Partial Ionization Cross Sections of Organic Molecules
Ontology highlight
ABSTRACT:
SUBMITTER: Irikura K
PROVIDER: S-EPMC7347380 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Molecular ionization potentials (IP) and photoionization cross sections (σ) can affect the sensitivity of photoionization detectors (PIDs) and other sensors for gaseous species. This study employs several methods of machine learning (ML) to predict IP and σ values at 10.6 eV (117 nm) for a dataset of 1251 gaseous organic species. The explicitness of the treatment of the species electronic structure progressively increases among the methods. The study compares the ML predictions of the IP and σ values to those obtained by quantum chemical calculations. The ML predictions are comparable in performance to those of the quantum calculations when evaluated against measurements. Pretraining further reduces the mean absolute errors (ε) compared to the measurements. The graph-based attentive fingerprint model was most accurate, for which εIP = 0.23 ± 0.01 eV and εσ = 2.8 ± 0.2 Mb compared to measurements and computed cross sections, respectively. The ML predictions for IP correlate well with both the measured IPs (R 2 = 0.88) and with IPs computed at the level of M06-2X/aug-cc-pVTZ (R 2 = 0.82). The ML predictions for σ correlated reasonably well with computed cross sections (R 2 = 0.66). The developed ML methods for IP and σ values, representing the properties of a generalizable set of volatile organic compounds (VOCs) relevant to industrial applications and atmospheric chemistry, can be used to quantitatively describe the species-dependent sensitivity of chemical sensors that use ionizing radiation as part of the sensing mechanism, such as photoionization detectors.
| S-EPMC10152554 | biostudies-literature
Project description:Characterizing the photochemical reactivity of transient volatile organic compounds (VOCs) in our atmosphere begins with a proper understanding of their abilities to absorb sunlight. Unfortunately, the photoabsorption cross-sections for a large number of transient VOCs remain unavailable experimentally due to their short lifetime or high reactivity. While structure-activity relationships (SARs) have been successfully employed to estimate the unknown photoabsorption cross-sections of VOCs, computational photochemistry offers another promising strategy to predict not only the vertical electronic transitions of a given molecule but also the width and shape of the bands forming its absorption spectrum. In this work, we focus on the use of the nuclear ensemble approach (NEA) to determine the photoabsorption cross-section of four exemplary VOCs, namely, acrolein, methylhydroperoxide, 2-hydroperoxy-propanal, and (microsolvated) pyruvic acid. More specifically, we analyze the influence that different strategies for sampling the ground-state nuclear density-Wigner sampling and ab initio molecular dynamics with a quantum thermostat-can have on the simulated absorption spectra. We highlight the potential shortcomings of using uncoupled harmonic modes within Wigner sampling of nuclear density to describe flexible or microsolvated VOCs and some limitations of SARs for multichromophoric VOCs. Our results suggest that the NEA could constitute a powerful tool for the atmospheric community to predict the photoabsorption cross-section for transient VOCs.
| S-EPMC8785186 | biostudies-literature
Project description:We introduce a fully stand-alone version of the Quantum Chemistry Electron Ionization Mass Spectra (QCEIMS) program [S. Grimme, Angew. Chem. Int. Ed., 2013, 52, 6306] allowing efficient simulations for molecules composed of elements with atomic numbers up to Z = 86. The recently developed extended tight-binding semi-empirical method GFN-xTB has been combined with QCEIMS, thereby eliminating dependencies on third-party electronic structure software. Furthermore, for reasonable calculations of ionization potentials, as required by the method, a second tight-binding variant, IPEA-xTB, is introduced here. This novel combination of methods allows the automatic, fast and reasonably accurate computation of electron ionization mass spectra for structurally different molecules across the periodic table. In order to validate and inspect the transferability of the method, we perform large-scale simulations for some representative organic, organometallic, and main-group inorganic systems. Theoretical spectra for 23 molecules are compared directly to experimental data taken from standard databases. For the first time, realistic quantum chemistry based EI-MS for organometallic systems like ferrocene or copper(ii)acetylacetonate are presented. Compared to previously used semiempirical methods, GFN-xTB is faster, more robust, and yields overall higher quality spectra. The partially analysed theoretical reaction and fragmentation mechanisms are chemically reasonable and reveal in unprecedented detail the extreme complexity of high energy gas phase ion chemistry including complicated rearrangement reactions prior to dissociation.
