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Binder-Free Earth-Based Building Material with the Compressive Strength of Concrete
No full textThe construction industry consumes a substantial amount of resources. The associated environmental degradation and accelerating biodiversity loss highlight the urgent need for sustainable building materials that can match the performance of conventional alternatives. The objective of this experimental study was to investigate a fully reused, binder-free earth-based material that remains recyclable after its useful life. The material consists of smectite-rich excavation earth and processed demolition waste in a 2:1 ratio, which was compacted under high pressures and subsequently tested to evaluate its mechanical properties. Cylindrical specimens were fabricated via double-ended uniaxial compaction at pressures ranging from 12.5 to 100 MPa and consolidation times between 1 s and 30 min. They were then tested for their compressive strength and water durability. The findings indicate a strong positive correlation between compaction pressure, density, and compressive strength. A compressive strength of 19.2 MPa was reached by specimens that were compacted at 100 MPa for 30 min, achieving values comparable to standard C20/25 concrete. Despite an increase in strength, water durability decreased with increasing compaction pressure but improved with higher molding water content, possibly due to changes in the microstructure. The findings confirm that compressed earth can reach similar compressive strength to conventional materials with a significantly smaller ecological footprint
Impact of electronic correlations on the superconductivity of high-pressure CeH₉
No full textRare-earth superhydrides have attracted considerable attention because of their high critical superconducting temperature under extreme pressures. They are known to have localized valence electrons, implying strong electronic correlations. However, such many-body effects are rarely included in first-principles studies of rare-earth superhydrides because of the complexity of their high-pressure phases. In this work, we use a combined density functional theory and dynamical mean-field theory approach to study both electrons and phonons in the prototypical rare-earth superhydride CeH9, shedding light on the impact of electronic correlations on its critical temperature for phonon-mediated superconductivity. