Fluorine doping: A feasible solution to enhancing the conductivity of high-resistance wide bandgap Mg0.51Zn0.49O active components

N-type doping of high-resistance wide bandgap semiconductors, wurtzite high-Mg-content MgxZn1-xO for instance, has always been a fundamental application-motivated research issue. Herein, we report a solution to enhancing the conductivity of high-resistance Mg0.51Zn0.49O active components, which has been reliably achieved by fluorine doping via radio-frequency plasma assisted molecular beam epitaxial growth. Fluorine dopants were demonstrated to be effective donors in Mg0.51Zn0.49O single crystal film having a solar-blind 4.43 eV bandgap, with an average concentration of 1.0E19 F/cm3.The dramatically increased carrier concentration (2.85E17 cm-3 vs ~1014 cm-3) and decreased resistivity (129 ohm.cm vs ~10E6 ohm cm) indicate that the electrical properties of semi-insulating Mg0.51Zn0.49O film can be delicately regulated by F doping. Interestingly, two donor levels (17 meV and 74 meV) associated with F were revealed by temperature-dependent Hall measurements. A Schottky type metal-semiconductor-metal ultraviolet photodetector manifests a remarkably enhanced photocurrent, two orders of magnitude higher than that of the undoped counterpart. The responsivity is greatly enhanced from 0.34 mA/W to 52 mA/W under 10 V bias. The detectivity increases from 1.89E9 cm Hz1/2/W to 3.58eE10 cm Hz1/2/W under 10 V bias at room temperature.These results exhibit F doping serves as a promising pathway for improving the performance of high-Mg-content MgxZn1-xO-based devices.Comment: 8 page

Characterization, dissolution and solubility of the hydroxypyromorphite–hydroxyapatite solid solution [(PbxCa1−x)5(PO4)3OH] at 25 °C and pH 2–9

Additional file 1: Appendix A. Supplementary data—X-ray diffractograms (XRD) of the hydroxypyromorphite–hydroxyapatite solid solution [(PbxCa1−x)5(PO4)3(OH)] after dissolution at 25 ˚C and an initial pH of 5.60 and 9.00 for 300d

Graphene as Transparent Electrode for Direct Observation of Hole Photoemission from Silicon to Oxide

The outstanding electrical and optical properties of graphene make it an excellent alternative as a transparent electrode. Here we demonstrate the application of graphene as collector material in internal photoemission (IPE) spectroscopy; enabling the direct observation of both electron and hole injections at a Si/Al2O3 interface and successfully overcoming the long-standing difficulty of detecting holes injected from a semiconductor emitter in IPE measurements. The observed electron and hole barrier heights are 3.5 eV and 4.1 eV, respectively. Thus the bandgap of Al2O3 can be further deduced to be 6.5 eV, in close agreement with the valued obtained by vacuum ultraviolet spectroscopic ellipsometry analysis. The detailed optical modeling of a graphene/Al2O3/Si stack reveals that by using graphene in IPE measurements the carrier injection from the emitter is significantly enhanced and the contribution of carrier injection from the collector electrode is minimal. The method can be readily extended to various IPE test structures for a complete band alignment analysis and interface characterization.Comment: 15 pages, 5 figure

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August, 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses

Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM

Impacts of various amendments on the microbial communities and soil organic carbon of coastal saline–alkali soil in the Yellow River Delta

