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37 results for “Desorption”
Fig. 2 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 2. Workflow for sample preparation and injection. Culture samples were filtered and dried (A–B). Dried filter papers were placed in clean vials (C) and then resuspended in methanol (D) before being extracted with Chloroform (E). Water was added (F) and subsequently, the chloroform layer was aliquotted into GC vials (G) for further sample preparation. Extracts were dried (H) and then derivatized using a two-step methoximation/silylation process to yield derivatized extracts (I). 9-μL aliquots of derivatized extracts were automatically transferred to microvial inserts in thermal desorption tubes for injection (J) using an initial solvent vent step to remove excess solvent and derivatisation reagents (K), followed by thermal desorption to a cooled PTV inlet and subsequent splitless injection to the GC × GC-TOFMS system. Non-volatile residues from the extracts remained in the microvial insert for subsequent disposal (L). See text for details.
Fig. 4 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 4. From left to right: results of principal component analysis of the raw data (autoscaled), similarly scaled data normalised to class-specific TUPA, and the normalised, scaled data using the selected features from the FS-CR routine. Quality control samples were not included in the feature selection routine, and are displayed as filled icons connected to their corresponding replicate with a straight line, following projection into the optimised principal component space. Confidence ellipses were drawn about each sample class for a confidence interval of 0.95. Note the convention: DUN refers to D. tertiolecta samples, CO refers to co-culture samples, and BAC refers to P. italicus R11 samples.
Fig. 5 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 5. DESI-MS/MSI of OPDA and OPC-8 in the developing Phaseolus vulgaris seeds. (a) Optical image of the seed section for OPDA analysis. (b) MS/MS spectrum of precursor ion at m/z 291.1966 ± 1 Da obtained at the target enhanced mode for m/z 165.1. (c) Ion image at m/z 165.1300. (d) Optical image of the seed section for OPC-8:0 analysis. (e) MS/MS spectrum of precursor ion at m/z 293.2122 ± 1 Da obtained at the target enhanced mode for m/z 225.1. Ion images at m/z (f) 223.1400 and (g) 231.2142. Scale bar = 2 mm. Compound names are defined in Table 1.
Fig. 4 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 4. LC-ESI-MS/MS analysis of JA-related compounds in the extracts from the radicle and seed coat of developing Phaseolus vulgaris seeds. MS/MS spectra of peaks at (a) 5.3 min in Fig. 3c, (b) 5.3 min in Fig. 3d, (c) 6.5 min in Fig. 3c and (d) 6.5 min in Fig. 3d and (e) 6.3 min in Fig. 3e and (f) 6.3 min in Fig. 3f and (g) 6.4 min in Fig. 3e, (h) 6.4 min in Fig. 3f, (i) 6.7 min in Fig. 3e, and (j) 6.7 min in Fig. 3f. Compound names are defined in Table 1.
Fig. 2 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 2. LC-ESI-MS/MS analysis of JA-related compound standards. Spectra of (a) OPDA, (b) OPC-8:0, and (c) JA standards. Compound names are defined in Table 1.
Fig. 1 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 1. DESI-MSI analysis of JA-related compounds in the developing Phaseolus vulgaris seeds. (a) Optical image of the section. (b) Mass spectrum obtained from the section. Ion images of m/z (c) 277.2172, (d) 291.1953, and (e) 293.2117. Three different developing seeds were analyzed, and the results from one are shown as representative data. Scale bar = 2 mm. Compound names are defined in Table 1.
Fig. 3 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 3. LC-ESI-MS analysis of JA-related compounds in the extracts from the radicle and seed coat of developing Phaseolus vulgaris seeds. Base peak chromatogram of m/z 277.2173 ±10 ppm for (a) radicle and (b) seed coat, m/z 291.1966 ± 10 ppm for (c) radicle and (d) seed coat, and m/z 293.2122 ± 10 ppm for (e) radicle and seed coat, respectively. Peaks with arrow indicates JA-related compounds: (a) and (b) αLA, (c) and (d) OPDA, and (e) and (f) OPC-8:0. Compound names are defined in Table 1.
Rapid Diagnosis of Prosthetic Joint Infection by Matrix-assisted Laser Desorption
ClinicalTrials.gov study NCT03717090. IPD Sharing: UNDECIDED. Countries: 1. Publications: 6.
