An analytical workflow for the analysis of olefins in gasoline that combines selective bromination and comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry ...(GC×GC-TOFMS) with discovery-based analysis is reported. First, a standard mix containing n-alkanes, 1-alkenes, and aromatic species was brominated and quantified using % reacted as a metric for each compound class, defined as the difference in the total peak area between the brominated and original samples normalized to the original sample. The average % reacted (1 s.d.) values were −1.45% (2.8%) for the alkanes, 99.5% (0.4%) for the alkenes, and 6.7% (11.6%) for the aromatics, demonstrating excellent selectivity toward the alkenes with only minor aromatic bromination. The bromination chemistry was then applied to gasoline, followed by GC×GC-TOFMS analysis of the original and brominated gasoline. This GC×GC-TOFMS data set was then submitted to the supervised discovery tool tile-based F-ratio analysis (FRA), which reduced the large data set to only the chromatographic regions which distinguish between the original and brominated gasoline samples. FRA discovered 314 hits, 56 of which were determined statistically significant using combinatorial null distribution analysis (CNDA), a permutation-based significance test. Since the brominated olefins elute in an uncrowded region of the 2D chromatogram and have no signal in the original sample, their discoverability was greatly increased relative to the original olefins. By combining the information gained from brominated olefin standards and the structured patterns of the GC×GC separations, the top hits were identified as the dibromoalkane products of mono-olefins, with five C5 mono-olefins identified on a species level. The analytical workflow has broad implications for using selective reaction chemistries to facilitate supervised discovery by targeting desired compound classes.
Multimodal mass spectrometry (MMS) incorporates an imaging modality with probe‐based mass spectrometry (MS) to enable precise, targeted data acquisition and provide additional biological and chemical ...data not available by MS alone. Two categories of MMS are covered; in the first, an imaging modality guides the MS probe to target individual cells and to reduce acquisition time by automatically defining regions of interest. In the second category, imaging and MS data are coupled in the data analysis pipeline to increase the effective spatial resolution using a higher resolution imaging method, correct for tissue deformation, and incorporate fine morphological features in an MS imaging dataset. Recent methodological and computational developments are covered along with their application to single‐cell and imaging analyses.
Recent developments are highlighted for multimodal mass spectrometry; this includes approaches integrating microscopy and probe‐based mass spectrometry for targeted analysis and approaches providing mass spectrometry spatial resolution enhancements for samples ranging from single organelles, individual cells, and tissues.
Changing emissions regulations, fuel price fluctuations and development of new energy-intensive mission systems are driving both component technological innovation and require more sophisticated ...controls on-board modern ships. Historically, numerous components and systems aboard ships perform energy conversions from one form to another. Conversion from chemical to thermal to kinetic to electrical and back to thermal energy are common. Today, subsystems are designed separately without opportunity for optimizing overall system-of-systems performance. By modeling multiple system domains simultaneously and applying the Second Law of Thermodynamics, this progresses towards overall ship system optimization. Exergy, the available energy for performing useful work, and exergy destruction was calculated in each energy conversion process. Knowledge of the exergy flows leads to a system-of-systems optimization to minimize overall exergy destruction translating into lower emissions and fuel costs. This can eventually result in more efficient, smaller and lighter shipboard systems. A model of notional shipboard power and cooling system is presented that features a pulsed load (an electromagnetic railgun) and have implemented both traditional and exergy-based control schemes. This paper will briefly review the modeling, which has been previously published, and present results using exergy destruction for optimization of the ship system controls.
•Model predictive exergy-based control strategy developed to regulate pulsed power cooling system flow rate.•Model-based approach reduced fuel consumption as compared to two fixed flow rate cases.•Exergy destruction minimization lead to reduced energy consumption.
We investigate the extent to which comprehensive three-dimensional gas chromatography (GC3) provides a signal enhancement (SE) and a signal-to-noise ratio enhancement (S/NRel) relative to ...one-dimensional (1D)-GC. Specifically, the SE is defined as the ratio of the tallest 3D peak height from the GC3 separation to the 1D peak height from the unmodulated 1D-GC separation. A model is proposed which allows the analyst to predict the theoretically attainable SE (SE T) based upon the peak width and sampling density inputs. The model is validated via comparison of the SE T to the experimentally measured SE (SE M) obtained using total-transfer GC3 (100% duty cycle for both modulators) with time-of-flight mass spectrometry detection. Two experimental conditions were studied using the same GC3 column set, differing principally in the modulation period from the 1D to 2D columns: 4 s versus 8 s. Under the first set of conditions, the average SE M was 97 (±22), in excellent agreement with the SE T of 97 (±18). The second set of conditions improved the average SE M to 181 (±27), also in agreement with the average SE T of 176 (±26). The average S/NRel following correction for the mass spectrum acquisition frequency was 38.8 (±11.2) and 59.0 (±27.2) for the two sets of conditions. The enhancement in S/N is largely attributed to moving the signal to a higher frequency domain where the impact of “low frequency” noise is less detrimental. The findings here provide strong evidence that GC3 separations can provide enhanced detectability relative to 1D-GC and comprehensive two-dimensional gas chromatography (GC×GC) separations.
