Stamp-pad ink tracing method based on volatile compound fingerprint identification and positional isomer identification

Abstract

The invention discloses a stamp-pad ink tracing method based on volatile compound fingerprint identification and positional isomer identification. The method adopts an HS-GC-IMS technology for detection, and specifically comprises the following steps: putting white paper coated with stamp-pad ink into a headspace sampling bottle, incubating, taking headspace gas, injecting the headspace gas into a gas chromatography-ion mobility spectrometer for analysis to obtain GC-IMS sample data, and comprehensively analyzing the sample data through instrument analysis software and a multivariate statistical method. According to the method, the HS-GC-IMS technology is combined with a multivariate statistical analysis method, fingerprint identification and positional isomer identification of volatile compounds in the stamp-pad ink sample are realized, an efficient stamp-pad ink sample tracing method is established, and a basis is provided for authenticity identification of document stamps.

Description

Technical Field

[0001] The present invention belongs to the technical field of new document inspection methods in forensic science, and in particular relates to a printing ink tracing method based on volatile compound fingerprint recognition and positional isomer identification. Background Art

[0002] With the development of science and technology, the level of document forgery and tampering is increasing, leading to rising crime rates, increasing the difficulty of solving cases, and affecting public security and social stability. On many documents, such as checks, invoices, and agreements, signatures alone are not enough; affixing an official seal is a direct way to prove the legal validity of the document. Document authentication is an important project in the field of forensic science forensic identification of physical evidence. Among them, projects such as seal inscription identification, identification of tampered (defaced) documents, identification of document formation methods, and identification of the time sequence of red and black ink often involve the identification of relevant properties of seal inscriptions. Tracing the source of the ink in the seal inscription and analyzing the time of formation can provide strong evidence for solving cases. Therefore, the authenticity identification of seal inscriptions is an important issue that needs to be solved urgently.

[0003] Existing seal inscription analysis methods primarily rely on physical methods, such as photography, contrast, and digital methods, which identify seals based on morphological features such as shape, lines, color, and fine structure. These methods are highly subjective and, with the advancement of counterfeiting methods, are no longer able to accurately identify seals. Currently, objective methods for identifying seal authenticity through chemical composition analysis are still lacking. Each ink sample has a different chemical composition, including dyes, solvents, and plasticizers. Furthermore, the volatile compounds in the seal inscription change over time. Therefore, investigating and analyzing volatile compounds can enable brand tracing of inks and analyze the creation time of documents, significantly assisting in the inspection of suspicious documents. Spectroscopic methods, such as ultraviolet-visible (UV-vis) absorption spectroscopy, infrared (IR) spectroscopy, and Raman spectroscopy, are commonly used to analyze the chemical composition of inks. These methods offer the advantages of fast analysis speed, high sensitivity, and minimally invasive molecular information. However, a limitation of spectroscopic methods is their limited ability to identify unknown compounds in the ink. Mass spectrometry, on the other hand, offers a strong ability to identify the structure of unknown substances. Its combination with chromatography, such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), makes it a powerful tool for separating and identifying unknown components in ink. These methods offer advantages such as high sensitivity, accurate qualitative analysis of unknown compounds, and precise quantitative analysis. However, these methods have limitations when analyzing the chemical composition of ink, such as low extraction yields, complex pretreatment procedures, and sample destructiveness.

[0004] In recent years, headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) has become a powerful tool for detecting volatile compounds. It has the characteristics of high sensitivity, fast analysis speed, and visualization of data analysis, and has been widely used in the fields of food, traditional Chinese medicine, environmental pollutants, human metabolites, etc. HS-GC-IMS relies on the synergistic effect of high-resolution gas chromatography and high-sensitivity ion mobility spectrometry to provide three-dimensional (3D) spectra containing ion drift time, retention time, and signal peak intensity. HS-GC-IMS can efficiently identify unknown compounds. More importantly, it does not require a complex pretreatment process and can even achieve non-destructive detection. In addition, the indelible ink matrix is complex and contains a large number of isomers, which have a great impact on the performance of the indelible ink. Especially for positional isomers, their structures are highly similar, posing a greater challenge to the analysis method. Therefore, the accurate identification of positional isomers is crucial for the traceability of indelible ink brands. Therefore, it is of great significance to develop an efficient method for indelible ink traceability based on the fingerprint recognition of volatile compounds and the identification of positional isomers in the field of forensic science. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for fingerprint recognition of volatile compounds and identification of positional isomers in ink aiming at the deficiencies of the prior art. The present invention combines HS-GC-IMS technology with multivariate statistical analysis to establish an effective method for indelible ink traceability.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions:

[0007] An indelible ink traceability method based on fingerprint recognition of volatile compounds and identification of positional isomers is detected by using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology, specifically including the following steps: (1) Sample preparation: Take 6 kinds of red quick-drying indelible inks of Comix, Arxin, M&G, Kingdee, SIMAA, and yonyou; (2) Place the white paper coated with indelible ink in a headspace vial, incubate, take the headspace gas and inject it into HS-GC-IMS for analysis to obtain sample data; (3) Comprehensively analyze the sample data through analysis software and multivariate statistical methods.