Photon Stimulated Desorption of MgS as a Potential Source of Sulfur in Mercury's Exosphere
<p>Experimental data for x-ray photoelectron spectroscopy (XPS) and resonance enhanced multiphoton ionization (REMPI) characterization of the surface of magnesium sulfide (MgS) exposed to 193 nm UV photons. These data accompany the manuscript "Photon Stimulated Desorption of MgS as a Potential Source of Sulfur in Mercury’s Exosphere" 'submitted in April 2020 to the Journal of Geophysical Research - Planets. The 'Mg-1s' and 'S-2p' data were used to make the XPS image (Figure 1). The 'power' data were used to make the signal intensity vs. power images (Figures 2 and 3). The 'delay' data were used to fit Maxwellian velocity distributions, and the fits are included (Figure 4). The 'MC' data were the output results of the Monte Carlo model used to determined the density of sulfur as a function of altitude above Mercury (Figure 6).</p>
Data from: Sorption and desorption of bicyclopyrone on soils
<p class="Abstract">Bicyclopyrone is a herbicide that is targeted for the control of herbicide-resistant weeds. However, there is a lack of extensive data on its sorption and factors that control its sorption in the soil system. In this study, we evaluated a series of 25 different soils, with a variety of soil properties to assess if an empirical relationship could be developed to predict the sorption coefficient for bicyclopyrone. Overall, there were no statistically significant relationships observed with organic carbon, cation exchange capacity, or clay content. There solely was a moderate negative correlation with soil pH (R=-0.65). Additionally, Freundlich isotherm analysis suggests that the K<sub>D</sub> could be adequate to characterize the sorption behavior for the range of soils evaluated here.</p>
Desorption (degassing) of CO2 out of subbituminous coal
<p>The desorption process is observed as CO2 degassing out of the coal. After flooding the coal with CO2 up to 1600 psi, the sub-bituminous coal sample is removed from the pressure chamber and exposed to atmospheric conditions. The CO2 desorption occurs mostly through the cleats and fractures in the coal (highlighted with white marker), evidenced by the stream of bubbles of the soapy water. Also, tiny bubbles burst randomly in the coal bulk matrix, indicating the location of microfractures conducting the CO2.</p> <p>Details of the research in: Vega-Ortiz, Carlos . 2021. Optimization of CO2 Mass Transport and Storage at In-situ Conditions in Two Unconventional Plays: Coalbed Methane and Carbonaceous Mudstones. Ph.D. Thesis. The University of Utah.</p>
Fig. 3 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 3. Example Total Ion Current (TIC) chromatograms from each sample class.
Data from: Sorption and desorption of bicyclopyrone on soils
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Does desorption affect the length distributions of nanowires?
<p>State-of-the art models for statistical properties within the nanowire ensembles consider influx of precursors, reflection and surface diffusion of adatoms. These models predict a delay in the nanowire growth start and the evolution toward an asymmetric length distribution. We demonstrate here the effect of desorption of the nanowire material, which has not been considered so far in studies of the nanowire length distributions. We show that at the very beginning of growth the length distribution should be asymmetric due to the slow nucleation of nanowires. At longer times, the length distribution acquires a symmetric Gaussian shape due to the increased weight of desorption. The width of this distribution is larger than Poissonian and increases for higher ratio of desorption over deposition rate. Our model is consistent with the length evolution of organized self-catalyzed GaAs nanowires. We outline that desorption of the nanowire material should be minimized to achieve arrays of highly identical nanowires. These results are relevant for a wide variety of material systems.</p>
Simulating desorption in vacuum from a porous soil, II: argon and water
<p>This dataset contains simulated data of desorption events from a Monte Carlo simulation of desorption and diffusion in 3D sphere packings. The data simulate lunar vacuum conditions.<br> The gas species in these simulations have microphysical parameters consistent with adsorbed argon and water.<br> The output may enable better representations of the desorption process in global exosphere models of solar system bodies.</p>
Advanced Development of Desorption Electrospray Ionization Mass Spectrometry for Intraoperative Molecular Diagnosis of Brain Cancer Using Pathology Biopsies
ClinicalTrials.gov study NCT06387979. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Fig. 1 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 1. Cross validated receiver operator characteristics suggest that the calculated model is robust, and improves with more iterations. Light blue lines show the results of further iterations, and red lines show the results of fewer iterations. Each line is semi-transparent, but the AUC is close to 1 in all cases. Calculation of the classification scores was based off the named class (Class 1), versus everything else (Class 0). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
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