Low-Cost One-Step Fabrication of Highly Conductive ZnO:Cl Transparent Thin Films with Tunable Photocatalytic Properties via Aerosol-Assisted Chemical Vapor Deposition

Low-cost, high-efficiency, and high quality Cl-doped ZnO (ZnO:Cl) thin films that can simultaneously function as transparent conducting oxides (TCOs) and photocatalysts are described. The films have been fabricated by a facile and inexpensive solution-source aerosol-assisted chemical vapor deposition technique using NH4Cl as an effective, cheap, and abundant source of Cl. Successful ClO substitutional doping in the ZnO films was evident from powder X-ray diffraction, X-ray photoelectron spectroscopy, and time-of-flight secondary ion mass spectrometry results, while scanning electron microscopy reveals the impact of Cl doping on the ZnO thin film morphology. All ZnO:Cl films deposited were transparent and uncolored; optical transmittance in the visible region (400−700 nm) exceeded 80% for depositions using 5−20 mol % Cl. Optimal electrical properties were achieved when using 5 mol % Cl with a minimum measured resistivity of (2.72 ± 0.04) × 10−3 Ω·cm, in which the charge carrier concentration and mobility were measured at (8.58 ± 0.16) × 1019 cm−3 and 26.7 ± 0.1 cm2 V−1 s −1 respectively, corresponding to a sheet resistance (Rsh) of 41.9 Ω□−1 at a thickness of 650 nm. In addition to transparent conducting properties, photocatalytic behavior of stearic acid degradation in the ZnO:Cl films was also observed with an optimal Cl concentration of 7 mol % Cl, with the highest formal quantum efficiency (ξ) measured at (1.63 ± 0.03) × 10−4 molecule/photon, while retaining a visible transparency of 80% and resistivity ρ = (9.23 ± 0.13) × 10−3 Ω·cm. The dual functionality of ZnO:Cl as both a transparent conductor and an efficient photocatalyst is a unique combination of properties making this a particularly unusual material

Strain effect in a GaAs-In0.25Ga0.75As-Al0.5Ga0.5As asymmetric quantum wire

We report a theoretical investigation of the strain effects on the electronic energy band in a GaAs-In0.25Ga0.75As-Al0.5Ga0.5As asymmetric quantum wire formed in a V-grooved substrate. Our model is based on the sp(3)s* tight-binding model. It includes different spatial distributions of the lattice-mismatch-induced strain. We solve numerically the tight-binding Hamiltonian through the local Green's function from which the electronic local density of states (LDOS) is obtained. The detailed energy band structure (discrete localized states and energy bands of extended states) and the spatial distribution of the eigenfunctions (wave function amplitude of nondegenerate states or sum of the wave function amplitudes of degenerate states) are directly reflected in the LDOS. Spatial mapping of the LDOS's shows a reduction of the lowest excitation energies in different regions of the system when the local lattice structure of the In0.25Ga0.75As layer relaxes from completely strained to completely relaxed. By comparing the calculated results with photoluminescence measurement data, we conclude that the strain in the In0.25Ga0.75As layer relaxes linearly from the heterointerface with the Al0.5Ga0.5As buffer layer to the heterointerface with the top GaAs layer

CSF metabolites associate with CSF tau and improve prediction of Alzheimer's disease status

Introduction: Cerebrospinal fluid (CSF) total tau (t-tau) and phosphorylated tau (p-tau) are biomarkers of Alzheimer's disease (AD), yet much is unknown about AD-associated changes in tau metabolism and tau tangle etiology. Methods: We assessed the variation of t-tau and p-tau explained by 38 previously identified CSF metabolites using linear regression models in middle-age controls from the Wisconsin Alzheimer's Disease Research Center, and predicted AD/mild cognitive impairment (MCI) versus an independent set of older controls using metabolites selected by the least absolute shrinkage and selection operator (LASSO). Results: The 38 CSF metabolites explained 70.3% and 75.7% of the variance in t-tau and p-tau, respectively. Of these, seven LASSO-selected metabolites improved the prediction ability of AD/MCI versus older controls (area under the curve score increased from 0.92 to 0.97 and 0.78 to 0.93) compared to the base model. Discussion: These tau-correlated CSF metabolites increase AD/MCI prediction accuracy and may provide insight into tau tangle etiology

