Solid-phase microextraction (SPME) has emerged as a powerful tool used for extracting analytes from complex matrices, offering high sensitivity, automation potential, and high-throughput efficiency. Despite its advantages, its performance is often limited by the selectivity and physicochemical properties of conventional coatings. This study addresses the limitations of conventional SPME coatings for monitoring environmental contaminants by introducing a nitrogen-rich covalent organic framework (COF) as an SPME extraction phase/coating. The COF-based SPME coating was implemented in a coated-blade spray (CBS) device format and was used to develop a robust analytical workflow that combined ambient mass spectrometry ionization via CBS for rapid screening, followed by LC-MS/MS for confirmation and quantification. Statistical validation using a t test showed that only 3 of 43 analytes exhibited statistically significant differences in loss during the microdesorption step of the CBS-MS/MS screening. The results demonstrate that the COF-based SPME coating facilitates simultaneous extraction of analytes with varying polarities from river samples without altering the sample matrix. The final protocol achieved limits of quantification ranging from 0.025 to 5 ng mL–1. The method was successfully applied to river samples, quantifying the target analytes and demonstrating that LC separation remains essential for confirmation. This work highlighted the effectiveness of a COF-based SPME coating as a next-generation extraction phase that simplifies rapid ambient MS screening, followed by traditional LC-MS/MS for confirmation and quantification, all within a single coated SPME device.

Tandem mass spectrometry relies on unique parent-to-product transitions for selective analysis. For sets of isomers or isobars that have identical behaviors in multiple separation dimensions (e.g., LC retention, m/z), quantitation is challenging owing to feature convolution. For example, recent environmental analysis of the enantiomers of O-desmethylvenlafaxine (ODV), an anti-depressant manufactured in a racemic mixture, identified tramadol (TRA, a racemic painkiller) as a co-eluting interference. Here, we demonstrate that differential ion mobility spectrometry (DMS) coupled with chiral LC-MS2 can be used to separate and quantify the enantiomers of ODV and TRA. This method was applied to six wastewater influent samples from an Ontario municipal wastewater plant, where the sum of the enantiomeric concentrations was statistically identical to the racemic concentrations observed on reverse-phase LC-MS2 (t-test, α = 0.05, p-value = 0.26 for ODV and p-value = 0.47 for TRA). We also identify low-intensity product ions specific to ODV that enable isolation and quantitation via chiral LC-MS2 alone, albeit at a relatively high limit of quantitation (LOQ) in comparison to the most intense MRM transition (m/z 264 → 58). Using our chiral (LC × DMS)-MS2 method, the instrumental LOQ of each enantiomer of TRA was determined to be 0.67 ng mL-1 and 5.0 ng mL-1 for the enantiomers of ODV.

Per- and polyfluoroalkyl substances (PFAS) are of increasing concern due to their environmental persistence, bioaccumulative nature, and association with adverse health outcomes. The growing need for large-scale monitoring and long-term exposure assessment studies necessitates the development of high-throughput, sustainable analytical methodologies. In this work, a solid-phase microextraction-microfluidic open interface-mass spectrometry (SPME-MOI-MS) platform was developed for the rapid screening of 18 PFAS compounds in human plasma. By bypassing the liquid chromatography separation, the method achieves high-throughput performance with an average analysis time of 3.7 min per sample. A novel SPME coating, comprising hydrophilic-lipophilic balanced mixed-mode weak anion exchange sorbent (HLB-WAX) particles embedded in a polyacrylonitrile (PAN) binder, enabled efficient extraction and effective cleanup of complex biological matrices, facilitating direct MS analysis. The method demonstrated excellent linearity (1-100 ng/mL) and low limits of detection (0.11-0.86 ng/mL) across target PFAS compounds. For practical application, PFOA and PFNA were detected in human plasma samples during these initial investigations, demonstrating the potential of the SPME-MOI-MS approach for large-scale PFAS biomonitoring and exposure assessment.

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental pollutants that pose potential risks to ecosystems and human health. Prior to mass spectrometric analysis of environmental samples, it is necessary to separate PFAS from compounds that can cause ion suppression and compromise analyte identification and quantification accuracy. Although liquid chromatography-mass spectrometry (LC-MS) is the gold standard for PFAS trace analysis, some PFAS species still coelute in the LC dimension and could benefit from an orthogonal dimension of separation. Moreover, an additional orthogonal dimension of separation could potentially aid in the identification of unknown fluorinated species (e.g., those identified within a specified mass-defect range). Here, we investigate the sequential use of LC and differential mobility spectrometry (DMS) separation to analyze 34 PFAS species. Upon incorporating DMS in a two-dimensional (2D) separation scheme, we observed baseline resolution of 29 compounds in the 2D LC × DMS space, with partial resolution of the remaining five. In comparison, only five PFAS compounds were baseline-resolved in 1D LC experiments. Because DMS measurements can be acquired in milliseconds, targeted 2D LC × DMS-MS2 analyses operate on the same time scale as LC-MS2 analysis. However, the limits of quantitation for PFAS using the 2D LC × DMS-MS2 method are slightly higher than those achieved by the state-of-the-art LC-MS2 method owing to ion fragmentation within the energetic DMS environment. Nevertheless, distinct trends observed in the 2D separation space for the various PFAS subclasses will facilitate analyte identification of unknown species in future nontargeted analyses. Finally, we assessed the feasibility of our method for quantifying PFAS in a series of wastewater samples obtained from a Southern Ontario wastewater treatment plant. We were successful in quantifying PFOS, although the concentrations determined were consistently higher than those measured with LC-MS2.

Liquid chromatography (LC) is a cornerstone of analytical separations, but comparing the retention times (RTs) across different LC methods is challenging because of variations in experimental parameters such as column type and solvent gradient. Nevertheless, RTs are powerful metrics in tandem mass spectrometry (MS2) that can reduce false positive rates for metabolite annotation, differentiate isobaric species, and improve peptide identification. Here, we present Graphormer-RT, a novel graph transformer that performs the first single-model method-independent prediction of RTs. We use the RepoRT data set, which contains 142,688 reverse phase (RP) RTs (from 191 methods) and 4,373 HILIC RTs (from 49 methods). Our best RP model (trained and tested on 191 methods) achieved a test set mean average error (MAE) of 29.3 ± 0.6 s, comparable performance to the state-of-the-art model which was only trained on a single LC method. Our best-performing HILIC model achieved a test MAE = 42.4 ± 2.9 s. We expect that Graphormer-RT can be used as an LC "foundation model", where transfer learning can reduce the amount of training data needed for highly accurate "specialist" models applied to method-specific RP and HILIC tasks. These frameworks could enable the machine optimization of automated LC workflows, improved filtration of candidate structures using predicted RTs, and the in silico annotation of unknown analytes in LC-MS2 measurements.