[0008] The detection conditions of the headspace gas chromatography-ion mobility spectrometry technology are as follows:

[0009] Headspace injection detection conditions: Injection volume: 500 μL; Incubation time: 15 min; Incubation temperature: 80 °C; Injection needle temperature: 85 °C; Incubation rotation speed: 500 rpm;

[0010] Gas-phase ion mobility spectrometry detection conditions: Chromatographic column MXT-5, length: 15 m, inner diameter: 0.53 mm, film thickness: 1 μm; column temperature: 60 °C; carrier gas / drift gas: N2; IMS temperature: 45 °C; analysis time: 30 min;

[0011] Carrier gas and drift gas conditions: 0 min: E1 / drift gas 150 mL / min, E2 / carrier gas 2 mL / min;

[0012] 2 min: E1 / drift gas 150 mL / min, E2 / carrier gas 2 mL / min;

[0013] 10 min: E1 / drift gas 150 mL / min, E2 / carrier gas 10 mL / min;

[0014] 25 min: E1 / drift gas 150 mL / min, E2 / carrier gas 100 mL / min;

[0015] 30 min: E1 / drift gas 150 mL / min, E2 / carrier gas 100 mL / min.

[0016] The comprehensive analysis of sample data is carried out by the instrument supporting analysis software and multivariate statistical analysis method. Specifically: (1) The Reporter plug-in is used to directly compare the spectral differences between samples. The spectra include two-dimensional top view, three-dimensional spectrum and differential comparison spectrum; (2) The NIST database and IMS database built in the VOCal software are used to qualitatively analyze volatile organic compounds, and the peaks of compounds are integrated to further calculate the peak volume to obtain the relative content of specific volatile substances; (3) The Gallery Plot plug-in is used to draw fingerprint spectra, and the differences in volatile organic compounds between different samples are visually and quantitatively compared through the comparison of fingerprint spectra; (4) The Dynamic PCA plug-in is used to perform clustering principal component analysis and similarity analysis on samples; (5) According to the HS-GC-IMS analysis principle, position isomers are qualitatively analyzed; (6) Multivariate statistical analysis methods are used to establish a sample traceability model, including hierarchical cluster analysis (HCA), orthogonal partial least squares discriminant analysis (OPLS-DA), etc.

[0017] The incubation is carried out at 80 °C for 15 min; the sampling volume of the headspace gas is 500 μL.

[0018] The present invention combines HS-GC-IMS technology with multivariate statistical analysis method to realize fingerprint recognition of volatile compounds in stamp ink samples and identification of position isomers, and establishes an efficient stamp ink sample traceability method, providing a basis for the authenticity identification of document seals. Description of the Drawings

[0019] Figure 1 For the volatile compound components in 6 ink samples, (A) 3D topographic map, (B) 2D top view, (C) 2D difference comparison map.

[0020] Figure 2 For the fingerprint spectra of 6 ink samples.

[0021] Figure 3 For the volcano plots of yonyou and SIMAA samples.

[0022] Figure 4 For the proportion of specific volatile compounds in the total volatiles of 6 ink samples.

[0023] Figure 5 For hierarchical clustering analysis, (A) dendrogram, (B) clustering heat map.

[0024] Figure 6 For the gas chromatograms of positional isomers, (A) 1-Butanol (33), 2-Butanol (107), tert-Butanol (78), (B) 2-Heptanone (19), 4-Heptanone (117).

[0025] Figure 7 For correlation analysis, (A) OPLS-DA model plot, (B) loading scatter plot. Detailed implementation manners

[0026] The following embodiments are further descriptions of the present invention rather than limitations thereof.

[0027] Embodiment 1

[0028] 1. Samples: Ink stamps are widely used in daily life, such as contracts, official documents, etc. Six typical quick-drying red inks commonly used in daily life were selected as experimental samples in this study, including: Comix, Arxin, M&G, Kingdee, SIMAA, yonyou.

