Abstract
Smokeless powder is the primary propellant in civilian and military ammunition, and in China, the use of propellants to make homemade ammunition and bombs is an emerging criminal practice. The identification and differentiation of the propellants used can provide forensic information about their sources. Depending upon the ammunition manufacturer and type, the recipe of propellants varies, and the characterization of smokeless powders in terms of their spectral components is useful for differentiating propellants. In this work, near-infrared spectroscopy (NIR) and chemometric modeling were used to explore the feasibility of differentiating and predicting smokeless powders from different sources. By comparison, the proposed neural network model in the study exhibited an average accuracy of over 80%. Furthermore, the potential for differentiating smokeless powders was well demonstrated via simple and rapid near-infrared spectroscopic analysis, and the employment of chemical agents and time-consuming chromatography and mass spectrometry could thereby be avoided.
Data availability
The data that supports the findings of this study are available in the supplementary material of this paper.
References
Heramb, R. M. & McCord, B. R. The manufacture of smokeless powders and their forensic analysis: A brief review. Forensic Sci. Commun. 4, 1–7 (2002).
Álvarez, Á. et al. Propellant’s differentiation using FTIR-photoacoustic detection for forensic studies of improvised explosive devices. Forensic Sci. Int. 280, 169–175 (2017).
Lennert, E. & Bridge, C. Analysis and classification of smokeless powders by GC-MS and DART-TOFMS. Forensic Sci. Int. 292, 11–22 (2018).
Van den Hurk, R. S. et al. Characterization and comparison of smokeless powders by on-line two-dimensional liquid chromatography. J. Chromatogr. A 1672, 463072 (2022).
Goudsmits, E., Sharples, G. P. & Birkett, J. W. Preliminary classification of characteristic organic gunshot residue compounds. Sci. Justice 56, 421–425 (2016).
ASTM E2999-17. Standard test method for analysis of organic compounds in smokeless powder by gas chromatography-mass spectrometry and Fourier transform infrared spectroscopy. ASTM International (2017).
López-López, M., Ferrando, J. L. & García-Ruiz, C. Comparative analysis of smokeless gun powders by Fourier transform infrared and Raman spectroscopy. Anal. Chim. Acta 717, 92–99 (2012).
Thomas, J. L., Lincoln, D. & McCord, B. R. Separation and detection of smokeless powder additives by ultra performance liquid chromatography with tandem mass spectrometry (UPLC/MS/MS). J. Forensic Sci. 58, 609–615 (2013).
Assner, A. L. & Weyermann, C. LC-MS method development and comparison of sampling materials for the analysis of organic gunshot residues. Forensic Sci. Int. 264, 47–55 (2016).
Lemmink, I. B., van Schaik, J. R., van den Hurk, R. S. & Van Asten, A. C. Characterizing nitrocellulose by nitration degree and molecular weight: A user-friendly yet powerful forensic comparison method for smokeless powders. Forensic Chem. 42, 100637 (2025).
Kesic, B. et al. Forensic profiling of smokeless powders (SLPs) by gas chromatography-mass spectrometry (GC-MS): A systematic investigation into injector conditions and their effect on the characterization of samples. Anal. Bioanal. Chem. 416, 1907–1922 (2024).
Dennis, D. M. K., Williams, M. R. & Sigman, M. E. Assessing the evidentiary value of smokeless powder comparisons. Forensic Sci. Int. 259, 179–187 (2016).
López-López, M., Fernández de la Ossa, M. Á. & García-Ruiz, C. Fast analysis of complete macroscopic gunshot residues on substrates using Raman imaging. Appl. Spectrosc. 69, 889–893 (2015).
Dou, Y., Qu, N., Wang, B., Chi, Y. Z. & Ren, Y. L. Simultaneous determination of two active components in compound aspirin tablets using principal component artificial neural networks (PC-ANNs) on NIR spectroscopy. Eur. J. Pharm. Sci. 32, 193–199 (2007).
Ouyang, Q., Zhao, J. & Chen, Q. Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 151, 280–285 (2015).
Reboucas, M. V., Santos, J. B. D., Domingos, D. & Massa, A. R. C. G. Near-infrared spectroscopic prediction of chemical composition of a series of petrochemical process streams for aromatics production. Vib. Spectrosc. 52, 97–102 (2010).
Judge, M. D. The application of near-infrared spectroscopy for the quality control analysis of rocket propellant fuel pre-mixes. Talanta 62, 675–679 (2004).
Zou, Q., Deng, G., Guo, X., Jiang, W. & Li, F. A green analytical tool for in-process determination of RDX content of propellant using the NIR system. ACS Sustain. Chem. Eng. 1, 1506–1510 (2013).
Zhou, S. et al. Rapid quantification of stabilizing agents in single-base propellants using near infrared spectroscopy. Infrared Phys. Technol. 77, 1–7 (2016).
Guo, Z. Q., Ren, Q., Huang, Y. Z. & Dong, S. L. Application of near infrared spectroscopy in determination of components of detonator. Chin. J. Spectrosc. Lab. 23, 187–190 (2006).
Funding
The work was funded by the grant of Ministry of Public Security under Grant Basic Work Plan for Strengthening Police Force of Ministry of Public Security(2022JC12),Grant Central Public-Interest Scientific Institution Basal Research Fund(2024JBGS002),Grant Double Ten Project of Ministry of Public Security, China (2021SSGG028) and Grant Technology Research Project of the Ministry of Public Security, China (2021JSYJC08).
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Hongling Guo: Conceptualization, Methodology, Formal analysis, Investigation, Writing - original draft. Haoyuan Shi: Methodology, Formal analysis, Investigation, Writing - original draft. Yinghua Feng: Formal analysis, Investigation Yiting Guo: investigation Xiuli zhang: investigation Ping Wang: investigation Can Hu: investigation Hongcheng Mei: investigation Yajun Li: investigation Jun Zhu: Writing -review & editing.
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Guo, H., Shi, H., Feng, Y. et al. A study for potential rapid discrimination of smokeless powders by near-infrared spectroscopy and chemometric modeling methods for forensic application. Sci Rep (2026). https://doi.org/10.1038/s41598-026-45433-0
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DOI: https://doi.org/10.1038/s41598-026-45433-0
