The Top 10 Most Influential Applications of Molecular Spectroscopy in Forensic Analysis (2025–2026)

Abstract

The application of molecular spectroscopy in forensic science has expanded significantly between 2025 and 2026, driven by innovations in instrumentation, chemometric modeling, and artificial intelligence. This review provides an in-depth analysis of ten highly influential publications that collectively define the modern landscape of forensic spectroscopy. These studies encompass diverse applications, including biological fluid aging, post-mortem interval estimation, drug detection in biological and seized samples, soil geolocation, skeletal identification, and pharmaceutical forensic toxicology.

Particular emphasis is placed on the integration of vibrational spectroscopy techniques—such as ATR FT-IR, Raman, and NIR—with advanced multivariate analysis and machine learning algorithms. These approaches enable the extraction of subtle spectral features associated with biochemical degradation, compositional variability, and environmental effects. The review further highlights the increasing role of portable instrumentation and explainable AI in enabling rapid, field-deployable, and legally robust forensic analyses.

Introduction

The analytical demands of modern forensic science have evolved considerably, requiring techniques that can deliver rapid, accurate, and non-destructive analysis of increasingly complex and minute sample evidence. Molecular spectroscopy has emerged as a central solution to these challenges due to its inherent ability to provide detailed chemical information based on molecular vibrations and electronic transitions.

Traditional forensic techniques such as gas and liquid chromatography–based mass spectrometry, such as GC–MS and (LC–MS/MS, remain indispensable in forensic work; however, they are often limited by extensive sample preparation, longer analysis times, and destructive workflows. In contrast, spectroscopic methods—particularly FT-IR, Raman, and NIR—offer rapid spectral acquisition with minimal or no sample preparation, making them highly suitable for trace evidence and in situ analysis.

In 2025 and 2026, the field has experienced a paradigm shift driven by the convergence of spectroscopy with chemometrics, machine learning, and portable instrumentation. These developments have enabled not only improved analytical performance but also the extraction of temporal and environmental information from spectral data—capabilities that were previously inaccessible or underdeveloped.

This review critically examines ten influential publications that exemplify these advances, focusing on their methodological contributions, forensic applicability, and broader impact on the discipline.

Selected Research

1. SERS in Forensic Detection (2026)

Murali et al. provide a comprehensive review of surface-enhanced Raman spectroscopy (SERS), detailing the underlying enhancement mechanisms and their application to forensic analysis (1). The authors describe how plasmonic nanostructures—such as gold and silver nanocubes, nanorods, and flexible substrates—enable dramatic signal amplification, and allow detection down to the single-molecule level.

The review spans a wide range of forensic applications, including latent fingerprint chemical imaging, explosive residue detection, illicit drug identification, and ink discrimination in questioned documents. Importantly, the authors discuss emerging innovations such as microfluidic SERS devices and AI-assisted spectral libraries, which are poised to enhance method reproducibility and field deployment.

Why influential: This paper is particularly impactful because it consolidates disparate developments in SERS into a coherent forensic framework. It also addresses critical challenges—such as substrate reproducibility and standardization—while outlining realistic pathways for transitioning SERS from research to operational forensic use.

2. Semen Stain Aging via ATR FT-IR and Raman (2026)

Cano-Trujillo et al. investigate the aging of semen stains on porous substrates using ATR FT-IR and Raman spectroscopy combined with orthogonal partial least squares–discriminant analysis (OPLS-DA) chemometric modeling (2). The study systematically evaluates spectral changes over time, revealing distinct phases of biochemical degradation, including early subtle changes followed by more pronounced spectral evolution after approximately one week.

A key strength of this work is the use of realistic substrates (for example, fabrics and paper), which introduces complexity due to spectral interference but enhances forensic relevance. The comparison between ATR FT-IR and Raman demonstrates complementary strengths: FT-IR provides bulk chemical information, while Raman offers localized molecular specificity.

Why influential: This study addresses one of the most challenging aspects of forensic biology—estimating the age of biological stains under realistic conditions. Its non-destructive methodology and robust chemometric framework represent a major step toward practical implementation in casework.

3. PMI Estimation Using ATR FT-IR and Explainable AI (2026)

Chen et al. present a novel approach for estimating post-mortem interval (PMI) using ATR FT-IR spectroscopy combined with multiple machine learning (ML) models and SHapley Additive exPlanations (SHAP)-based interpretability (3). The study achieves high predictive accuracy while also identifying key spectral features associated with biochemical degradation, such as carbohydrate and metabolite-related bands.

The integration of SHAP analysis provides insight into the contribution of individual spectral variables, effectively linking model predictions to underlying biochemical processes. This addresses a major limitation of many machine learning approaches in forensic science—the lack of interpretability.