[0029] 2. Experimental conditions: Headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), instrument model: Flavor analyzer:

[0030] Table 1 Analysis conditions

[0031]

[0032] Table 2 Carrier gas and drift gas conditions

[0033] Time(min:sec) E1 (drift gas) E2 (carrier gas) Recording (data recording) 00:00 150 mL / min 2 mL / min rec 02:00 150 mL / min 2 mL / min - 10:00 150 mL / min 10 mL / min - 25:00 150 mL / min 100 mL / min - 30:00 150 mL / min 100 mL / min stop

[0034] 3. Experimental procedure:

[0035] Place a white paper (2 cm × 3 cm) coated with two drops (100 μg) of stamp ink into a 20 mL headspace vial, incubate at 80 °C for 15 min, then the autosampler takes 500 μL of headspace gas and injects it into the instrument for analysis. Each sample is tested in five parallels. The specific test conditions are shown in Table 1 and Table 2. Use headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) to detect six brands of quick-drying stamp inks, obtain HS-GC-IMS sample data, and comprehensively analyze the sample data through the analysis software and multivariate statistical methods supporting the instrument.

[0036] The analysis software supporting the instrument includes VOCal software and three plugins, which can analyze samples from different perspectives.

[0037] 1) VOCal: Used for qualitative and quantitative analysis of spectra and data. The built-in NIST database and IMS database in the application software can be used for qualitative analysis of substances, and data can be expanded by oneself according to needs using reference standards. Each point in the figure represents a volatile organic compound; after establishing a standard curve for it, quantitative analysis can be carried out;

[0038] 2) Reporter plugin: Directly compare the spectral differences between samples (two-dimensional top view, three-dimensional spectrum, and difference spectrum);

[0039] 3) Gallery Plot plugin: Fingerprint spectrum comparison, visually and quantitatively compare the differences in volatile organic compounds between different samples;

[0040] 4) Dynamic PCA plugin: Dynamic principal component analysis and similarity analysis diagram, used for clustering analysis and similarity analysis of samples, and quickly determining the types of unknown samples.

[0041] Several other software are also used in the data processing process, including: Origin, SIMCA, etc.

[0042] 4. Experimental results:

[0043] 4.1 HS-GC-IMS spectral analysis of multiple stamp ink samples

[0044] The HS-GC-IMS 2D / 3D topographic maps can reflect the overall information of various volatile compounds in the stamp ink samples, as Figure 1 shown. The 3D topographic map of volatile organic compounds in the stamp ink samples is as Figure 1As shown in A, the x-axis represents the drift time of the IMS instrument, and the y-axis represents the retention time of gas chromatography. The concentration of each volatile compound can be shown by the difference in peak volume. To make the data more intuitive and visual, the peak signal intensity in the 3D graph is represented by color brightness to obtain a two-dimensional spectrum, as Figure 1 shown in B. The red vertical line at 1.0 on the left side of the spectrum represents the signal position of the reaction ion peak (RIP), and the background of the spectrum is blue.

[0045] The invention can further distinguish different series of printing inks produced by the same manufacturer. Yonyou and SIMAA samples belong to the same manufacturer. Using the Figure 1 difference comparison model in C, the volatile components in similar printing ink samples are distinguished. Taking Yonyou as a reference, the spectrum of the SIMAA sample is subtracted from it. When the concentrations of the two volatile compounds are the same, the spectrum shows white. Blue dots indicate that the concentrations of these volatiles are lower than the reference value, and red dots indicate that the concentrations of these volatiles are higher than the reference value. As can be seen from Figure 1 C, most areas of the spectrum of the SIMAA sample in the difference comparison model are red, indicating that it has more types or higher concentrations of volatile components than the reference sample. There are also many blue dots in the spectrum of the SIMAA sample, mainly distributed between the retention times of 100 to 800 s. The results show that different production processes and formulations of printing inks affect the types and contents of volatile components, which plays a key role in distinguishing the brands and categories of various printing ink samples.

[0046] 4.2 Qualitative and difference analysis of volatile compounds

[0047] Figure 2 is the fingerprint spectrum of volatile compounds in different printing ink samples, intuitively and quantitatively comparing the differences in volatile organic compounds between different samples. A total of 127 peaks in the present invention were qualitatively analyzed, and 22 compounds were not accurately identified and marked with numbers. Their detailed information is listed in Table 3. According to the mechanism of HS-GC-IMS, monomers or dimers may be formed in the drift tube under the influence of the compound concentration, represented by M and D respectively. When the concentration of the compound is high, two molecules share a proton to form a dimer. In addition, the formation of dimers is also related to the proton affinity of the analyte. If the proton affinity of the compound is higher than that of water, it is more easily ionized to form a dimer.