Tile-based Fisher ratio (F-ratio) analysis is emerging as a versatile data analysis tool for supervised discovery-based experimentation using comprehensive two-dimensional (2D) gas chromatography ...coupled with time-of-flight mass spectrometry (GC × GC-TOFMS). None the less, analyte identification can often be marred by poor 2D resolution and low analyte abundance relative to overlapping compounds. Linear algebra-based chemometric methods, in particular multivariate curve resolution alternating least squares (MCR-ALS), parallel factor analysis (PARAFAC) and PARAFAC2, are often applied in an effort to address this situation. However, these chemometric methods can fail to produce an accurate spectrum when the analyte is at low 2D resolution and/or in low relative abundance. To address this challenge, we introduce class comparison enabled mass spectrum purification (CCE-MSP), a method that utilizes the underlying requirement for signal consistency of the background interference compounds between the two classes in the F-ratio analysis to purify the mass spectrum of the analyte hits. CCE-MSP is validated using a dataset obtained for a neat JP-8 jet fuel spiked with 14 sulfur containing compounds at two levels (15 ppm and 30 ppm), using the p-value and lack-of-fit (LOF) for each analyte hit as consistency metrics. A purified mass spectrum was produced for each spiked analyte hit and their mass spectrum match value (MV) was compared to the MV obtained by MCR-ALS, PARAFAC, and PARAFAC2. The resulting MV for CCE-MSP were found to be as good or better than these chemometric methods, eg., for 2-butyl-5-ethylthiophene with an analyte-to-interference relative signal abundance of 1:87 and a 2D resolution of 0.2, CCE-MSP produced a MV of 831, compared to 476 for MCR-ALS, 403 for PARAFAC, and 336 for PARAFAC2. CCE-MSP is also extended to obtain the purified spectrum for more than one analyte, eg., two analyte hits in overlapping hit locations. The spectra produced by CCE-MSP can also be utilized as estimates to facilitate quantitative signal decomposition using MCR-ALS.
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•Tile-based Fisher ratio analysis enables mass spectrum purification.•Identification of pure interference mass channels provide the leverage.•Mass spectra obtained can be better than those obtained by chemometric decomposition.•The method is well suited to situations of severe chromatographic overlap.
Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a ...brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary brain-wide and single-cell biochemical mapping using MEISTER, an integrative experimental and computational mass spectrometry (MS) framework. Our framework integrates a deep-learning-based reconstruction that accelerates high-mass-resolving MS by 15-fold, multimodal registration creating three-dimensional (3D) molecular distributions and a data integration method fitting cell-specific mass spectra to 3D datasets. We imaged detailed lipid profiles in tissues with millions of pixels and in large single-cell populations acquired from the rat brain. We identified region-specific lipid contents and cell-specific localizations of lipids depending on both cell subpopulations and anatomical origins of the cells. Our workflow establishes a blueprint for future development of multiscale technologies for biochemical characterization of the brain.
•Low flow conditions are employed with flow modulation.•Dynamic pressure gradient modulation in full modulation mode is utilized.•Fully modulated peaks provide enhanced signal and low limit of ...detection.•The evaluation of the quality of the data using chemometric tools is provided.•Decomposition of poorly resolved analytes at low concentration was successful.
Dynamic pressure gradient modulation (DPGM) is investigated for comprehensive two-dimensional gas chromatography (GC × GC) with time-of-flight mass spectrometry (TOFMS) detection. With DPGM, a commercial pneumatic “pulse” valve is opened to introduce a suitably high auxiliary gas pressure at a T-junction connecting the first dimension (1D) and second dimension (2D) columns during the modulation period (PM), temporarily stopping the 1D flow. The valve is then closed for the duration of a pulse width (pw) to “re-inject” temporally focused 1D eluate onto the 2D column for separation. This flow modulation technique is observed to be compatible with TOFMS detection using a 2D flow rate of 4 ml/min for the separation of a 90-component test mixture. A 25 min separation window using a PM = 1 s and pw = 200 ms for full modulation (and 100% duty cycle) provided an average 1Wb = 4.5 s and 2Wb = 130 ms for a 2D peak capacity of nc,2D = 2700 (100 peaks per min). The detector response enhancement factor (DREF) serves as a metric for the enhanced sensitivity of the modulated relative to the unmodulated 1D peaks, with DREFs ranging between 10 and 20 and about a 5-fold improvement in signal-to-noise ratio (S/N). The bilinear “quality” of the GC × GC data is studied using the chemometric method parallel factor analysis (PARAFAC). Since PARAFAC requires sufficiently trilinear data, the reproducibility of the 2D peak shape for a given analyte is confirmed using lack-of-fit (LOF) and percent variation (R2) metrics. The limit-of-detection (LOD) for the representative analyte hexadecane is determined using PARAFAC, providing an LOD of 0.7 ppb (±0.03 ppb) for three replicates. Seven heavily overlapped analytes are also fully resolved by PARAFAC down to the part-per-million (ppm) concentration level, producing reproducible spectra with a majority of spectral match values (MV) over 800 (RSD ≤ 7.1%). This study provides promising results for DPGM as a flow modulation technique compatible with GC × GC-TOFMS, providing high sensitivity data suitable for chemometric analysis.
