Decoding Fingerprint Aging: Leveraging GC×GC–TOF-MS for Forensic Chemical Profiling

Traditional fingerprint analysis relies on ridge pattern matching, but chemical profiling opens a new forensic dimension—estimating the age of prints and reconstructing timelines. In this interview, Petr Vozka from California State University, Los Angeles, discusses how comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC–TOF-MS) enables high-resolution detection of subtle, time-dependent changes in fingerprint residues. He also outlines the chemical transformations fingerprints undergo—from rapid loss of volatiles to oxidative lipid degradation—and explains how chemometric modeling can transform these changes into predictive aging tools.

You are currently involved in analyzing the chemical composition of fingerprints and how they change over time. Please can you discuss how comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC–TOF-MS) enhances the detection of age-related chemical changes in fingerprints?

At California State University, Los Angeles, our laboratory collaborates closely with the School of Criminal Justice and Criminalistics to identify chemical markers that can be used to estimate the age of fingerprints and determine the timing of activities such as alcohol consumption. Traditionally, fingerprint analysis has focused on matching ridge patterns between latent and known fingerprints. However, chemical analysis of fingerprints is not yet routinely implemented in forensic assessments, and a significant number of recovered prints are unsuitable for this approach, often due to poor quality or smudging.

Chemical analysis provides a complementary route that can expand the forensic value of fingerprints. GC×GC–TOF-MS offers unparalleled resolution and sensitivity, allowing for detailed chemical profiling of complex, low-abundance mixtures. These capabilities are particularly valuable for monitoring the subtle chemical transformations that occur as fingerprint residues age. When coupled with robust aging models, GC×GC–TOF-MS can support forensic investigations by enabling more accurate event reconstruction and suspect timeline verification.

How do fingerprint components change over time?

Fingerprint composition is dynamic and evolves through a range of chemical and physical processes. Immediately after deposition, the most volatile constituents begin to evaporate. Over subsequent days, semi-volatile compounds and lipids such as fatty acids undergo oxidative degradation, producing new oxygenated species. These reactions continue over weeks or months, often leading to the formation of high-molecular-weight products that contribute to a tacky or resinous residue. Proteins and amino acids from eccrine sweat also degrade over time, which can complicate the chemical signature further.

Additionally, fingerprint residues interact with the surrounding environment, absorbing atmospheric particles, pollutants, and microbial communities, all of which may alter the chemical profile. A detailed understanding of these temporal transformations is essential for developing accurate aging models and increasing the evidentiary value of latent prints.

How do you envision the application of your fingerprint aging models in real-world forensic investigations?

Our goal is to create fingerprint aging models that are compatible with current forensic workflows. This includes developing sampling protocols that mirror standard procedures used by crime scene investigators. A key challenge lies in balancing analytical sophistication with field practicality—clearly, deploying GC×GC–TOF-MS at every crime scene is neither feasible nor necessary.

Instead, we envision these models being used in forensic laboratories to provide temporal context to fingerprint evidence. For example, if a suspect claims to have visited a location several hours before a crime, chemical aging analysis could help determine whether their fingerprint aligns with that timeframe. Such insight could serve to corroborate or challenge statements, thus providing critical context to investigative timelines.

What are the main advantages of GC×GC–TOF-MS for complex forensic samples versus traditional GC–MS methods?

Fingerprint residues represent chemically diverse and compositionally complex matrices. GC×GC–TOF-MS provides critical advantages in this context. Its orthogonal separation mechanism significantly enhances peak capacity, which minimizes coelution and allows for better resolution of structurally similar compounds that evolve during fingerprint aging.

TOF-MS enables high-speed spectral acquisition, which, when combined with sharper chromatographic peaks from modulation, enhances sensitivity to trace-level compounds, such as volatile degradation products or oxidation markers. This level of detail is often unattainable with one-dimensional GC–MS systems.

Additionally, the rich data sets produced by GC×GC–TOF-MS are well-suited for chemometric analyses, allowing us to identify and quantify age-related chemical trends with high reproducibility. This comprehensive profiling is instrumental in building reliable and predictive forensic models.

How does precise and consistent sample preparation contribute to the reliability of forensic chromatography results?

That is an excellent question. Sample preparation is arguably the most critical determinant of analytical reliability. Every instrument has inherent limitations in sensitivity and precision, but these are magnified when sample treatment is inconsistent. In forensic contexts, sample collection often occurs under uncontrolled conditions, introducing variability in sample quantity and integrity.

To address this, we are developing models based on compound ratios that minimize sensitivity to sampling inconsistencies. However, post-collection processing (extraction, concentration, and injection) must still be tightly controlled. Standardizing these steps is essential for ensuring data comparability and reproducibility, which are prerequisites for admissibility in forensic and legal settings.

What are some common challenges forensic scientists face when analyzing trace compounds in fingerprints or other biological residues?

Trace evidence analysis is inherently difficult due to the low abundance of target analytes and the complexity of biological matrices. In fingerprints, for example, endogenous compounds may degrade or react with environmental agents, while exogenous contaminants can obscure meaningful signals.

GC×GC–TOF-MS offers the resolving power necessary to disentangle these complex mixtures, but the technique also demands rigorous quality control, specialized expertise, and often still suffers from a lack of fully curated compound libraries specific to fingerprint constituents. Moreover, ensuring legal defensibility requires meticulous documentation and validation. Challenges that are magnified when dealing with trace-level analytes and untargeted workflows.

What emerging trends or technologies do you believe will shape the future of forensic analysis?

I think that one of the most transformative trends in (not just) forensic science is the integration of chemometrics and machine learning to interpret high-dimensional data sets from techniques such as GC×GC–TOF-MS. As forensic chemistry moves beyond targeted assays toward untargeted or semi-targeted analysis of complex mixtures, the ability to extract meaningful information from large data sets is becoming essential.

In our fingerprint aging research, we apply chemometric techniques to identify key molecular markers and temporal trends, reduce data dimensionality, and improve model robustness. We anticipate that these data-driven approaches will become increasingly central, not just in fingerprint analysis but also across the broader spectrum of forensic applications.

Petr Vozka is an associate professor of chemistry and biochemistry at California State University, Los Angeles, USA, and is the director of the Complex Chemical Composition Analysis Laboratory (C³AL). He holds a B.S. in chemistry and chemical technologies, an M.S. in chemistry and technology of fuels and environment, and a Ph.D. with a specialization in analytical chemistry of liquid transportation fuels. His research centers on the advanced characterization of complex chemical mixtures, such as alternative fuels, microplastics, and fingerprints, using state-of-the-art analytical techniques such as comprehensive two-dimensional gas chromatography (GC×GC) and mass spectrometry. Vozka has authored numerous peer-reviewed publications, contributing to analytical methodologies for fuels and environmental systems.