Chemical Profiling and Chemometric Classification of Magic Pen (Disappearing) Ink Samples Using ATR-FTIR Spectroscopy
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Abstract
Ink has always been an important aspect of document examination, which while may appear optically similar to the naked eye, but can vary significantly in terms of their chemical constituents. Majority of studies has been focussed on distinguishing these visibly similar inks. However, disappearing inks, also known as magic inks presents a unique set of challenge to document security given its ability to fade entirely within approximately seconds to days, thus enabling undetectable forgery. The current study attempted a non-destructive chemical profiling and classification of blue disappearing inks available in Indian markets using Attenuated Total Reflectance – Fourier Transform Infrared (ATR-FTIR) spectroscopy in conjunction with chemometric methods
In the present study, a total of ninety different blue magic pen (disappearing) inks, representing the 30 different brands were purchased from e-shopping websites and local markets of Jhansi district of Uttar Pradesh in India. The samples were prepared by drawing circles of 2 cm radius and filling it completely with ink in five subsequent strokes on 80 gsm white A4 copying paper for each pen which was then spectroscopically analyzed by ATR-FTIR within the range of 4000- 600 cm-1. The spectral data was further subjected to chemometric analysis viz. HCA and PC-DA.
FTIR spectroscopy of magic pen inks demonstrated significant similarities in spectra with characteristic peaks for O-H (alcohol/water), C-H (aliphatic), C=C (aromatic) and C-O stretching peaks indicating the presence of thymolphthalein as fundamental constituent to most of the blue disappearing ink formulations available in the markets. Chemometric analysis using Hierarchical Cluster Analysis (HCA) revealed four major clusters within the samples. PC based Discriminant Analysis (DA) model was then used to assess the classification of samples in these respective groups which performed reasonably well achieving an accuracy of 100% in classification and cross-validation. Also, PC based DA model for classification of samples according to manufacturer successfully, linked samples to their respective manufacturer with an original and cross-validated accuracy of 97.8% and 82.2% respectively.
Keywords
forensic sciences, magic pen, FTIR, PCA, DA, ink analysis, questioned document examination
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References
Welch, J. (2008). Erasable ink; something old, something new. Science & Justice, 48(4), 187–191. https://doi.org/10.1016/j.scijus.2007.11.002
Campbell, D. J., Bosma, W. B., Bannon, S. J., Gunter, M. M., & Hammar, M. K. (2012). Demonstration of thermodynamics and kinetics using FriXion erasable pens. Journal of Chemical Education, 89(4), 526-528. https://dx.doi.org/10.1021/ed100831p
Vaid, B. A., Kumar, S., Rana, R. S., & Kumar, N. (2012). Visualisation of disappearing ink writings. Problems of Forensic Sciences, 92, 311-318.
Gupta, G., Saha, S. K., Chakraborty, S., & Mazumdar, C. (2007, March). Document frauds: Identification and linking fake document to scanners and printers. In 2007 International Conference on Computing: Theory and Applications (ICCTA'07) (pp. 497-501). IEEE. http://dx.doi.org/10.1109/ICCTA.2007.55
Lal, B., & Chandra, R. (2010). Cross-examination of handwriting expert. Selective & Scientific Books.
Saferstein, R. (2001). Criminalistics: An introduction to forensic science. Prentice Hall
Harrison, W. R. (2011). Suspect documents: Their scientific examination (5th ed.). Universal Law Publishing Co. Pvt Ltd.
Patodiya, S. N. (1983). Practical problems on practice and law of banking in India (1st ed.). Banker's Books Publishing House Pvt Ltd.
Chayal, V. M., Handa, D. R., Singh, J., & Menon, S. K. (2016). A sensitive non-destructive method for detection of document frauds using thermal ink. Australian Journal of Forensic Sciences, 48(5), 601–612. http://dx.doi.org/10.1080/00450618.2015.1107132
Yousaf, M., & Lazzouni, M. (1995). Formulation of an invisible infrared printing ink. Dyes and Pigments, 27(4), 297–303. https://doi.org/10.1016/0143-7208(94)00068-D
Lee, J., Kong, G. S., Kang, T. K., Kim, B., & Jeon, O.Y. (2014). Invisible ink mark detection in the visible spectrum using absorption difference. Forensic Science International, 236, 77–83. https://doi.org/10.1016/j.forsciint.2013.12.024
Bartolome, F. B., Burguera, V. G., & Stanzak, R. K. (1996). Disappearing ink marking system (U.S. Patent No. US5586501A). U.S. Patent and Trademark Office.
