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A new micro/mesoporous hybrid clay nanocomposite prepared from kaolinite clay, Carica papaya seeds, and ZnCl2 via calcination in an inert atmosphere is presented. Regardless of the synthesis temperature, the specific surface area of the nanocomposite material is between ≈150 and 300 m2/g. The material contains both micro- and mesopores in roughly equal amounts. X-ray diffraction, infrared spectroscopy, and solid-state nuclear magnetic resonance spectroscopy suggest the formation of several new bonds in the materials upon reaction of the precursors, thus confirming the formation of a new hybrid material. Thermogravimetric analysis/differential thermal analysis and elemental analysis confirm the presence of carbonaceous matter. The new composite is stable up to 900 °C and is an efficient adsorbent for the removal of a water micropollutant, 4-nitrophenol, and a pathogen, E. coli, from an aqueous medium, suggesting applications in water remediation are feasible.
Trait-based approaches to investigate (short- and long-term) phytoplankton dynamics and community assembly have become increasingly popular in freshwater and marine science. Although the nature of the pelagic habitat and the main phytoplankton taxa and ecology are relatively similar in both marine and freshwater systems, the lines of research have evolved, at least in part, separately. We compare and contrast the approaches adopted in marine and freshwater ecosystems with respect to phytoplankton functional traits. We note differences in study goals relating to functional trait use that assess community assembly and those that relate to ecosystem processes and biogeochemical cycling that affect the type of characteristics assigned as traits to phytoplankton taxa. Specific phytoplankton traits relevant for ecological function are examined in relation to
herbivory, amplitude of environmental change and spatial and temporal scales of study. Major differences are identified, including the shorter time scale for regular environmental change in freshwater ecosystems compared to that in the open oceans as well as the
type of sampling done by researchers based on site-accessibility. Overall, we encourage researchers to better motivate why they apply trait-based analyses to their studies and to make use of process-driven approaches, which are more common in marine studies. We further propose fully comparative trait studies conducted along the habitat gradient spanning freshwater to brackish to marine systems, or along geographic gradients. Such studies will benefit from the combined strength of both fields.
Alluvial and transport-limited bedrock rivers constitute the majority of fluvial systems on Earth. Their long profiles hold clues to their present state and past evolution. We currently possess first-principles-based governing equations for flow, sediment transport, and channel morphodynamics in these systems, which we lack for detachment-limited bedrock rivers. Here we formally couple these equations for transport-limited gravel-bed river long-profile evolution. The result is a new predictive relationship whose functional form and parameters are grounded in theory and defined through experimental data. From this, we produce a power-law analytical solution and a finite-difference numerical solution to long-profile evolution. Steady-state channel concavity and steepness are diagnostic of external drivers: concavity decreases with increasing uplift rate, and steepness increases with an increasing sediment-to-water supply ratio. Constraining free parameters explains common observations of river form: to match observed channel concavities, gravel-sized sediments must weather and fine – typically rapidly – and valleys typically should widen gradually. To match the empirical square-root width–discharge scaling in equilibrium-width gravel-bed rivers, downstream fining must occur. The ability to assign a cause to such observations is the direct result of a deductive approach to developing equations for landscape evolution.
Perovskite solar cells combine high carrier mobilities with long carrier lifetimes and high radiative efficiencies. Despite this, full devices suffer from significant nonradiative recombination losses, limiting their VOC to values well below the Shockley–Queisser limit. Here, recent advances in understanding nonradiative recombination in perovskite solar cells from picoseconds to steady state are presented, with an emphasis on the interfaces between the perovskite absorber and the charge transport layers. Quantification of the quasi‐Fermi level splitting in perovskite films with and without attached transport layers allows to identify the origin of nonradiative recombination, and to explain the VOC of operational devices. These measurements prove that in state‐of‐the‐art solar cells, nonradiative recombination at the interfaces between the perovskite and the transport layers is more important than processes in the bulk or at grain boundaries. Optical pump‐probe techniques give complementary access to the interfacial recombination pathways and provide quantitative information on transfer rates and recombination velocities. Promising optimization strategies are also highlighted, in particular in view of the role of energy level alignment and the importance of surface passivation. Recent record perovskite solar cells with low nonradiative losses are presented where interfacial recombination is effectively overcome—paving the way to the thermodynamic efficiency limit.
We combine ultrafast X-ray diffraction (UXRD) and time-resolved Magneto-Optical Kerr Effect (MOKE) measurements to monitor the strain pulses in laser-excited TbFe2/Nb heterostructures. Spatial separation of the Nb detection layer from the laser excitation region allows for a background-free characterization of the laser-generated strain pulses. We clearly observe symmetric bipolar strain pulses if the excited TbFe2 surface terminates the sample and a decomposition of the strain wavepacket into an asymmetric bipolar and a unipolar pulse, if a SiO2 glass capping layer covers the excited TbFe2 layer. The inverse magnetostriction of the temporally separated unipolar strain pulses in this sample leads to a MOKE signal that linearly depends on the strain pulse amplitude measured through UXRD. Linear chain model simulations accurately predict the timing and shape of UXRD and MOKE signals that are caused by the strain reflections from multiple interfaces in the heterostructure.
We show that the codifference is a useful tool in studying the ergodicity breaking and non-Gaussianity properties of stochastic time series. While the codifference is a measure of dependence that was previously studied mainly in the context of stable processes, we here extend its range of applicability to random-parameter and diffusing-diffusivity models which are important in contemporary physics, biology and financial engineering. We prove that the codifference detects forms of dependence and ergodicity breaking which are not visible from analysing the covariance and correlation functions. We also discuss a related measure of dispersion, which is a nonlinear analogue of the mean squared displacement.