| S-EPMC5603848 | biostudies-literature
Project description:We present a machine learning (ML) method to accelerate the nuclear ensemble approach (NEA) for computing absorption cross sections. ML-NEA is used to calculate cross sections on vast ensembles of nuclear geometries to reduce the error due to insufficient statistical sampling. The electronic properties-excitation energies and oscillator strengths-are calculated with a reference electronic structure method only for a relatively few points in the ensemble. The KREG model (kernel-ridge-regression-based ML combined with the RE descriptor) as implemented in MLatom is used to predict these properties for the remaining tens of thousands of points in the ensemble without incurring much of additional computational cost. We demonstrate for two examples, benzene and a 9-dicyanomethylene derivative of acridine, that ML-NEA can produce statistically converged cross sections even for very challenging cases and even with as few as several hundreds of training points.
| S-EPMC7511037 | biostudies-literature
Project description:Analysis of large biomolecules including proteins has proven challenging using ambient ionization mass spectrometry imaging techniques. Here, we have successfully optimized desorption electrospray ionization mass spectrometry (DESI-MS) to detect intact proteins directly from tissue sections and further integrated DESI-MS to a high field asymmetric waveform ion mobility (FAIMS) device for protein imaging. Optimized DESI-FAIMS-MS parameters were used to image mouse kidney, mouse brain, and human ovarian and breast tissue samples, allowing detection of 11, 16, 14, and 16 proteoforms, respectively. Identification of protein species detected by DESI-MS was performed on-tissue by top-down ultraviolet photodissociation (UVPD) and collision induced dissociation (CID) as well as using tissue extracts by bottom-up CID and top-down UVPD. Our results demonstrate that DESI-MS imaging is suitable for the analysis of the distribution of proteins within biological tissue sections.
| S-EPMC6102199 | biostudies-literature
Project description:A new ionization method for the analysis of fragile gangliosides without undesired fragmentation or salt adduction is presented. In laserspray ionization inlet (LSII), the matrix/analyte sample is ablated at atmospheric pressure, and ionization takes place in the ion transfer capillary of the mass spectrometer inlet by a process that is independent of a laser wavelength or voltage. The softness of LSII allows the identification of gangliosides up to GQ1 with negligible sialic acid loss. This is of importance to the field of MS imaging, as undesired fragmentation has made it difficult to accurately map the spatial distribution of fragile ganglioside lipids in tissue. Proof-of-principle structural characterization of endogenous gangliosides using MS(n) fragmentation of multiply charged negative ions on a LTQ Velos and subsequent imaging of the GD1 ganglioside is demonstrated. This is the first report of multiply charged negative ions using inlet ionization. We find that GD1 is detected at higher levels in the mouse cortex and hippocampus compared with the thalamus. In LSII with the laser aligned in transmission geometry relative to the inlet, images were obtained in approximately 60 min using an inexpensive nitrogen laser.
| S-EPMC3371251 | biostudies-literature
Project description:Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or using cross-sections of the brain. Prior to two practical assignments, a pretest (extended matching questions, double-choice questions and a test on cross-sectional anatomy) and a mental rotation test (MRT) were completed. Sex and MRT scores were used to stratify students over the two groups. The two practical assignments were designed to study (1) general brain anatomy and (2) subcortical structures. Subsequently, participants completed a posttest similar to the pretest and a motivational questionnaire. Finally, a focus group interview was conducted to appraise participants' perceptions. Medical and biomedical students (n = 31); 19 males (61.3%) and 12 females (38.7%), mean age 19.2 ± 1.7 years participated in this experiment. Students who worked with cross-sections (n = 16) showed significantly more improvement on test scores than students who worked with GreyMapp-AR (P = 0.035) (n = 15). Further analysis showed that this difference was primarily caused by significant improvement on the cross-sectional questions. Students in the cross-section group, moreover, experienced a significantly higher germane (P = 0.009) and extraneous cognitive load (P = 0.016) than students in the GreyMapp-AR group. No significant differences were found in motivational scores. To conclude, this study suggests that AR applications can play a role in future anatomy education as an add-on educational tool, especially in learning three-dimensional relations of anatomical structures.