Why influential: The combination of high accuracy and explainability is a significant advancement. This work sets a new standard for AI-driven forensic analysis by ensuring that predictive models are both scientifically interpretable and legally defensible.

4. Optical Imaging and Machine Learning in Toxicology (2026)

Pérez-Beltrán et al. review the integration of spectroscopic imaging techniques—such as hyperspectral and multispectral imaging—with machine learning for pharmaceutical forensic toxicology (4). The paper highlights how these techniques generate high-dimensional data cubes that capture both spatial and spectral information.

Applications discussed include counterfeit drug detection, analysis of seized pharmaceuticals, and retrospective toxicological investigations. The authors also emphasize the importance of regulatory frameworks, data governance, and explainability in adopting AI-based methods in forensic environments.

Why influential: This review is influential because it expands the scope of forensic spectroscopy beyond point analysis to spatially resolved imaging, while also addressing the critical non-technical challenges associated with AI adoption in forensic science.

5. FT-IR Analysis of Soil for Forensic Geolocation (2025)

Force and Elkins provide a detailed review of FT-IR spectroscopy for soil analysis, focusing on its application to forensic geolocation (5). The paper describes how variations in organic matter, mineral composition, and environmental factors produce unique spectral fingerprints that can be used to differentiate soils.

The authors also discuss sampling protocols, preprocessing methods, and statistical approaches, highlighting the need for standardization across studies to improve comparability and evidentiary reliability.

Why influential: Soil evidence has long been valuable in forensic investigations, but this work elevates its analytical rigor by promoting standardized spectroscopic methodologies and chemometric analysis, thereby enhancing its utility in modern forensic science.

6. Detection of Drug Metabolites in Urine (2025)

Yu et al. demonstrate the use of ATR FT-IR spectroscopy combined with principal components analysis (PCA), partial least squares–discriminant analysis (PLS-DA), and OPLS-DA for detecting drug metabolites in urine (6). The method achieves detection limits as low as 0.02 mg/mL without requiring sample extraction or separation.

The study highlights the ability of vibrational spectroscopy to capture subtle differences in molecular composition within complex biological matrices, enabling rapid and non-invasive drug screening.

Why influential: This work is important because it offers a practical alternative to traditional chromatographic methods, significantly reducing analysis time and complexity while maintaining sensitivity and specificity.

7. Handheld NIR for Bone Identification (2026)

Weisleitner et al. explore the use of handheld NIR spectroscopy combined with artificial neural networks (ANNs) for distinguishing human and animal bones (7). The study demonstrates high classification accuracy and highlights the potential for real-time, on-site analysis.

The use of portable instrumentation represents a major advancement, enabling forensic investigators to perform preliminary analyses directly at crime scenes without sample destruction.

Why influential: This study exemplifies the transition of spectroscopy from the laboratory to the field, providing a rapid, non-destructive, and user-friendly tool for forensic practitioners.

8. Bloodstain Aging in Tropical Environments (2026)

Kamaruzaman et al. conduct a comprehensive comparison of Vis (visible) reflectance, ATR FT-IR, and Raman spectroscopy for estimating bloodstain TSD under tropical outdoor conditions (8). The study accounts for environmental variability, including humidity and temperature fluctuations, which significantly influence spectral changes with time..

The results demonstrate that while all techniques provide valuable information, micro-Raman spectroscopy achieved the highest predictive accuracy when combined with partial least squares (PLS) modeling.

Why influential: This work is particularly valuable because it addresses environmental realism, a critical factor often overlooked in laboratory studies, thereby improving the robustness and applicability of forensic models.

9. Trends in DNA Analysis of Skeletal Remains (2026)

Luo et al. present a bibliometric analysis of DNA research in aged skeletal remains, highlighting trends in methodology, collaboration, and technological innovation (9).

The study underscores the increasing integration of advanced analytical techniques, including spectroscopy, with genetic analysis.

Why influential: While not focused solely on spectroscopy, this paper provides important context for the broader evolution of molecular forensic analysis, emphasizing interdisciplinary integration and technological convergence.

10. Portable NIR for Cocaine and Adulterant Detection (2026)

Soriano-Hernández et al. develop a portable NIR spectroscopic method for simultaneously quantifying cocaine and common adulterants using PLS models (10). The method demonstrates high accuracy and reproducibility across real seized samples.

The ability to analyze multiple analytes in a single measurement represents a significant advancement over traditional single-compound approaches.

Why influential: This work is impactful due to its direct applicability in law enforcement and public health, enabling rapid, on-site drug analysis with minimal infrastructure.

