Energie Baden-Württemberg (Germany)

The move to the cloud raised expectations to finally leave behind on-premises silos and all the issues that accompany them. The complexity of hybrid scenarios, cloud provider lock-in situations and heavy dependencies on centralised cloud services take problems to a next level. Large and complex cyber systems, often encompassing both legacy and cloud, are difficult to maintain and operate, particularly in terms of cyber security. Investing in cyber resilience brings benefits not only in cyber security but also in building, maintaining and operating these systems. This paper introduces a practical model for building resilience within cyber system architectures. The main goal of the model is to reduce complexity and keep distributed large cyber environments manageable. As an architectural approach, the structure of the model extends from the enterprise level through the system level to the component level. The model is accompanied by a selection of basic patterns for building robust and resilient cyber systems. Its applicability is illustrated by some practical use cases in typical on-premises and cloud scenarios. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.

<strong class="journal-contentHeaderColor">Abstract.</strong> Iceland is a major high-latitude dust source area. Airborne Icelandic dust influences the climate system via interacting with radiation, clouds, and biogeochemical systems, impacts the snow/ice albedo, and air quality. These impacts are sensitive to its mineralogical, chemical, and physical composition. However, comprehensive particle measurement and analysis of Icelandic dust is still limited. This study examines dust samples collected during a field campaign in the Dyngjusandur desert (August&ndash;September 2021) using active and passive aerosol sampling. Over 190,000 individual particles, ranging from 0.1 to 120 &micro;m, were analyzed for their chemical and physical properties using scanning electron microscopy/energy dispersive X-ray spectroscopy (ccSEM/EDX). Results show heterogeneity in particle size, shape, and composition. The most abundant particle type was Medium-Al mixed particles, likely glass-like, comprising 35&ndash;93 % of the aerosol volume. Sulfate particles, suggesting volcanic contributions, were detected in some samples. Iron (Fe) and titanium (Ti)-rich particles made up 3.5 % and 1.8 % of the aerosol volume, respectively, mainly in the fine fraction. The median aspect ratio ranged from 1.37 to 1.53, increasing with particle size. Our findings highlight key differences in Icelandic dust compared to Moroccan dust, including higher iron and titanium content and a lack of potassium in Icelandic dust. Additionally, Icelandic dust shows a size-dependent increase in aspect ratio, unlike Moroccan dust, which remains constant. These observations can improve model simulations of high-latitude dust&rsquo;s role in the Earth system.

Abstract. The atmospheric absorption of the oxygen collision complex O2-O2, in the following referred to as O4, can be used to derive properties of aerosols and clouds from remote sensing observations. In recent years, inconsistencies between the measured atmospheric O4 absorption and radiative transfer simulations were found for Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements. In the presented study, over two years of observations from a long-path (LP-) DOAS instrument deployed at the German research station Neumayer, Antarctica, are analysed. While MAX-DOAS instruments measure spectra of scattered sunlight at different elevation angles, LP-DOAS utilises an artificial light source and the atmospheric absorptions are measured along a fixed (and well-defined) light path close to the surface. Further, the pristine measurement location allows to investigate the relation between measured and modelled O4 absorption over a large range of temperatures (-45 °C to +5 °C). Overall good agreement is found between the retrieved O4 absorption cross-sections covering the absorption band at 360 nm and laboratory measurements. While the best agreement is obtained for the Finkenzeller and Volkamer (2022) cross-sections, deviations at cold ambient temperatures (below ca. -25 °C) are observed for the Thalman and Volkamer (2013) cross-sections. Other O4 absorption bands could not be investigated because these are not (fully) within the spectral range of the measured spectra. This study strongly supports the accuracy of commonly used O4 absorption cross-sections in DOAS analyses, while more work is needed to understand the earlier reported inconsistencies in MAX-DOAS observations.

Abstract In this work, a facile hydrometallurgical approach combined with heat treatment has been adopted to recycle spent graphite from retired lithium‐ion battery cells. Graphite regenerated with 18 M H2SO4 leaching leads to a high specific surface area, significant porosity and small crystallite size. The regenerated graphite has been infiltrated with sulfur under solvothermal conditions at 160 °C. The sample containing 68 wt % of sulfur recovers a capacity of 224 mAh/g after 100 cycles. Furthermore, the electrode with a higher sulfur content of 84 wt %, recuperates the specific discharging capacity of 207 mAh/g after 100 cycles. After the initial fading during the first 5–10 cycles, the cathodes based on regenerated graphite demonstrate stable cycling behavior. This research not only offers an accessible and scalable method for regenerating graphite from spent LIBs but also demonstrates a new application of the regenerated graphite in LSBs, showcasing outstanding electrochemical performance.

Driven by the electrification of transport sector the demand of lithium for battery application is increasing exponentially. The major sources for lithium are continental brines and hard minerals where the production comes along with consumptive water requirements and energy intensive processing and extraction. Therefore, it is of tremendous importance to consider alternative, non-conventional, sources and to develop more efficient and environmentally benign Li extraction methods. Geothermal brines can have significant Li concentrations (150–240 mgLi+ L−1)[1] and could represent an attractive sustainable lithium source. Implementing electrochemical methods for lithium extraction offers further advantages of high Li-selectivity, minimal waste production and low water consumption.[2] Here, we present a dual-ion battery type setup for the selective electrochemical Li-adsorption and desorption from geothermal brines. The chloride concentration in brines is a thousand times higher than that of Li+, hence, both species can be captured at opposite electrode sides. In the dual-ion setup presented in this work, Li+ are stored in a Li-selective LiFePO4(LFP) battery electrode and Cl− are stored using bismuth oxychloride (BiOCl) as counter electrode that has shown excellent Cl− storage capabilities and chemical stability in chloride-ion batteries and desalination batteries.[3] In the second step, both ions are released in a recovery solution to yield a Li-rich solution that could be further processed into battery-grade lithium hydroxide or carbonate. The stability of LFP in aqueous solutions and high Li -selectivity makes it a favored candidate for the electrochemical recovery of Li from natural solutions, where a diverse mixture of cations and anion is present.[4] Therefore, we examined the stability of the electrodes in brine solutions by XRD, indicating good reversibility and no intercalation of competitor ions. In addition, the Li-selectivity in extraction/recovery experiments was analyzed by ICP-OES and influences of different process parameters (e.g. current density, pH, temperature) were investigated. The results demonstrate that the LFP/BiOCl dual-ion battery setup is a feasible and promising low cost method for environmentally friendly Li extraction from geothermal brines.

Abstract Wind turbine towers are subjected to highly varying internal loads, characterized by large uncertainty. The uncertainty stems from many factors, including what the actual wind fields experienced over time will be, modeling uncertainties given the various operational states of the turbine with and without controller interaction, the influence of aerodynamic damping, and so forth. To monitor the true experienced loading and assess the fatigue, strain sensors can be installed at fatigue-critical locations on the turbine structure. A more cost-effective and practical solution is to predict the strain response of the structure based only on a number of acceleration measurements. In this contribution, an approach is followed where the dynamic strains in an existing onshore wind turbine tower are predicted using a Gaussian process latent force model. By employing this model, both the applied dynamic loading and strain response are estimated based on the acceleration data. The predicted dynamic strains are validated using strain gauges installed near the bottom of the tower. Fatigue is subsequently assessed by comparing the damage equivalent loads calculated with the predicted as opposed to the measured strains. The results confirm the usefulness of the method for continuous tracking of fatigue life consumption in onshore wind turbine towers.