aligned closely with the spectroscopic analysis.

Figure 6. (a)–(c) SEM-EDS results of the third layer of the three paint samples. (a) Scene sample. (b) Suspect sample 1. (c) Suspect sample 2.

Conclusion

The infrared and Raman spectra offer comprehensive molecular information for material analysis in forensic applications. SEM-EDS, an effective tool for surface composition analysis, further identifies the elemental composition of substances. The integration of the three methods enables more comprehensive and accurate characterization of evidence materials, thereby reducing misidentification and case-handling risks. In this study, three methods effectively differentiated organic components, fillers, pigments, and other inorganic components in various paints. Mutual verification and complementary data enhanced the reliability of the evidence. Additionally, the study provided a detailed analysis of four of the eight widely used vehicle coatings, including an in-depth examination of their chemical structures and spectral peaks. The characteristic peaks of these coatings were summarized, offering critical foundational data for coating analysis in real-world cases. Portable Raman spectroscopy, a promising tool for rapid on-site detection, was successfully applied in this research, paving the way for innovative approaches in similar applications.

References

1. Champod, C. Edmond Locard—Numerical Standards and “Probable” Identifications. J. Forensic Identif. 1995, 45 (2), 136–163.
2. Bécue, A.; Champod, C. Interpol Review of Fingermarks and Other Body Impressions 2019–2022. Forensic Sci. Int.: Synergy 2023, 6, 100304. DOI: https://doi.org/10.1016/j.fsisyn.2022.100304
3. He, Z. N. Application of Trace Evidence in Forensic Medical Examination. J. Forensic Sci. 1989, 34 (2), 391–398. DOI: https://doi.org/10.1520/JFS12649J
4. Guo, H. L.; Qiao, T.; Song, X. J., et al. Application of Inductively Coupled Plasma Mass Spectrometry in Trace Evidence Examination. Forensic Science and Technology 2016, No. 6, 470–475.
5. Zhang, Z. X.; Wang, J.; Lu, X.; Wang, H. M. Recent Progress in the Application of Chemical Attribution in Forensic Profiles. Forensic Chem. 2024, 37, 100556. DOI: https://doi.org/10.1016/j.forc.2024.100556
6. Bernhard, W. R. Paint and Tape: Collection and Storage of Microtraces of Paint in Adhesive Tape. J. Forensic Sci. 2000, 45 (6), 1312–1315. DOI: https://doi.org/10.1520/JFS14886J
7. Kruglak, K. J.; Dubnicka, M.; Kammrath, B.; Maxwell, V.; Reffner, J. A. The Evidentiary Significance of Automotive Paint from the Northeast: A Study of Red Paint. J. Forensic Sci. 2019, 64 (5), 1345–1358. DOI: https://doi.org/10.1111/1556-4029.14007
8. Jost, C.; Muehlethaler, C.; Massonnet, G. Forensic Aspects of the Weathering and Ageing of Spray Paints. Forensic Sci. Int. 2016, 258, 32–40. DOI: https://doi.org/10.1016/j.forsciint.2015.11.001
9. Quevillon, S.; Toupin, N.; Tremblay, A.; Fournier, R.; Muehlethaler, C. Batch-to-Batch Variation in Domestic Paints: Insights into the Newly Commercialized Recycled Paints. Forensic Sci. Int. 2019, 303, 109946. DOI: https://doi.org/10.1016/j.forsciint.2019.109946
10. Huang, L.; Beauchemin, D. Forensic Analysis of Automotive Paint Chips for the Identification of the Vehicle Manufacturer, Colour, and Year of Production Using Electrothermal Vaporization Coupled to Inductively Coupled Plasma Optical Emission Spectrometry. J. Anal. At. Spectrom. 2017, 32 (8), 1601–1607. DOI: https://doi.org/10.1039/C7JA00196G
11. Lavine, B. K.; White, C. G.; Ding, T. Library Search Prefilters for Vehicle Manufacturers to Assist in the Forensic Examination of Automotive Paints. Appl. Spectrosc. 2018, 72 (3), 476–488. DOI: https://doi.org/10.1177/0003702817737787
12. Fasasi, A.; Mirjankar, N.; Stoian, R.-I., et al. Pattern Recognition-Assisted Infrared Library Searching of Automotive Clear Coats. Appl. Spectrosc. 2015, 69 (1), 84–94. DOI: https://doi.org/10.1366/14-07578
13. Castle, D. A. Pigment Analysis in the Forensic Examination of Paints. II. Analysis of Motor Vehicle Paint Pigments by Chemical Tests. J. Forensic Sci. Soc. 1982, 22 (2), 179–186. DOI: https://doi.org/10.1016/S0015-7368(82)71468-9
14. Hu, C.; Zhu, J.; Mei, H., et al. The Transfer and Change of Paints in a Hit-and-Run Motor Vehicle Accident. J. Forensic Sci. Med. 2024, 10 (1), 24–27. DOI: https://doi.org/10.4103/jfsm.jfsm_90_22
