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An alternative method for the structure tuning of carbon nitride materials by using a supramolecular approach in combination with caffeine as lining-agent is described. The self-assembly of the precursor complex consisting of melamine and cyanuric acid can be controlled by this doping molecule in terms of morphology, electronic, and photophysical properties. Caffeine is proposed to insert as an edge-molecule eventually leading to hollow tube-like carbon nitride structures with improved efficiency of charge formation. Compared to the bulk carbon nitride, the caffeine-doped analogue possesses a higher photocatalytic activity for the degradation of rhodamineB dye. Furthermore, this approach is also shown to be suitable for the modification of carbon nitride electrodes.
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Reduced expression of the Indy ("I am Not Dead, Yet") gene in lower organisms promotes longevity in a manner akin to caloric restriction. Deletion of the mammalian homolog of Indy (mIndy, Slc13a5) encoding for a plasma membrane-associated citrate transporter expressed highly in the liver, protects mice from high-fat diet-induced and aging-induced obesity and hepatic fat accumulation through a mechanism resembling caloric restriction. We studied a possible role of mIndy in human hepatic fat metabolism. In obese, insulin-resistant patients with nonalcoholic fatty liver disease, hepatic mIndy expression was increased and mIndy expression was also independently associated with hepatic steatosis. In nonhuman primates, a 2-year high-fat, high-sucrose diet increased hepatic mIndy expression. Liver microarray analysis showed that high mIndy expression was associated with pathways involved in hepatic lipid metabolism and immunological processes. Interleukin-6 (IL-6) was identified as a regulator of mIndy by binding to its cognate receptor. Studies in human primary hepatocytes confirmed that IL-6 markedly induced mIndy transcription through the IL-6 receptor and activation of the transcription factor signal transducer and activator of transcription 3, and a putative start site of the human mIndy promoter was determined. Activation of the IL-6-signal transducer and activator of transcription 3 pathway stimulated mIndy expression, enhanced cytoplasmic citrate influx, and augmented hepatic lipogenesis in vivo. In contrast, deletion of mIndy completely prevented the stimulating effect of IL-6 on citrate uptake and reduced hepatic lipogenesis. These data show that mIndy is increased in liver of obese humans and nonhuman primates with NALFD. Moreover, our data identify mIndy as a target gene of IL-6 and determine novel functions of IL-6 through mINDY. Conclusion: Targeting human mINDY may have therapeutic potential in obese patients with nonalcoholic fatty liver disease. German Clinical Trials Register: DRKS00005450.
Among modern functional materials, the class of nitrogen-containing carbons combines non-toxicity and sustainability with outstanding properties. The versatility of this materials class is based on the opportunity to tune electronic and catalytic properties via the nitrogen content and –motifs: This ranges from the electronically conducting N-doped carbon, where few carbon atoms in the graphitic lattice are substituted by nitrogen, to the organic semiconductor graphitic carbon nitride (g-C₃N₄), with a structure based on tri-s-triazine units.
In general, composites can reveal outstanding catalytic properties due to synergistic behavior, e.g. the formation of electronic heterojunctions. In this thesis, the formation of an “all-carbon” heterojunction was targeted, i.e. differences in the electronic properties of the single components were achieved by the introduction of different nitrogen motives into the carbon lattice. Such composites are promising as metal-free catalysts for the photocatalytic water splitting. Here, hydrogen can be generated from water by light irradiation with the use of a photocatalyst. As first part of the heterojunction, the organic semiconductor g-C₃N₄ was employed, because of its suitable band structure for photocatalytic water splitting, high stability and non-toxicity. The second part was chosen as C₂N, a recently discovered semiconductor. Compared to g-C₃N₄, the less nitrogen containing C₂N has a smaller band gap and a higher absorption coefficient in the visible light range, which is expected to increase the optical absorption in the composite eventually leading to an enhanced charge carrier separation due to the formation of an electronic heterojunction.
The aim of preparing an “all-carbon” composite included the research on appropriate precursors for the respective components g-C₃N₄ and C₂N, as well as strategies for appropriate structuring. This was targeted by applying precursors which can form supramolecular pre-organized structures. This allows for more control over morphology and atom patterns during the carbonization process.
In the first part of this thesis, it was demonstrated how the photocatalytic activity of g-C₃N₄ can be increased by the targeted introduction of defects or surface terminations. This was achieved by using caffeine as a “growth stopping” additive during the formation of the hydrogen-bonded supramolecular precursor complexes. The increased photocatalytic activity of the obtained materials was demonstrated with dye degradation experiments.
The second part of this thesis was focused on the synthesis of the second component C₂N. Here, a deep eutectic mixture from hexaketocyclohexane and urea was structured using the biopolymer chitosan. This scaffolding resulted in mesoporous nitrogen-doped carbon monoliths and beads. CO₂- and dye-adsorption experiments with the obtained monolith material revealed a high isosteric heat of CO₂-adsorption and showed the accessibility of the monolithic pore system to larger dye molecules. Furthermore, a novel precursor system for C₂N was explored, based on organic crystals from squaric acid and urea. The respective C₂N carbon with an unusual sheet-like morphology could be synthesized by carbonization of the crystals at 550 °C. With this precursor system, also microporous C₂N carbon with a BET surface area of 865 m²/g was obtained by “salt-templating” with ZnCl₂.
Finally, the preparation of a g-C₃N₄/C₂N “all carbon” composite heterojunction was attempted by the self-assembly of g-C₃N₄ and C₂N nanosheets and tested for photocatalytic water splitting. Indeed, the composites revealed high rates of hydrogen evolution when compared to bulk g-C₃N₄. However, the increased catalytic activity was mainly attributed to the high surface area of the nanocomposites rather than to the composition. With regard to alternative composite synthesis ways, first experiments indicated N-Methyl-2-pyrrolidon to be suitable for higher concentrated dispersion of C₂N nanosheets. Eventually, the results obtained in this thesis provide precious synthetic contributions towards the preparation and processing of carbon/nitrogen compounds for energy applications.
This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. in this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment. Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model performance are considered and that all models are suitable to participate in further multi-model ensemble set-ups and land use change scenario investigations.
An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions.
This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9- year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles. in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non- stationarity of the climate series and possible cross-correlations between models.
We present a catalogue of white dwarf candidates selected from the second data release of Gaia (DR2). We used a sample of spectroscopically confirmed white dwarfs from the Sloan Digital Sky Survey (SDSS) to map the entire space spanned by these objects in the Gaia Hertzsprung–Russell diagram. We then defined a set of cuts in absolute magnitude, colour, and a number of Gaia quality flags to remove the majority of contaminating objects. Finally, we adopt a method analogous to the one presented in our earlier SDSS photometric catalogues to calculate a probability of being a white dwarf (PWD) for all Gaia sources that passed the initial selection. The final catalogue is composed of 486641 stars with calculated PWD from which it is possible to select a sample of ≃260000 high-confidence white dwarf candidates in the magnitude range 8 < G < 21. By comparing this catalogue with a sample of SDSS white dwarf candidates, we estimate an upper limit in completeness of 85 per cent for white dwarfs with G ≤ 20 mag and Teff >7000 K, at high Galactic latitudes (|b| > 20°). However, the completeness drops at low Galactic latitudes, and the magnitude limit of the catalogue varies significantly across the sky as a function of Gaia’s scanning law. We also provide the list of objects within our sample with available SDSS spectroscopy. We use this spectroscopic sample to characterize the observed structure of the white dwarf distribution in the H–R diagram.