Evaluating polyvinylidene fluoride - carbon black composites as solid phase microextraction coatings for the detection of urinary volatile organic compounds by gas chromatography-mass spectrometry

Abstract

Volatile organic compounds (VOCs) are biomarkers of disease, which can be utilized for accurate diagnostics. The gold standard for VOC identification is gas chromatography-mass spectrometry (GC-MS) as it allows for structure elucidation and quantification. Headspace solid phase microextraction (HS-SPME) is often used in biomarker discovery due to its ability to preconcentrate VOCs prior to GC-MS analysis. However, HS-SPME GC-MS is time-consuming, expensive and requires trained personnel. Gas sensor arrays can detect VOC biomarkers at a point-of-care and therefore are more suitable for disease diagnostics in the clinic. Nevertheless, qualification and optimization of sensing layers is tedious as each VOC of interest needs to be tested individually. Therefore, using SPME fibers to extract VOCs and GC-MS to quantitate the analytes may be an efficient strategy with high throughput to tune sensing layers and increase analyte affinity. To investigate this, suspensions of polyvinylidene fluoride (PVDF) and polyvinylidene fluoride-carbon black (PVDF-CB) fabricated at varying concentration were immobilized on SPME fibers through physical deposition, used to extract urinary VOCs and were subject to GC-MS analysis. The addition of CB shows increased fiber performance in terms of total integrated signal and sensitivity toward individual VOCs. PVDF-CB fibers were compared to a commercial polydimethylsiloxane (PDMS) SPME fiber run using the same method. The PVDF-CB fiber outperformed the commercial fiber in detecting numerous urinary VOCs of interest. Results of this study show not only that custom SPME fiber performance can be evaluated through GC-MS analysis, but the capability of custom fibers to adsorb urinary VOCs can be tuned based on properties of interest. Hence, this method may be utilized as an analytical tool to characterize and tune gas sensing layers with high analytical throughput.