Observation and Characterization of the Hg-O Diatomic Molecule: A Matrix-Isolation and Quantum-Chemical Investigation

Mercuric oxide is a well-known and stable solid, but the diatomic molecule Hg-O is very fragile and do not survive detection in the gas phase. However, laser ablation of Hg atoms from a dental amalgam target into argon or neon containing about 0.3% of 16 O 2 or of 18 O 2 during their condensation into a cryogenic matrix at 4 K allows the formation of O atoms which react on annealing to make ozone and new IR absorptions in solid argon at 521.2 cm –1 for Hg- 16 O or at 496.4 cm –1 for Hg- 18 O with the oxygen isotopic frequency ratio 521.2/496.4 = 1.0500. Solid neon gives a 529.0 cm –1 absorption with a small 7.8 blue shift. CCSD(T) calculations found 594 cm –1 for Hg 16 O and 562 cm –1 for Hg 18 O (frequency ratio = 1.0569). Such calculations usually produce harmonic frequencies that are slightly higher than the anharmonic (observed) values, which supports their relationship. These observed frequencies have the isotopic shift predicted for Hg-O and are within the range of recent high-level frequency calculations for the Hg-O molecule. Spectra for the related mercury superoxide and ozonide species are also observed for the first time

Infrared Spectroscopic and Theoretical Investigations of Group 13 Oxyfluorides OMF2 and OMF (M = B, Al, Ga, In)

Group 13 oxyfluorides OMF2 were produced by the reactions of laser-ablated group 13 atoms M (M = B, Al, Ga and In) with OF2 and isolated in excess neon or argon matrices at 5 K. These molecules were characterized by matrix-isolation infrared spectroscopy and isotopic substitution experiments in conjunction with quantum-chemical calculations. The calculations indicate that the OMF2 molecules have a 2B2 ground state with C2v symmetry. The computed molecular orbitals and spin densities show that the unpaired electron is mainly located at the terminal oxygen atom. Oxo monofluorides OMF were only observed in solid argon matrices and exhibit a linear structure in the singlet ground state. The M−O bonding in the OMF molecules can be rationalized as highly polar multiple bonds based on the calculated bond lengths and natural resonance theory (NRT) analyses. In particular, the molecular orbitals of OBF exhibit the character of a triple bond B−O resulting from two degenerate electron-sharing π bonds and a O → B dative σ bond formed by the oxygen 2p lone pair which donates electron density to the boron empty 2p orbital

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images.

BackgroundLiver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a convolutional neural network algorithm to register cross-sectional liver imaging series and compared its performance to manual image registration.MethodsThree hundred fourteen patients, including internal and external datasets, who underwent gadoxetate disodium-enhanced magnetic resonance imaging for clinical care from 2011 to 2018, were retrospectively selected. Automated registration was applied to all 2,663 within-patient series pairs derived from these datasets. Additionally, 100 within-patient series pairs from the internal dataset were independently manually registered by expert readers. Liver overlap, image correlation, and intra-observation distances for manual versus automated registrations were compared using paired t tests. Influence of patient demographics, imaging characteristics, and liver uptake function was evaluated using univariate and multivariate mixed models.ResultsCompared to the manual, automated registration produced significantly lower intra-observation distance (p < 0.001) and higher liver overlap and image correlation (p < 0.001). Intra-exam automated registration achieved 0.88 mean liver overlap and 0.44 mean image correlation for the internal dataset and 0.91 and 0.41, respectively, for the external dataset. For inter-exam registration, mean overlap was 0.81 and image correlation 0.41. Older age, female sex, greater inter-series time interval, differing uptake, and greater voxel size differences independently reduced automated registration performance (p ≤ 0.020).ConclusionA fully automated algorithm accurately registered the liver within and between examinations, yielding better liver and focal observation co-localization compared to manual registration

Noncovalent Interactions in Halogenated Pyridinium Salts of the Weakly Coordinating Anion [Al(OTeF5)4]–