Emily, W. (2009). Faded handwriting Forensic Document Examiner.
Anamika, D., & Kumar, S. (2020). A Brief Review on Invisible Ink: It's Various Types and Examination Methods. Journal of University of Shanghai for Science and Technology. ISSN: 1007-6735.
Purba, M. K., Gupta, S., Gupta, R. R., & Shukla, S. K. (2019). A survey of techniques used for Ink examination. Journal of Punjab Academy of Forensic Medicine and Toxicology, 19(1), 155. http://dx.doi.org/10.5958/0974-083X.2019.00032.3Sauzier, G., van Bronswijk, W., & Lewis, S. W. (2021). Chemometrics in forensic science: Approaches and applications. Analyst, 146(8), 2415–2448.
Throckmorton, J. G. (1990). Disappearing inks: Use, abuse, and detection. Journal of Forensic Sciences, 35(1), 199–203. https://doi.org/10.1520/JFS12820J
Abd-ElZaher, M. A.-E. (2014). Different types of inks having certain medicolegal importance: deciphering the faded and physically erased handwriting. Egyptian Journal of Forensic Sciences, 4(2), 39–44. https://doi.org/10.1016/j.ejfs.2013.09.002
El-Molla, M. M., Shama, S. A., & Saeed, S. E. S. (2013). Preparation of disappearing inks and studying the fading time on different paper surfaces. Journal of Forensic Sciences, 58(1), 188–194. https://doi.org/10.1111/j.1556-4029.2012.02208.x
Hemantini, D., & Khudbudin, M. (2018). Decipherment of disappeared ink: A case study. Brazilian Journal of Forensic Sciences, Medical Law and Bioethics, 7(3), 156-161. https://dx.doi.org/10.17063/bjfs7(3)y2018156
Ordway, H. (1984). Characteristics of erasable point pens. Forensic Science International, 26(4), 269–275.
Asicioglu, F., Tekin, T., Ozbek, N., Cevik, E. F., Ozcan, M., & Mohammed, A. L. (2019). Prepared disappearing ink and deciphering of documents. Journal of Forensic Sciences, 64(6), 1898–1905. https://doi.org/10.1111/1556-4029.14084
Silva, C. S., Borba, F. D. S. L., Pimentel, M. F., Pontes, M. J. C., Honorato, R. S., & Pasquini, C. (2013). Classification of blue pen ink using infrared spectroscopy and linear discriminant analysis. Microchemical Journal, 109, 122–127.
Pearson, K. (1901). LIII. On lines and planes of closest fit to systems of points in space. The London, Edinburgh, and Dublin philosophical magazine and journal of science, 2(11), 559-572. https://doi.org/10.1080/14786440109462720
Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. Journal of educational psychology, 24(6), 417.
https://doi.org/ 10.1039/D1AN00082A.
https://doi.org/10.1016/j.microc.2012.03.025
https://psycnet.apa.org/doi/10.1037/h0071325
Jolliffe, I. (2011). Principal component analysis. In International encyclopedia of statistical science (pp. 1094-1096). Springer, Berlin, Heidelberg.
Sauzier, G., van Bronswijk, W., & Lewis, S. W. (2021). Chemometrics in forensic science: Approaches and applications. Analyst, 146(8), 2415–2448.