[0048] The present invention uses a volcano plot to analyze these two volatile components in similar samples. Yonyou and SIMAA samples belong to the same manufacturer and contain some similar volatile compounds. The volcano plot is used to compare and analyze their volatile compounds, as Figure 3As shown. Each point represents a compound, the red points indicate compounds with significantly increased content, and the blue points indicate compounds with significantly decreased content. The results of the volcano plot show that there are significant differences in 83 compounds between the yonyou and SIMAA samples.

[0049] 4.3 Proportion of Specific Compounds in Total Volatiles

[0050] A total of 127 volatile compounds were selected in this invention, among which 105 compounds were accurately identified, including 17 alcohols, 17 aldehydes, 26 ketones, 23 esters, 3 alkenes, 3 acids, and 16 others. The specific information of the compounds is listed in Table 3. The relative contents of various compounds were analyzed based on the results of HS-GC-IMS peak volume. The percentage composition of each type of compound in the six stamp ink samples is shown in Figure 4 Alcohols had relatively high concentrations in the Comix (24.59%), Arxin (27.98%), and yonyou (35.14%) samples. Aldehydes had high contents in Comix (40.47%), Arxin (39.22%), and SIMAA (42.12%), while they decreased sharply in yonyou (5.47%), M&G (6.05%), and Kingdee (2.21%). The contents of ketones were relatively stable in the six stamp ink samples, remaining in the range of 15% - 36%. Esters had the highest content in M&G (60.28%), and decreased successively in other samples, namely Kingdee (33.42%), yonyou (19.47%), SIMAA (15.87%), Arxin (13.13%), and Comix (8.10%). Comix and Arxin were the most similar, both containing alcohols, aldehydes, ketones, esters, and alkenes, and their contents were close.

[0051] Table 3 Detailed Information of Volatile Compounds in Six Stamp Ink Samples According to HS-GC-IMS Results

[0052]

[0053]

[0054]

[0055]

[0056]

[0057] RI: Retention index, indicating the retention index calculated using normal ketones C4 - C9 as external standards.

[0058] Rt: Retention time, representing the retention time in the gas-phase capillary chromatographic column.

[0059] Dt: Drift time, representing the drift time in the drift tube.

[0060] M: Monomer.

[0061] D: Dimer.

[0062] 4.4 Hierarchical cluster analysis (HCA) of volatile compounds

[0063] Based on the signal intensities of volatile compounds in the HS-GC-IMS results, two hierarchical cluster analysis methods, dendrogram and cluster heatmap, were used to analyze the correlation between the classification of volatile compounds and stamp ink samples. The dendrogram is shown in Figure 5 Figure A. According to the differences in the types and contents of volatile compounds, the stamp ink samples were clearly divided into 6 clusters. Five parallel detections of each stamp ink sample were clustered into one category, indicating a very high similarity among them, which proves the good reproducibility and stability of this method. The cluster heatmap was used to visually display the differential volatile compounds of 6 stamp ink samples. As shown in Figure 5 Figure B. Each square represents a volatile compound, and the compounds are aggregated in the horizontal direction. Red indicates a high content of the compound and a strong correlation with the sample, while blue indicates a low content of the compound in the sample and a weak correlation with the sample. It can be seen from the figure that all volatile compounds are divided into six groups, and each group indicates that the expression patterns of these compounds in the samples are similar and they have a strong correlation. For example, the compounds in group VI have relatively high contents mainly in comix and Arxin samples, indicating a certain similarity between the two samples, and these compounds affect the performance of this kind of stamp ink.

[0064] 4.5 Identification of positional isomers

[0065] The present invention established a method for identifying positional isomers in stamp ink samples. The accurate determination of positional isomers is a crucial step in judging the compound composition in the sample and controlling the product quality. The present invention utilized the different average collision cross-sectional areas of compound molecular sizes in ion mobility spectrometry to establish an accurate identification method for structurally similar positional isomers. Figure 6 Figure A shows the qualitative analysis results of fatty alcohol positional isomers. 1-butanol (33), 2-butanol (107), and tert-butanol (78) are positional isomers of butanol. They have exactly the same elemental composition, but due to the different connection positions of -OH on the fatty chain, there are differences in molecular sizes, resulting in different collision cross-sectional areas in the drift tube and different mobilities, which are 1.698, 1.737, and 1.752 cm 2 / Vs. Accordingly, HS-GC-IMS can efficiently achieve accurate determination of them. Similarly, Figure 6 B shows the analysis results of fatty ketone position isomers. The mobilities of 2-heptanone (19) and 4-heptanone (117) are 1.222 and 1.653 cm 2 / Vs, respectively.