15. China National Standard. Classification and Nomenclature for Coating Products; GB/T 2705-2000; Beijing, China, 2000.
16. Lambert, D.; Muehlethaler, C.; Esseiva, P.; Massonnet, G. Combining Spectroscopic Data in the Forensic Analysis of Paint: Application of a Multiblock Technique as a Chemometric Tool. Forensic Sci. Int. 2016, 263, 39–47. DOI: https://doi.org/10.1016/j.forsciint.2016.03.049
17. Ferreira, K. B.; Oliveira, A. G. G.; Gonçalves, A. S.; Gomes, J. A. Evaluation of Hyperspectral Imaging Visible/Near Infrared Spectroscopy as a Forensic Tool for Automotive Paint Distinction. Forensic Chem. 2017, 5, 46–52. DOI: https://doi.org/10.1016/j.forc.2017.06.001
18. Duarte, J. M.; Sales, N. G. S.; Braga, J. W. B., et al. Discrimination of White Automotive Paint Samples Using ATR-FT-IR and PLS-DA for Forensic Purposes. Talanta 2022, 240, 123154. DOI: https://doi.org/10.1016/j.talanta.2021.123154
19. Lv, J. G.; Zhang, W.; Liu, S., et al. Analysis of 52 Automotive Coating Samples for Forensic Purposes with Fourier Transform Infrared Spectroscopy (FT-IR) and Raman Microscopy. Environ. Forensics 2016, 17 (1), 59–67. DOI: https://doi.org/10.1080/15275922.2015.1091403
20. Merk, V.; Werncke, W.; Pfeifer, L. Cross-Section Measurements of Multilayer Automotive Paint Samples Using Combined Raman Spectroscopy and LIBS. Analyst 2022, 147 (23), 5470–5476. DOI: https://doi.org/10.1039/D2AN01474B
21. Germinario, G.; van der Werf, I. D.; Sabbatini, L. Chemical Characterisation of Spray Paints by a Multi-Analytical (Py/GC-MS, FT-IR, μ-Raman) Approach. Microchem. J. 2016, 124, 929–939. DOI: https://doi.org/10.1016/j.microc.2015.04.016
22. Malek, M. A.; Nakazawa, T.; Kang, H.-W.; Tsuji, K.; Ro, C.-U. Multi-Modal Compositional Analysis of Layered Paint Chips of Automobiles by the Combined Application of ATR-FT-IR Imaging, Raman Microspectrometry, and SEM/EDX. Molecules 2019, 24 (7), 1381. DOI: https://doi.org/10.3390/molecules24071381
23. Feng, J. M. Application of Infrared Spectrometry in Trace Evidence; Chemistry Industry Press: Beijing, China, 2009.
24. Conti, C.; Botteon, A.; Bertasa, M., et al. Portable Sequentially Shifted Excitation Raman Spectroscopy as an Innovative Tool for In Situ Chemical Interrogation of Painted Surfaces. Analyst 2016, 141 (15), 4599–4607. DOI: https://doi.org/10.1039/C6AN00753H
25. Botteon, A.; Colombo, C.; Realini, M., et al. Non-Invasive and In Situ Investigation of Layers Sequence in Panel Paintings by Portable Micro-Spatially Offset Raman Spectroscopy. J. Raman Spectrosc. 2020, 51 (10), 2016–2021. DOI: https://doi.org/10.1002/jrs.5939
26. Chen, R.; Lv, J. G.; Feng, J. M. Characterization of Paint by Fourier-Transform Infrared Spectroscopy, Raman Microscopy, and Scanning Electron Microscopy–Energy Dispersive X-ray Spectroscopy. Anal. Lett. 2015, 48 (9), 1502–1510. DOI: https://doi.org/10.1080/00032719.2014.984190
27. Aguilar-Rodríguez, P.; Zetina, S.; Mejía-González, A.; Esturau-Escofet, N. Microanalytical Characterization of an Innovative Modern Mural Painting Technique by SEM-EDS, NMR, and Micro-ATR-FT-IR among Others. Molecules 2023, 28 (2), 564. DOI: https://doi.org/10.3390/molecules28020564

Author Biographies

Yiwen Ge is affiliated with the Procuratorial Technology and Information Research Center of the Supreme People’s Procuratorate in Beijing, China. She is also associated with the Key Laboratory of Geriatric Nutrition and Health at Beijing Technology and Business University and the Key Laboratory of Brewing Molecular Engineering of China Light Industry. Her research interests span applied analytical and biomedical research, with interdisciplinary connections to nutrition, health, and molecular analysis.

Jungang Lv, Ph.D. is a researcher at the Procuratorial Technology and Information Research Center of the Supreme People’s Procuratorate in Beijing, China, where he serves as the corresponding author for this work. His research interests encompass the application of scientific and technological approaches to information analysis and related areas of analytical and biomedical research. He is also associated with research activities involving Beijing Technology and Business University and its laboratories in geriatric nutrition and health and brewing molecular engineering.