Dynamic pressure gradient modulation (DPGM) in full modulation mode is optimized for comprehensive two-dimensional (2D) gas chromatography (GC × GC) with time-of-fight mass spectrometry (TOFMS) ...detection to obtain high peak capacity separations and demonstrate broad applicability for complex samples. A pulse valve introduces an auxiliary carrier gas flow at a T-union connecting the first dimension (1D) column to the second dimension (2D) column. At a sufficiently high auxiliary pressure (Paux) the 1D flow is temporarily stopped. Then, during each modulation period (PM) the valve is turned off briefly, a period termed the pulse width (pw), allowing the 1D effluent to essentially be reinjected onto the 2D column for the modulated separations. Modifications to the modulator assembly are provided to improve performance. Method optimization is demonstrated for a 116-component test mixture by tuning the Paux and the pw. For a PM = 2 s and 1F of 0.10 ml/min, the optimal pw and initial Paux selected were 200 ms and 330.9 kPa (33 psig), respectively. The 30 min separation of the test mixture provided a 1D peak capacity of 1nc = 330 and a 2D peak capacity of 2nc = 15, hence an ideal 2D peak capacity nc,2D = 1nc × 2nc = 4950. Likewise, the 2D peak capacity corrected for undersampling of the 1D separation was 4500 and corrected for both undersampling and sampling variation via statistical overlap theory was 4090. These results provide a 2-fold improvement in peak capacity relative to the previous DPGM study in full modulation mode for GC × GC-TOFMS. The optimized conditions were applied for a variety of applications: diesel fuel, derivatized cow serum, solid phase microextraction (SPME) of coffee headspace, and SPME of river water headspace. Additionally, the fraction of 2D separation space utilized (fcoverage), as defined by the minimum convex hull method, ranged from 0.60 to 0.85. We observed that any fcoverage correction to 2D peak capacity is highly sample dependent, since all samples, except for the diesel sample, were run with the same separation conditions, and yet the fcoverage ranged from 0.60 to 0.80.
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•Dynamic pressure gradient modulation in full modulation mode is optimized.•Modifications to modulator interface for improved performance are detailed.•Selection of optimal auxiliary gas pressure and pulse width is demonstrated.•Undersampling, statistical sampling variation, and surface coverage were all examined.•High peak capacity is achieved for various real samples under optimal conditions.
A new tile-based pairwise analysis workflow, termed 1v1 analysis, is presented to discover and identify analytes that differentiate two chromatograms collected using comprehensive two-dimensional ...(2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS). Tile-based 1v1 analysis easily discovered all 18 non-native analytes spiked in diesel fuel within the top 30 hits, outperforming standard pairwise chromatographic analyses. However, eight spiked analytes could not be identified with multivariate curve resolution-alternating least-squares (MCR-ALS) nor parallel factor analysis (PARAFAC) due to background contamination. Analyte identification was achieved with class comparison enabled-mass spectrum purification (CCE-MSP), which obtains a pure analyte spectrum by normalizing the spectra to an interferent mass channel (m/z) identified from 1v1 analysis and subtracting the two spectra. This report also details the development of CCE-MSP assisted MCR-ALS, which removes the identified interferent m/z from the data prior to decomposition. In total, 17 out of 18 spiked analytes had a match value (MV) > 800 with both versions of CCE-MSP. For example, MCR-ALS and PARAFAC were unable to decompose the pure spectrum of methyl decanoate (MVs < 200) due to its low 2D chromatographic resolution (∼0.34) and high interferent-to-analyte signal ratio (∼30:1). By leveraging information gained from 1v1 analysis, CCE-MSP and CCE-MSP assisted MCR-ALS obtained a pure spectrum with an average MV of 908 and 964, respectively. Furthermore, tile-based 1v1 analysis was applied to track moisture damage in cacao beans, where 86 analytes with at least a 2-fold concentration change were discovered between the unmolded and molded samples. This 1v1 analysis workflow is beneficial for studies where multiple replicates are either unavailable or undesirable to save analysis time.