[0066] 4.6 Establishment and verification of multivariate statistical models

[0067] To achieve the prediction of unknown sample classification, the orthogonal partial least squares discriminant analysis (OPLS-DA) model was further analyzed. In this method, 6 different types of stamp ink samples were used as independent variables, and 127 volatile compounds were used as dependent variables. The effective identification of 6 brands of stamp ink samples was successfully achieved through OPLS-DA. As Figure 7 shown in A, in this analysis, the fitting index of the independent variable (R2X) was 0.974, the fitting index of the dependent variable (R2Y) was 0.99, and the model prediction index (Q2) was 0.984, which proved that the OPLS-DA model established in this study had excellent prediction ability for the classification of different stamp ink samples. In addition, the correlation between volatile compound variables and sample clusters is as Figure 7 shown in B. Volatile compounds located in the same quadrant had a strong correlation with the sample cluster, indicating that these compounds were characteristic markers in the sample.

[0068] Thus, through the HS-GC-IMS technology combined with multivariate statistical analysis methods, the present invention realizes fingerprint recognition of volatile compounds and identification of position isomers in stamp ink samples, and establishes an efficient traceability method for stamp ink samples.

[0069] The above is only the preferred embodiment of the present invention. It should be noted that the above preferred embodiment should not be regarded as a limitation of the present invention. The protection scope of the present invention should be subject to the scope defined by the claims. For those of ordinary skill in the art of this technology, without departing from the spirit and scope of the present invention, several improvements and refinements can also be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. An ink tracing method based on volatile compound fingerprint recognition and positional isomer identification, characterized in that, Detection is carried out by using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology, which specifically includes the following steps: (1) Sample preparation: Take 6 kinds of red quick-drying printing inks, namely Qixin Comix, Arxin, M&G, Kingdee, SIMAA, and yonyou; (2) Place the white paper coated with printing ink in a headspace vial, incubate, take the headspace gas and inject it into HS-GC-IMS for analysis to obtain sample data; (3) Comprehensively analyze the sample data through analysis software and multivariate statistical methods.

2. The ink tracing method based on volatile compound fingerprint recognition and positional isomer identification according to claim 1, wherein The detection conditions of the headspace gas chromatography-ion mobility spectrometry technology are as follows: Headspace injection detection conditions: Injection volume: 500 μL; Incubation time: 15 min; Incubation temperature: 80 °C; Injection needle temperature: 85 °C; Incubation rotation speed: 500 rpm; Gas-phase-ion mobility spectrometry detection conditions: Chromatographic column MXT-5, length: 15 m, inner diameter: 0.53 mm, film thickness: 1 μm; Column temperature: 60 °C; Carrier gas / drift gas: N2; IMS temperature: 45 °C; Analysis time: 30 min; Carrier gas and drift gas conditions: 0 min: E1 / drift gas 150 mL / min, E2 / carrier gas 2 mL / min; 2 min: E1 / drift gas 150 mL / min, E2 / carrier gas 2 mL / min; 10 min: E1 / drift gas 150 mL / min, E2 / carrier gas 10 mL / min; 25 min: E1 / drift gas 150 mL / min, E2 / carrier gas 100 mL / min; 30 min: E1 / drift gas 150 mL / min, E2 / carrier gas 100 mL / min.

3. The ink tracing method based on volatile compound fingerprint recognition and position isomer identification according to claim 1, characterized in that The comprehensive analysis of the sample data by using the instrument analysis software and multivariate statistical analysis method is specifically as follows: (1) Use the Reporter plug-in to directly compare the spectral differences between samples. The spectra include two-dimensional top view, three-dimensional spectrum, and differential comparison spectrum; (2) Use the NIST database and IMS database built into the VOCal software to qualitatively analyze volatile organic compounds, integrate the peaks of compounds, and further calculate the peak volume to obtain the relative content of specific volatile substances; (3) Use the Gallery Plot plug-in to draw fingerprint spectra, and visually and quantitatively compare the differences in volatile organic compounds between different samples through fingerprint spectrum comparison; (4) Use the Dynamic PCA plug-in to perform principal component analysis and similarity analysis on samples; (5) Qualitatively analyze positional isomers according to the HS-GC-IMS analysis principle; (6) Use multivariate statistical analysis methods to establish a sample traceability model, including hierarchical clustering analysis and orthogonal partial least squares discriminant analysis.

4. The ink tracing method based on volatile compound fingerprint recognition and positional isomer identification according to claim 1, characterized in that The incubation is carried out at 80 °C for 15 min; the sampling volume of the headspace gas is 500 μL.

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