The synthesis and the first structural characterization of the halogenated pyridinium salts [C 5 F 5 NH] + , [C 5 F 4 ClNH] + , [(C 5 F 5 N) 2 H] + , [(C 5 Cl 5 N) 2 H] + of the weakly coordinating anion (WCA) [Al(OTeF 5 ) 4 ] − , showing noncovalent interactions in the solid state, are presented. The salts were characterized by the multinuclear NMR and IR spectroscopy as well as X-Ray diffraction. Hirshfeld surface analysis and solid state structures reveal various intermolecular anion-π and σ-hole interactions between the corresponding halogenated pyridinium cations and the anion [Al(OTeF 5 ) 4 ] −

Gold Teflates Revisited: from the Lewis Superacid [Au(OTeF5)3] to the Anion [Au(OTeF5)4]−

A new synthetic access to the Lewis acid [Au(OTeF5)3] and the preparation of the related, unprecedented anion [Au(OTeF5)4]− with inorganic or organic cations starting from commercially available and easy-to-handle gold chlorides are presented. In this first extensive study of the Lewis acidity of a transition metal teflate complex using different experimental and quantum chemical methods, [Au(OTeF5)3] was classified as a Lewis superacid. The solid state structure of the triphenylphosphane adduct [Au(OPPh3)(OTeF5)3] was determined, representing the first structural characterization of an adduct of this highly reactive [Au(OTeF5)3]. Therein, the coordination environment around the gold center slightly deviates from the typical square planar geometry. The related, unprecedented anion [Au(OTeF5)4]− shows a similar coordination motif

Reactivity of [AuF3(SIMes)] – Pathway to Unprecedented Structural Motifs

We report on a comprehensive reactivity study starting from [AuF3(SIMes)] to synthesize different motifs of monomeric gold(III) fluorides. A plethora of different ligands has been introduced in a mono-substitution yielding trans-[AuF2X(SIMes)] including alkynido, cyanido, azido, and a set of perfluoroalkoxido complexes. The latter were better accomplished via use of perfluorinated carbonyl-bearing molecules, which is unprecedented in gold chemistry. In case of the cyanide and azide, triple substitution gave rise to the corresponding [AuX3(SIMes)] complexes. Comparison of the chemical shift of the carbene carbon atom in the 13C{1H} NMR spectrum, the calculated SIMes affinity and the Au–C bond length in the solid state with related literature-known complexes yields a classification of trans-influences for a variety of ligands attached to the gold center. Therein, the mixed fluorido perfluoroalkoxido complexes have a similar SIMes affinity to AuF3 with a very low Gibbs energy of formation when using the perfluoro carbonyl route

Automated CT and MRI Liver Segmentation and Biometry Using a Generalized Convolutional Neural Network.

PurposeTo assess feasibility of training a convolutional neural network (CNN) to automate liver segmentation across different imaging modalities and techniques used in clinical practice and apply this to enable automation of liver biometry.MethodsWe trained a 2D U-Net CNN for liver segmentation in two stages using 330 abdominal MRI and CT exams acquired at our institution. First, we trained the neural network with non-contrast multi-echo spoiled-gradient-echo (SGPR)images with 300 MRI exams to provide multiple signal-weightings. Then, we used transfer learning to generalize the CNN with additional images from 30 contrast-enhanced MRI and CT exams.We assessed the performance of the CNN using a distinct multi-institutional data set curated from multiple sources (n = 498 subjects). Segmentation accuracy was evaluated by computing Dice scores. Utilizing these segmentations, we computed liver volume from CT and T1-weighted (T1w) MRI exams, and estimated hepatic proton- density-fat-fraction (PDFF) from multi-echo T2*w MRI exams. We compared quantitative volumetry and PDFF estimates between automated and manual segmentation using Pearson correlation and Bland-Altman statistics.ResultsDice scores were 0.94 ± 0.06 for CT (n = 230), 0.95 ± 0.03 (n = 100) for T1w MR, and 0.92 ± 0.05 for T2*w MR (n = 169). Liver volume measured by manual and automated segmentation agreed closely for CT (95% limit-of-agreement (LoA) = [-298 mL, 180 mL]) and T1w MR (LoA = [-358 mL, 180 mL]). Hepatic PDFF measured by the two segmentations also agreed closely (LoA = [-0.62%, 0.80%]).ConclusionsUtilizing a transfer-learning strategy, we have demonstrated the feasibility of a CNN to be generalized to perform liver segmentations across different imaging techniques and modalities. With further refinement and validation, CNNs may have broad applicability for multimodal liver volumetry and hepatic tissue characterization