Zeitschriftenaufsätze

Relaxation and diffusion measurements were carried out on single and binary liquids filling the pore space of controlled porous glass Vycor with an average pore size of about 4 nm. The dispersion of the longitudinal relaxation time T1 is discussed as a means to identify liquid-surface interaction based on existing models developed for metal-free glass surfaces. In addition, the change of T1 and T2 with respect to their bulk values is discussed, in particular T2 serves as a probe for the strength of molecular interactions. As the native glass surface is polar and contains a large amount of hydroxyl groups, a pronounced interaction of polar and protic adsorbate liquids is expected; however, the T1 dispersion, and the corresponding reduction of T2, are also observed for non-polar liquids such as alkanes and cyclohexane. Deuterated liquids are employed for simplifying data analysis in binary systems, but also for separating the respective contributions of intra- and intermolecular interactions to the overall relaxation rate. Despite the lack of paramagnetic impurities in the glass material, 1H and 2H relaxation dispersions of equivalent molecules are frequently found to differ from each other, suggesting intermolecular relaxation mechanisms for the 1H nuclei. The variation of the T1 dispersion when comparing single and binary systems gives clear evidence for the preferential adsorption of one of the two liquids, suggesting complete phase separation in several cases. Measurement of the apparent tortuosity by self-diffusion experiments supports the concept of a local variation of sample composition within the porespace.

We propose a new approach to dynamical system forecasting called data-informed-reservoir computing (DI-RC) that, while solely being based on data, yields increased accuracy, reduced computational cost, and mitigates tedious hyper-parameter optimization of the reservoir computer (RC). Our DI-RC approach is based on the recently proposed hybrid setup where a knowledge-based model is combined with a machine learning prediction system, but it replaces the knowledge-based component by a data-driven model discovery technique. As a result, our approach can be chosen when a suitable knowledge-based model is not available. We demonstrate our approach using a delay-based RC as the machine learning component in conjunction with sparse identification of nonlinear dynamical systems for the data-driven model component. We test the performance on two example systems: the Lorenz system and the Kuramoto-Sivashinsky system. Our results indicate that our proposed technique can yield an improvement in the time-series forecasting capabilities compared with both approaches applied individually, while remaining computationally cheap. The benefit of our proposed approach, compared with pure RC, is most pronounced when the reservoir parameters are not optimized, thereby reducing the need for hyperparameter optimization.

Aqueous zinc-ion batteries (AZIBs) have attracted the attention of researchers because of their high theoretical capacity and safety. Among the many vanadium-based AZIB cathode materials, zinc vanadate is of great interest as a typical phase in the dis-/charge process. Here, a remarkable method to improve the utilization rate of zinc vanadate cathode materials is reported. In situ growth of Zn2(V3O8)2 on carbon cloth (CC) as the cathode material (ZVOCC) of AZIBs. Compared with the Zn2(V3O8)2 cathode material bonded on titanium foil (ZVO@Ti), the specific capacity increases from 300 to 420 mAh g−1, and the utilization rate of the material increases from 69.60% to 99.2%. After the flexible device is prepared, it shows the appropriate specific capacity (268.4 mAh g−1 at 0.1 A g−1) and high safety. The method proposed in this work improves the material utilization rate and enhances the energy density of AZIB and also has a certain reference for the other electrochemical energy storage devices.

Hysteresis response of epitaxially grown graphene nanoribbons devices on semi-insulating 4H-SiC in the armchair and zigzag directions is evaluated and studied. The influence of the orientation of fabrication and dimensions of graphene nanoribbons on the hysteresis effect reveals the metallic and semiconducting nature graphene nanoribbons. The hysteresis response of armchair based graphene nanoribbon side gate and top gated devices implies the influence of gate field electric strength and the contribution of surface traps, adsorbents, and initial defects on graphene as the primary sources of hysteresis. Additionally, passivation with AlOx and top gate modulation decreased the hysteresis and improved the current-voltage characteristics.

The evaporation of water from bare soil is often accompanied by the formation of a layer of crystallized salt, a process that must be understood in order to address the issue of soil salinization. Here, we use nuclear magnetic relaxation dispersion measurements to better understand the dynamic properties of water within two types of salt crusts: sodium chloride (NaCl) and sodium sulfate (Na2SO4). Our experimental results display a stronger dispersion of the relaxation time T1 with frequency for the case of sodium sulfate as compared to sodium chloride salt crusts. To gain insight into these results, we perform molecular dynamics simulations of salt solutions confined within slit nanopores made of either NaCl or Na2SO4. We find a strong dependence of the value of the relaxation time T1 on pore size and salt concentration. Our simulations reveal the complex interplay between the adsorption of ions at the solid surface, the structure of water near the interface, and the dispersion of T1 at low frequency, which we attribute to adsorption-desorption events.