Work function tuning of tin-doped indium oxide electrodes with solution-processed lithium fluoride

Solution-processed lithium fluoride (sol-LiF) nanoparticles synthesized in polymeric micelle nanoreactors enable tuning of the surface work function of tin-doped indium oxide (ITO) films. The micelle reactors provide the means for controlling surface coverage by progressively building up the interlayer through alternating deposition and plasma etch removal of the polymer. In order to determine the surface coverage and average interparticle distance, spatial point pattern analysis is applied to scanning electron microscope images of the nanoparticle dispersions. The work function of the sol-LiF modified ITO, obtained from photoelectron emission yield spectroscopy analysis, is shown to increase with surface coverage of the sol-LiF particles, suggesting a lateral depolarization effect. Analysis of the photoelectron emission energy distribution in the near threshold region reveals the contribution of surface states for surface coverage in excess of 14.1%. Optimization of the interfacial barrier is achieved through contributions from both work function modification and surface states

Large Scale Benchmark of Materials Design Methods

Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboar

Broadband luminescence in defect-engineered electrochemically produced porous Si/ZnO nanostructures

The fabrication, by an all electrochemical process, of porous Si/ZnO nanostructures with engineered structural defects, leading to strong and broadband deep level emission from ZnO, is presented. Such nanostructures are fabricated by a combination of metal-assisted chemical etching of Si and direct current electrodeposition of ZnO. It makes the whole fabrication process low-cost, compatible with Complementary Metal-Oxide Semiconductor technology, scalable and easily industrialised. The photoluminescence spectra of the porous Si/ZnO nanostructures reveal a correlation between the lineshape, as well as the strength of the emission, with the morphology of the underlying porous Si, that control the induced defects in the ZnO. Appropriate fabrication conditions of the porous Si lead to exceptionally bright Gaussian-type emission that covers almost the entire visible spectrum, indicating that porous Si/ZnO nanostructures could be a cornerstone material towards white-light-emitting devices

The Effect of Complex Interventions on Depression and Anxiety in Chronic Obstructive Pulmonary Disease: Systematic Review and Meta-Analysis

Background Depression and anxiety are very common in people with chronic obstructive pulmonary disease (COPD) and are associated with excess morbidity and mortality. Patients prefer non-drug treatments and clinical guidelines promote non-pharmacological interventions as first line therapy for depression and anxiety in people with long term conditions. However the comparative effectiveness of psychological and lifestyle interventions among COPD patients is not known. We assessed whether complex psychological and/or lifestyle interventions are effective in reducing symptoms of anxiety and depression in patients with COPD. We then determined what types of psychological and lifestyle interventions are most effective. Methods and Findings Systematic review of randomised controlled trials of psychological and/or lifestyle interventions for adults with COPD that measured symptoms of depression and/or anxiety. CENTRAL, Medline, Embase, PsychINFO, CINAHL, ISI Web of Science and Scopus were searched up to April 2012. Meta-analyses using random effects models were undertaken to estimate the average effect of interventions on depression and anxiety. Thirty independent comparisons from 29 randomised controlled trials (n = 2063) were included in the meta-analysis. Overall, psychological and/or lifestyle interventions were associated with small reductions in symptoms of depression (standardised mean difference −0.28, 95% confidence interval −0.41 to −0.14) and anxiety (standardised mean difference −0.23, 95% confidence interval −0.38 to −0.09). Multi-component exercise training was the only intervention subgroup associated with significant treatment effects for depression (standardised mean difference −0.47, 95% confidence interval −0.66 to −0.28), and for anxiety (standardised mean difference −0.45, 95% confidence interval −0.71 to −0.18). Conclusions Complex psychological and/or lifestyle interventions that include an exercise component significantly improve symptoms of depression and anxiety in people with COPD. Furthermore, multi-component exercise training effectively reduces symptoms of anxiety and depression in all people with COPD regardless of severity of depression or anxiety, highlighting the importance of promoting physical activity in this population

Porous Silicon Based Humidity Sensor

Porous silicon (PS) is well known as a photovoltaic material. However, in the last couple of years, research has focused on the use of porous silicon as chemical-biological sensors. This paper discusses the use of PS as an optical humidity sensor. Photo-luminescence (PL) quenching measurements in a controlled humidity atmosphere (mixed Nitrogen gas and water vapor) were performed to test the sensor response towards the water vapor. Surface morphologies of the PS samples were characterized by a scanning electron microscopy (SEM) and structural properties were investigated via Fourier Transform Infrared (FTIR) spectroscopy. It was found that PS surface is very sensitive to the water vapor. The experimental results suggested that PS surface is a promising candidate material to be used as a humidity sensor