Daszykowski, M., Kaczmarek, K., Vander Heyden, Y., & Walczak, B. (2007). Robust Statistics in Data Analysis—A Review Basic Concepts. Chemometrics and Intelligent Laboratory Systems, 85(2), 203–219. https://doi.org/10.1016/j.chemolab.2006.06.016
McLachlan, G. J. (2005). Discriminant analysis and statistical pattern recognition. John Wiley & Sons. ISBN: 978-0-471-69115-0
Verma, N., Kumar, R., & Sharma, V. (2018). Analysis of Laser Printer and Photocopier Toners by Spectral Properties and Chemometrics. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 196, 40–48. https://doi.org/10.1016/j.saa.2018.02.001
Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wiley interdisciplinary reviews: computational statistics, 2(4), 433-459. https://doi.org/10.1002/wics.101
Bro, R., & Smilde, A. K. (2014). Principal component analysis. Analytical methods, 6(9), 2812-2831. https://doi.org/10.1039/C3AY41907J
Gromski, P. S., Correa, E., Vaughan, A. A., Wedge, D. C., Turner, M. L., & Goodacre, R. (2014). A comparison of different chemometrics approaches for the robust classification of electronic nose data. Analytical and bioanalytical chemistry, 406(29), 7581-7590. https://doi.org/10.1007/s00216-014-8216-7
Lee, L. C., Liong, C. Y., Osman, K., & Jemain, A. A. (2016). Comparison of Several Variants of Principal Component Analysis (PCA) on Forensic Analysis of Paper Based on IR spectrum. AIP Conference Proceedings, 1750(1), 060012. https://doi.org/10.1063/1.4954617
Singla, A., Shekhar, S., & Ahirwar, N. (2024). AI-Driven Approaches to Reshape Forensic Practices: Automating the Tedious, Augmenting the Astute. In Cases on Forensic and Criminological Science for Criminal Detection and Avoidance (pp. 280-312). IGI Global Scientific Publishing. http://dx.doi.org/10.4018/978-1-6684-9800-2.ch010
Kumar, R., & Sharma, V. (2018). Chemometrics in forensic science. TrAC Trends in Analytical Chemistry, 105, 191-201. https://doi.org/10.1016/j.trac.2018.05.010
Chatterjee, P. M., Krishan, K., Singh, R. K., & Kanchan, T. (2020). Sex estimation from the femur using discriminant function analysis in a Central Indian population. Medicine, Science and the Law, 60(2), 112-121. https://doi.org/10.1177/0025802419900576
Bagheripour-Asl, M., Jahanmardi, R., Tahermansouri, H., & Forghani, E. (2018). Evaluation of thymolphthalein-grafted graphene oxide as an antioxidant for polypropylene. Carbon letters, 25, 60-67. http://dx.doi.org/10.5714/CL.2018.25.060
Jahanmardi, R., Saberi, M., & Fathi, M. (2020). Preparation of thymolphthalein stearate and appraisement of its efficacy as an antioxidant for polypropylene. Frontiers in Chemical Research, 2(1), 10-17. http://dx.doi.org/10.22034/FCR.2020.117673.1014
Kamil, M., Asri, M. N. M., Desa, W. N. S. M., & Ismail, D. (2015). Fourier transform infrared (FTIR) spectroscopy and principal component analysis (PCA) of unbranded black ballpoint pen inks. Malaysian Journal of Forensic Sciences, 6(1), 48-53.
Lee, L. C. (2014). Investigating Between-model variation of the PaperMate® pen using infrared spectrum and multivariate statistical techniques. Forensic Sci. J, 13(1), 15-22.
Halim, M. I. A., Saim, N., Osman, R., Jasmani, H., & Aziz, N. S. A. (2013, April). Multivariate chemometric discrimination of blue gel-pen inks by fourier transform infrared spectroscopy: Diskriminasi kimometrik statistik terhadap pen gel dakwat biru dengan spektroskopi sinar merah. In 2013 IEEE Symposium on Computers & Informatics (ISCI) (pp. 236-240). IEEE.
Zhao, F., & Li, B. (2021). Identification of Different Brands Erasable Pens by Infrared Spectroscopy Combined with Chemometrics Methods. In 2021 6th International Conference on Automation, Control and Robotics (ICACR) (pp. 57-61). IEEE. http://dx.doi.org/10.3964/j.issn.1000-0593(2021)08-2420-07
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