Zeitschriftenaufsätze

Herein, magnetoelectric microelectromechanical system (MEMS) cantilevers are investigated on basis of a TiN/AlN/Ni laminate derived from experimental sensors using finite-element simulations. With the anisotropic ΔE effect as an implication of the magnetocrystalline anisotropy, the lateral sensitivity of the sensor is studied for different nickel layer thicknesses and boundary conditions. It is found that above 60% of the cantilever length, the nickel is effectively not contributing to the sensor sensitivity anymore which is supported by the investigation of sensors with partial nickel coverage. The boundary condition of the magnetostrictive layer is found to affect the sensitivity of thick layers while it is negligible for thinning layers. Further investigations on basis of polycrystalline untextured nickel with slightly preferred orientations reveal a stronger effect on thin layers than on thicker ones. It is found to arise from relatively large crystals in the high-sensitivity region near the clamping of the sensor. For thicker polycrystalline layers, the ΔE effect reproduces a characteristic based mainly on the (110) and (111) orientations while the (100) orientation appears to be underrepresented.

Alkali metal-CO2 batteries, which combine CO2 recycling with energy conversion and storage, are a promising way to address the energy crisis and global warming. Unfortunately, the limited cycle life, poor reversibility, and low energy efficiency of these batteries have hindered their commercialization. Li-CO2 battery systems have been intensively researched in these aspects over the past few years, however, the exploration of Na-CO2 batteries is still in its infancy. To improve the development of Na-CO2 batteries, one must have a full picture of the chemistry and electrochemistry controlling the operation of Na-CO2 batteries and a full understanding of the correlation between cell configurations and functionality therein. Here, recent advances in CO2 chemical and electrochemical mechanisms on nonaqueous Na-CO2 batteries and hybrid Na-CO2 batteries (including O2-involved Na-O2/CO2 batteries) are reviewed in-depth and comprehensively. Following this, the primary issues and challenges in various battery components are identified, and the design strategies for the interfacial structure of Na anodes, electrolyte properties, and cathode materials are explored, along with the correlations between cell configurations, functional materials, and comprehensive performances are established. Finally, the prospects and directions for rationally constructing Na-CO2 battery materials are foreseen.

Time-resolved photoluminescence (TRPL) measurements and the extraction of meaningful parameters involve four key ingredients: a suitable sample such as a semiconductor double heterostructure, a state-of-the-art measurement setup, a kinetic model appropriate for the description of the sample behavior, and a general analysis method to extract the model parameters of interest from the measured TRPL transients. Until now, the last ingredient is limited to single curve fits, which are mostly based on simple models and least-squares fits. These are often insufficient for the parameter extraction in real-world applications. The goal of this article is to give the community a universal method for the analysis of TRPL measurements, which accounts for the Poisson distribution of photon counting events. The method can be used to fit multiple TRPL transients simultaneously using general kinematic models, but should also be used for single transient fits. To demonstrate this approach, multiple TRPL transients of a GaAs/AlGaAs heterostructure are fitted simultaneously using coupled rate equations. It is shown that the simultaneous fits of several TRPL traces supplemented by systematic error estimations allow for a more meaningful and more robust parameter determination. The statistical methods also quantify the quality of the description by the underlying physical model.

In the reservoir computing literature, the information processing capacity is frequently used to characterize the computing capabilities of a reservoir. However, it remains unclear how the information processing capacity connects to the performance on specific tasks. We demonstrate on a set of standard benchmark tasks that the total information processing capacity correlates poorly with task specific performance. Further, we derive an expression for the normalized mean square error of a task as a weighted function of the individual information processing capacities. Mathematically, the derivation requires the task to have the same input distribution as used to calculate the information processing capacities. We test our method on a range of tasks that violate this requirement and find good qualitative agreement between the predicted and the actual errors as long as the task input sequences do not have long autocorrelation times. Our method offers deeper insight into the principles governing reservoir computing performance. It also increases the utility of the evaluation of information processing capacities, which are typically defined on i.i.d. input, even if specific tasks deliver inputs stemming from different distributions. Moreover, it offers the possibility of reducing the experimental cost of optimizing physical reservoirs, such as those implemented in photonic systems.

Nano-structuring enables us to add additional degrees of freedom to the design of optical elements. Especially the possibility of controlling the polarization is of great interest in the field of nano-structured optics. For being able to exploit the whole range of form-birefringent phase shifts, the aspect ratios of the resulting element are typically much higher than the aspect ratios of conventional diffractive optical elements (DOEs), which does not only pose a challenge on fabrication but also on characterization. We evaluate several well-established approaches for the nondestructive characterization, including Müller-Matrix-Ellipsometry, measurement of the diffraction efficiencies, scattering measurements and calibration with rigorous coupled-wave modelling. The goal is to understand the challenges with all these techniques and combine them to a reliable method for structural reconnaisance of high aspect ratio nanostructures.