The utilization of industrial and agricultural resources, such as desulfurization gypsum and straw, is increasingly favored to improve saline alkali land. However, there is still a lack of comprehensive study on the mechanism of organic carbon turnover under the conditions of desulfurization gypsum and straw application. We studied the changes in soil chemical performance, microbial diversity, and microbial community structure in soils with the addition of various levels of straw (no straw, S0; low straw, Sl; medium straw, Sm; and high straw, Sh) and gypsum (no gypsum, DG0; low gypsum, DGl; and high gypsum, DGh) in a 120-day incubation experiment. The bacterial and fungal community richness was higher in the SmDGl treatment than in the SmDG0 treatment. The microbial community evenness showed a similar pattern between the SmDGl and SmDG0 treatments. The combination of the straw and desulfurization gypsum treatments altered the relative abundance of the main bacterial phyla Bacteroidetes and Firmicutes and the dominant fungal class Sordariomycetes, which increased with the enhancement of the SOC ratio. The combination of the straw and desulfurization gypsum treatments, particularly SmDGl, significantly decreased the soil pH and exchangeable sodium percentage (ESP), while it increased the soil organic carbon, microbial biomass carbon, and activities of soil enzymes. Improvement in the soil salinization environment clearly drove the changes in bacterial α-diversity and community, particularly those in the soil carbon fractions and ESP. In conclusion, these findings provide a strong framework to determine the impact of application practices on soil restoration, and the information gained in this study will help to develop more sustainable and effective integrated strategies for the restoration of saline–alkali soil

A brief review of the phase-field-based lattice Boltzmann method for multiphase flows

In this paper, we present a brief overview of the phase-field-based lattice Boltzmann method (LBM) that is a distinct and efficient numerical algorithm for multiphase flow problems. We first give an introduction to the mathematical theory of phase-field models for multiphase flows, and then present some recent progress on the LBM for the phase-field models which are composed of the classic Navier-Stokes equations and the Cahn-Hilliard or Allen-Cahn equation. Finally, some applications of the phase-field-based LBM are also discussed.Cited as: Wang, H., Yuan, X., Liang, H., Chai, Z., Shi, B. A brief review of the phase-field-based lattice Boltzmann method for multiphase flows. Capillarity, 2019, 2(3): 33-52, doi: 10.26804/capi.2019.03.0

Characterizing Cancer and COVID-19 Outcomes Using Electronic Health Records

PURPOSE: Patients with cancer often have compromised immune system which can lead to worse COVID-19 outcomes. The purpose of this study is to assess the association between COVID-19 outcomes and existing cancer-specific characteristics. PATIENTS AND METHODS: Patients aged 18 or older with laboratory-confirmed COVID-19 between June 1, 2020, and December 31, 2020, were identified (n = 314 004) from the Optum® de-identified COVID-19 Electronic Health Record (EHR) derived from more than 700 hospitals and 7000 clinics in the United States. To allow sufficient observational time, patients with less than one year of medical history in the EHR dataset before their COVID-19 tests were excluded (n = 42 365). Assessed COVID-19 outcomes including all-cause 30-day mortality, hospitalization, ICU admission, and ventilator use, which were compared using relative risks (RRs) according to cancer status and treatments. RESULTS: Among 271 639 patients with COVID-19, 18 460 had at least one cancer diagnosis: 8034 with a history of cancer and 10 426 with newly diagnosed cancer within one year of COVID-19 infection. Patients with a cancer diagnosis were older and more likely to be male, white, Medicare beneficiaries, and have higher prevalences of chronic conditions. Cancer patients had higher risks for 30-day mortality (RR 1.07, 95% CI 1.01-1.14, P = 0.028) and hospitalization (RR 1.04, 95% CI 1.01-1.07, P = 0.006) but without significant differences in ICU admission and ventilator use compared to non-cancer patients. Recent cancer diagnoses were associated with higher risks for worse COVID-19 outcomes (RR for mortality 1.17, 95% CI 1.08-1.25, P\u3c0.001 and RR for hospitalization 1.10, 95% CI 1.06-1.14, P\u3c0.001), particularly among recent metastatic (stage IV), hematological, liver and lung cancers compared with the non-cancer group. Among COVID-19 patients with recent cancer diagnosis, mortality was associated with chemotherapy or radiation treatments within 3 months before COVID-19. Age, black patients, Medicare recipients, South geographic region, cardiovascular, diabetes, liver, and renal diseases were also associated with increased mortality. CONCLUSIONS AND RELEVANCE: Individuals with cancer had higher risks for 30-day mortality and hospitalization after SARS-CoV-2 infection compared to patients without cancer. More specifically, patients with a cancer diagnosis within 1 year and those receiving active treatment were more vulnerable to worse COVID-19 outcomes