| S-EPMC7317366 | biostudies-literature
Project description:RationaleIonization by atmospheric pressure gas discharge has been employed for a long time in mass spectrometry. Inductively coupled plasma mass spectrometry is an exemplar, and widely used for elemental analysis. The technique has less uptake in organic mass spectrometry. We describe a simple source design that can be readily implemented in most atmospheric pressure ionization (API) systems and compare its performance with that of electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI).MethodsAn in-house designed helium gas discharge source (referred to as 'GlowFlow') was used on a Xevo G2-S time-of-flight mass spectrometer. The GlowFlow source was transferred to a compatible Xevo TQ-S triple-quadrupole mass spectrometer using an ultrahigh-performance liquid chromatograph inlet. Its performance was compared to that of Waters ESI and APCI sources.ResultsPreliminary results of GlowFlow on the Swansea instrument are presented to establish context and include analysis of low-molecular-mass polymers, benzoic acid and cinnamic acid. Comparison of performance on the Xevo TQ-S triple-quadrupole mass spectrometer involved three test mixtures. The method limits of detection (six-mix) for positive-ion GlowFlow source were between 0.03 and 10.00 pg with good linear response over two to four orders of magnitude and values of R2 > 0.98. The GlowFlow ionization source provided a signal intensity that was an order of magnitude greater than that of ESI for an atmospheric pressure gas chromatography standard mix and ionized several compounds that ESI could not.ConclusionsThe current GlowFlow design is relatively simple to retrofit to most API systems due to its small size. The sensitivity of the GlowFlow design is typically an order of magnitude less than that of ESI in positive-ion mode, but similar in sensitivity in negative-ion mode and comparable to that of APCI.
| S-EPMC9285393 | biostudies-literature
Project description:Through the use of the technique of time-of-flight mass spectroscopy, we obtain strong-field ionization yields for randomly oriented 1,2-dichloroethylene (1,2-DCE) (C2H2Cl2) and 2-butene (C4H8). We are interested in studying the effect of conformal structure in strong-field ionization and, in particular, the role of molecular polarity. That is, we can perform strong-field ionization studies in polar vs non-polar molecules that have the same chemical composition. We report our findings through the ionization yields and the ratio (trans/cis) of each stereoisomer pair as a function of intensity.
| S-EPMC5301495 | biostudies-literature
Project description:Electrospray ionization (ESI) operating in the negative mode coupled to high-resolution mass spectrometry is the most popular technique for the characterization of dissolved organic matter (DOM). The vast molecular heterogeneity and the functional group diversity of this complex mixture prevents the efficient ionization of the organic material by a single ionization source, so the presence of uncharacterized material is unavoidable. The extent of this poorly ionizable pool of carbon is unknown, is presumably variable between samples, and can only be assessed by the combination of analysis with a uniform detection method. Charged aerosol detection (CAD), whose response is proportional to the amount of nonvolatile material and is independent from the physicochemical properties of the analytes, is a suitable candidate. In this study, a fulvic acid mixture was fractionated and analyzed by high-pressure liquid chromatography-mass spectrometry in order to investigate the polarity and size distributions of highly and poorly ionizable material in the sample. Additionally, DOM samples of terrestrial and marine origins were analyzed to evaluate the variability of these pools across the land-sea aquatic continuum. The relative response factor values indicated that highly ionizable components of aquatic DOM mixtures are more hydrophilic and have lower molecular weight than poorly ionizable components. Additionally, a discrepancy between the samples of terrestrial and marine origins was found, indicating that marine samples are better represented by ESI than terrestrial samples, which have an abundant portion of hydrophobic poorly ionizable material.
| S-EPMC7584329 | biostudies-literature