Final Summary

The ten papers reviewed here collectively illustrate the rapid evolution of molecular spectroscopy in forensic science. Key themes include the transition toward non-destructive and in situ analysis, the integration of advanced chemometric and machine learning techniques, and the increasing importance of portability and real-world applicability.

These developments are not merely incremental; they represent a fundamental shift in how forensic evidence is analyzed, interpreted, and presented.

Conclusion

Molecular spectroscopy has firmly established itself as a cornerstone of modern forensic analysis. The innovations highlighted in this review demonstrate that the field is moving toward more rapid, accurate, and interpretable analytical methods that can be deployed directly at crime scenes.

Future progress will depend on continued advances in instrumentation, algorithm development, and standardization, as well as collaboration between scientists, legal professionals, and regulatory bodies. As these challenges are addressed, spectroscopy will play an increasingly central role in delivering reliable and defensible forensic evidence for legal investigations and in the courtroom.

References

(1) Murali, K.; Murugan, D.; Pathak, R.; Chauhan, A.; Munjal, S.; Usha, S. P.; Shrivastav, A. M. Forensic Detection: A Comprehensive Review of SERS Mechanisms and Applications. ACS Appl. Opt. Mater. 2026, 4 (in press). DOI: 10.1021/acsaom.6c00017.

(2) Cano-Trujillo, C.; Ortega-Ojeda, F. E.; García-Ruiz, C.; Montalvo, G. Forensic Estimation of Semen Stains’ Time Since Deposition on Porous Substrates Using ATR-FTIR and Raman Spectroscopy Supported by OPLS-DA Models. Forensic Chem. 2026, 40, 100734. DOI: 10.1016/j.forc.2026.100734.

(3) Chen, Q.; Qian, X.; Xiao, H.; Xia, L.; Deng, S. Interpretable Machine Learning for Forensic Post-Mortem Interval Prediction: SHapley Additive ExPlanations Analysis of Corneal ATR-FTIR Spectral Features. Microchem. J. 2026, 197, 117263. DOI: 10.1016/j.microc.2026.117263.

(4) Pérez-Beltrán, C. H.; Jiménez-Carvelo, A. M.; Sandoval-Sicairos, E. S.; Osuna-Martínez, L. U.; Santos-Ballardo, C. L.; Carrazco-Ávila, P. Y.; Cuevas-Rodríguez, E. O.; Cuadros-Rodríguez, L. Machine Learning and Optical Imaging for Pharmaceutical Forensic Toxicology: A Comprehensive Review. J. Pharm. Biomed. Anal. Open 2026, 100104. DOI: 10.1016/j.jpbao.2026.100104.

(5) Force, J.; Elkins, K. M. FTIR Spectroscopic Analysis of Soil in Forensic Science. Front. Anal. Sci. 2025, 5, 1716867. DOI: 10.3389/frans.2025.1716867.

(6) Yu, Y.; Chen, T.; Yuan, L.; et al. Detection of Common Drug Metabolites in Urine Using Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR). Forensic Sci. Med. Pathol. 2025, 21 (6), 1617–1625. DOI: 10.1007/s12024-025-01017-4.

(7) Weisleitner, K.; Wöss, C.; Kampik, L.; Huck, C. W.; Arora, R.; Brunner, A.; Zelger, B.; Schirmer, M.; Pallua, J. D. Rapid Forensic Differentiation of Human and Animal Bones Using Handheld Near-Infrared Spectroscopy and Deep Learning. Spectrochim. Acta, Part A 2026, 313, 126657. DOI: 10.1016/j.saa.2025.126657.

(8) Kamaruzaman, N. U.; Khyasudeen, M. F.; Jamil, A. K. M.; Low, K. H. Benchmarking Spectroscopic-Chemometric Models for Human Bloodstain Time Since Deposition in Tropical Outdoor Microenvironments. Spectrochim. Acta, Part A 2026, 317, 127651. DOI: 10.1016/j.saa.2026.127651.

(9) Luo, J.; Hua, Z.; Chen, J.; et al. Global Trends in DNA Research on Aged Human Skeletal Remains: A Bibliometric Analysis (1989–2024). Int. J. Legal Med. 2026, 140 (3), 605–619. DOI: 10.1007/s00414-025-03672-2.

(10) Soriano-Hernández, S.; Cruz, J.; Muñoz-Bartual, M.; Cervera, M. L.; Sáez-Hernández, R. Rapid and Simultaneous Quantification of Cocaine and Adulterants in Seized Samples Using Portable NIR Spectroscopy and Chemometrics. Vib. Spectrosc. 2026, 137, 103912. DOI: 10.1016/j.vibspec.2026.103912.