Orbital dynamics during an ultrafast insulator to metal transition

Phase transitions driven by ultrashort laser pulses have attracted interest both for understanding the fundamental physics of phase transitions and for potential new data storage or device applications. In many cases these transitions involve transient states that are different from those seen in equilibrium. To understand the microscopic properties of these states, it is useful to develop elementally selective probing techniques that operate in the time domain. Here we show fs-time-resolved measurements of V Ledge Resonant Inelastic X-Ray Scattering (RIXS) from the insulating phase of the Mott- Hubbard material V2O3 after ultrafast laser excitation. The probed orbital excitations within the d-shell of the V ion show a sub-ps time response, which evolve at later times to a state that appears electronically indistinguishable from the high-temperature metallic state. Our results demonstrate the potential for RIXS spectroscopy to study the ultrafast orbital dynamics in strongly correlated materials.Comment: 12 pages, 4 figure

Black carbon and organic carbon in aerosol particles from crown fires in the Canadian boreal forest

Version of RecordIn the boreal forest, high-intensity crown fires account for an overwhelming proportion of the area burned yearly. Quantifying the amount of black carbon (BC) from boreal crown fires in Canada is essential for assessing the effect on regional climate from natural wildfire aerosol emissions versus that from anthropogenic activities. This is particularly relevant because climate change will likely lead to increased wildfire activity in northern Canada. During 4-5 July 1998, two controlled fires in Northwest Territories, Canada, were conducted as part of the International Crown Fire Modeling Experiment. We report here the BC and organic carbon (OC) compositions of aerosols produced during the flaming and smoldering stages of burning. Particles were collected on back-to-back quartz-fiber filters by helicopter with a hi-vol sampler and at ground level with a dichotomous sampler to separate the fine (≤2.5 μm diameter) and coarse (2.5-10 μm diameter) particle fractions. An analysis of the back filter in relation to the front filter from the dichot sampler for both the fine and coarse fractions provided a means to correct for the adsorption of gas-phase organic compounds on filters (positive artifact) and for the loss of particulate carbon from filters by volatilization (negative artifact). BC and OC masses, which combine here to give total carbon (TC), were determined by the thermal-optical method. The BC to TC ratio for the flaming stage was 0.085 ± 0.032 (xˉ ± ksn-1/2, k = 2, n = 2), based on aerial sampling of the dark plume 300-500 m above the flame front. BC/TC for the smoldering stage was 0.0087 ± 0.0046 from ground-based sampling. Uncertainties consist of the combined variances in measurement and sampling and in emissions from different fires. These averages and uncertainties serve as important aerosol data input for predictions of climate change on both global and regional scales.Conny, J. M., and Slater, J. F. (2002), Black carbon and organic carbon in aerosol particles from crown fires in the Canadian boreal forest, J. Geophys. Res., 107(D11), 4116, doi:10.1029/2001JD001528

Transient Expression of Hemagglutinin Antigen from Low Pathogenic Avian Influenza A (H7N7) in Nicotiana benthamiana

The influenza A virus is of global concern for the poultry industry, especially the H5 and H7 subtypes as they have the potential to become highly pathogenic for poultry. In this study, the hemagglutinin (HA) of a low pathogenic avian influenza virus of the H7N7 subtype isolated from a Swedish mallard Anas platyrhynchos was sequenced, characterized and transiently expressed in Nicotiana benthamiana. Recently, plant expression systems have gained interest as an alternative for the production of vaccine antigens. To examine the possibility of expressing the HA protein in N. benthamiana, a cDNA fragment encoding the HA gene was synthesized de novo, modified with a Kozak sequence, a PR1a signal peptide, a C-terminal hexahistidine (6×His) tag, and an endoplasmic retention signal (SEKDEL). The construct was cloned into a Cowpea mosaic virus (CPMV)-based vector (pEAQ-HT) and the resulting pEAQ-HT-HA plasmid, along with a vector (pJL3:p19) containing the viral gene-silencing suppressor p19 from Tomato bushy stunt virus, was agro-infiltrated into N. benthamiana. The highest gene expression of recombinant plant-produced, uncleaved HA (rHA0), as measured by quantitative real-time PCR was detected at 6 days post infiltration (dpi). Guided by the gene expression profile, rHA0 protein was extracted at 6 dpi and subsequently purified utilizing the 6×His tag and immobilized metal ion adsorption chromatography. The yield was 0.2 g purified protein per kg fresh weight of leaves. Further molecular characterizations showed that the purified rHA0 protein was N-glycosylated and its identity confirmed by liquid chromatography-tandem mass spectrometry. In addition, the purified rHA0 exhibited hemagglutination and hemagglutination inhibition activity indicating that the rHA0 shares structural and functional properties with native HA protein of H7 influenza virus. Our results indicate that rHA0 maintained its native antigenicity and specificity, providing a good source of vaccine antigen to induce immune response in poultry species