Pyrite-type ruthenium disulfide with tunable disorder and defects enables ultra-efficient overall water splitting

The exploration of efficient electrocatalysts for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is significant for water splitting associated with the storage of clean and renewable energy. Here, we report a simple and scalable low-temperature sulfuration method to achieve simultaneous modulation of disorder and defects in pyrite-type RuS2 nanoparticles to dramatically enhance the HER and OER catalytic activity. The disordered structure can increase the electrochemically active surface area, while defect engineering can effectively regulate the electronic structure and thus improve the intrinsic activity, as revealed by combined experimental and theoretical density functional theory (DFT) investigations. Through controllable disorder and defect engineering, the optimized RuS2-500 catalyst (with a sulfuration temperature of 500 °C) supported on a glassy carbon electrode exhibits ultra-efficient bifunctional electrocatalytic activity with η-10 = 78 mV for the HER and η10 = 282 mV for the OER, superior to various Ru-based and pyrite-type catalysts. Remarkably, when used as both the anode and the cathode in an alkaline water electrolyzer, RuS2-500 delivers 10 mA cm-2 at an ultralow cell voltage of 1.527 V with long-term stability, outperforming the benchmark Pt/C//RuO2 couple and most state-of-the-art overall-water-splitting electrocatalysts ever reported. This work thus provides a new and facile way for improving the catalytic activity through a synergistic modulation strategy

Solving the riddle of codon usage preferences: a test for translational selection

Translational selection is responsible for the unequal usage of synonymous codons in protein coding genes in a wide variety of organisms. It is one of the most subtle and pervasive forces of molecular evolution, yet, establishing the underlying causes for its idiosyncratic behaviour across living kingdoms has proven elusive to researchers over the past 20 years. In this study, a statistical model for measuring translational selection in any given genome is developed, and the test is applied to 126 fully sequenced genomes, ranging from archaea to eukaryotes. It is shown that tRNA gene redundancy and genome size are interacting forces that ultimately determine the action of translational selection, and that an optimal genome size exists for which this kind of selection is maximal. Accordingly, genome size also presents upper and lower boundaries beyond which selection on codon usage is not possible. We propose a model where the coevolution of genome size and tRNA genes explains the observed patterns in translational selection in all living organisms. This model finally unifies our understanding of codon usage across prokaryotes and eukaryotes. Helicobacter pylori, Saccharomyces cerevisiae and Homo sapiens are codon usage paradigms that can be better understood under the proposed model

Transparent superhydrophobic PTFE films via one-step aerosol assisted chemical vapor deposition

In this study, hierarchical micro/nano-structured transparent superhydrophobic polytetrafluoroethylene (PTFE) films showing a water contact angle (CA) of 168°, a water sliding angle (SA) 90% were prepared on glass substrates via aerosol-assisted chemical vapor deposition (AACVD). Scanning electron microscopy showed the morphology to be rough, composed of both micro and nano sized protrusions. Mechanical testing showed that after impingement from 800 drops of 15 μL water (height = 1 m) or 10 g of sand grains (height = 65 cm), the CA of the transparent PTFE surface was still >150°, still demonstrating excellent superhydrophobicity. The films also showed self-cleaning and anti-corrosion properties. This one-step fabrication is a facile way of producing various kinds of transparent superhydrophobic surfaces

Josephson coupled Ising pairing induced in suspended MoS2 bilayers by double-side ionic gating

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Science Models as Value-Added Services for Scholarly Information Systems

The paper introduces scholarly Information Retrieval (IR) as a further dimension that should be considered in the science modeling debate. The IR use case is seen as a validation model of the adequacy of science models in representing and predicting structure and dynamics in science. Particular conceptualizations of scholarly activity and structures in science are used as value-added search services to improve retrieval quality: a co-word model depicting the cognitive structure of a field (used for query expansion), the Bradford law of information concentration, and a model of co-authorship networks (both used for re-ranking search results). An evaluation of the retrieval quality when science model driven services are used turned out that the models proposed actually provide beneficial effects to retrieval quality. From an IR perspective, the models studied are therefore verified as expressive conceptualizations of central phenomena in science. Thus, it could be shown that the IR perspective can significantly contribute to a better understanding of scholarly structures and activities.Comment: 26 pages, to appear in Scientometric

The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis

Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate sample types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and individual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research