Technical University of Berlin

About: Technical University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Laser & Catalysis. The organization has 27292 authors who have published 59342 publications receiving 1414623 citations. The organization is also known as: Technische Universität Berlin & TU Berlin.

Oxygen Evolution Reaction Dynamics, Faradaic Charge Efficiency, and the Active Metal Redox States of Ni–Fe Oxide Water Splitting Electrocatalysts

Abstract: Mixed Ni–Fe oxides are attractive anode catalysts for efficient water splitting in solar fuels reactors. Because of conflicting past reports, the catalytically active metal redox state of the catalyst has remained under debate. Here, we report an in operando quantitative deconvolution of the charge injected into the nanostructured Ni–Fe oxyhydroxide OER catalysts or into reaction product molecules. To achieve this, we explore the oxygen evolution reaction dynamics and the individual faradaic charge efficiencies using operando differential electrochemical mass spectrometry (DEMS). We further use X-ray absorption spectroscopy (XAS) under OER conditions at the Ni and Fe K-edges of the electrocatalysts to evaluate oxidation states and local atomic structure motifs. DEMS and XAS data consistently reveal that up to 75% of the Ni centers increase their oxidation state from +2 to +3, while up to 25% arrive in the +4 state for the NiOOH catalyst under OER catalysis. The Fe centers consistently remain in the +3 sta...

Individual Risk Attitudes: New Evidence from a Large, Representative, Experimentally-Validated Survey

Abstract: This paper presents new evidence on the distribution of risk attitudes in the population, using a novel set of survey questions and a representative sample of roughly 22,000 individuals living in Germany. Using a question that asks about willingness to take risks in general, on an 11-point scale, we find evidence of heterogeneity across individuals, and show that willingness to take risks is negatively related to age and being female, and positively related to height and parental education. We test the behavioral relevance of this survey measure by conducting a complementary field experiment, based on a representative sample of 450 subjects, and find that the general risk question is a good predictor of actual risk-taking behavior. We then use a more standard lottery question to measure risk preferences in our sample of 22,000, and find similar results regarding heterogeneity and determinants of risk preferences, compared to the general risk question. The lottery question also makes it possible to estimate the coefficient of relative risk aversion for each individual in the sample. Using five questions about willingness to take risks in specific domains - car driving, financial matters, sports and leisure, career, and health - the paper also studies the impact of context on risk attitudes, finding a strong but imperfect correlation across contexts. Using data on a collection of risky behaviors from different contexts, including traffic offences, portfolio choice, smoking, occupational choice, participation in sports, and migration, the paper compares the predictive power of all of the risk measures. Strikingly, the general risk question predicts all behaviors whereas the standard lottery measure does not. The best predictor for any specific behavior is typically the corresponding context-specific measure.

Covariate Shift Adaptation by Importance Weighted Cross Validation

Abstract: A common assumption in supervised learning is that the input points in the training set follow the same probability distribution as the input points that will be given in the future test phase However, this assumption is not satisfied, for example, when the outside of the training region is extrapolated The situation where the training input points and test input points follow different distributions while the conditional distribution of output values given input points is unchanged is called the covariate shift Under the covariate shift, standard model selection techniques such as cross validation do not work as desired since its unbiasedness is no longer maintained In this paper, we propose a new method called importance weighted cross validation (IWCV), for which we prove its unbiasedness even under the covariate shift The IWCV procedure is the only one that can be applied for unbiased classification under covariate shift, whereas alternatives to IWCV exist for regression The usefulness of our proposed method is illustrated by simulations, and furthermore demonstrated in the brain-computer interface, where strong non-stationarity effects can be seen between training and test sessions

Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Abstract: Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.