The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies

Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys

Internal Composition of Atmospheric Dust Particles from Focused Ion-Beam Scanning Electron Microscopy

Use of focused ion-beam scanning electron microscopy (FIB-SEM) to investigate the internal composition of atmospheric particles is demonstrated for assessing particle optical properties. In the FIB-SEM instrument equipped with an X-ray detector, a gallium-ion beam mills the particle, while the electron beam images the slice faces and energy-dispersive X-ray spectroscopy provides element maps of the particle. Differences in assessments of optical behavior based on FIB-SEM and conventional SEM were shown for five selected urban dust particles. The benefit of FIB-SEM for accurately determining the depth and size of optically important phases within particles was shown. FIB-SEM revealed that iron oxide grains left undetected by conventional SEM could potentially shift the single-scattering albedo of the particle from negative to positive radiative forcing. Analysis of a coke-like particle showed that 73% of the light-scattering inclusion went undetected with conventional SEM, causing the bulk absorption coefficient to vary by as much as 25%. Optical property calculations for particles as volume-equivalent spheres and as spheroids that approximated actual particle shapes revealed that the largest effect between conventional SEM and FIB-SEM analyses was on backscattering efficiency, in some cases varying several-fold

Filter Material Effects on Particle Absorption Optical Properties

<div><p>Absorption enhancement and shadowing effects were investigated for nigrosin-laden quartz (fibrous), Teflon (matted), and polycarbonate (membrane) filters in inert surroundings at different sample steady-state temperatures and particle mass loadings. Sample absorptivity was determined using a novel laser-heating technique, which is based on perturbing the sample steady-state temperature and monitoring the thermal response during decay back to steady state, along with a model for thermal energy conservation. In addition, transmissivity measurements were carried out to enable determination of the sample absorption coefficient. The results indicated that the isolated-nigrosin absorption coefficient decreased with steady-state temperature and increased with mass loading and filter pore size. Comparing the absorption coefficient for both the isolated nigrosin and nigrosin-laden filters, indicated that absorption enhancement was most significant for the Teflon filters and least significant for the polycarbonate filters. The effect became more significant as the pore size decreased, steady-state temperature increased, and particle mass loading decreased. The decrease in the isolated-nigrosin, mass-specific absorption cross-section with heavier sample loadings was attributed to shadowing effects.</p> <p>Copyright 2014 American Association for Aerosol Research</p> </div

Qualitative Multiplatform Microanalysis of Individual Heterogeneous Atmospheric Particles from High-Volume Air Samples

High-resolution microscopic analysis of individual atmospheric particles can be difficult, because the filters upon which particles are captured are often not suitable as substrates for microscopic analysis. Described here is a multiplatform approach for microscopically assessing chemical and optical properties of individual heterogeneous urban dust particles captured on fibrous filters during high-volume air sampling. First, particles embedded in fibrous filters are transferred to polished silicon or germanium wafers with electrostatically assisted high-speed centrifugation. Particles are clustered in an array of deposit areas, which allows for easily locating the same particle with different microscopy instruments. Second, particles with light-absorbing and/or light-scattering behavior are identified for further study from bright-field and dark-field light-microscopy modes, respectively. Third, particles identified from light microscopy are compositionally mapped at high definition with field-emission scanning electron microscopy and energy-dispersive X-ray spectroscopy. Fourth, compositionally mapped particles are further analyzed with focused ion-beam (FIB) tomography, whereby a series of thin slices from a particle are imaged, and the resulting image stack is used to construct a three-dimensional model of the particle. Finally, particle chemistry is assessed over two distinct regions of a thin FIB slice of a particle with energy-filtered transmission electron microscopy (TEM) and electron energy-loss spectroscopy associated with scanning transmission electron microscopy (STEM)

Rapid chemical screening of microplastics and nanoplastics by thermal desorption and pyrolysis mass spectrometry with unsupervised fuzzy clustering

The transport and chemical identification of microplastics and nanoplastics (MNPs) are critical to the concerns over plastic accumulation in the environment. Chemically and physically transient MNP species present unique challenges for isolation and analysis due to many factors such as their size, color, surface properties, morphology, and potential for chemical change. These factors contribute to the eventual environmental and toxicological impact of MNPs. As analytical methods and instrumentation continue to be developed for this application, analytical test materials will play an important role. Here, a direct mass spectrometry screening method was developed to rapidly characterize manufactured and weathered MNPs, complementing lengthy pyrolysis-gas chromatography mass spectrometry analyses. The chromatography-free measurements took advantage of Kendrick mass defect analysis, in-source collision induced dissociation, and advancements in machine learning approaches for data analysis of the complex mass spectra. In this study, we applied Gaussian mixture models and fuzzy c-means clustering for the unsupervised analysis of MNP sample spectra, incorporating clustering stability and information criterion measurements to determine latent dimensionality. These models provided insight into the composition of mixed and weathered MNP samples. The multiparametric data acquisition and machine learning approach presented improved confidence in polymer identification and differentiation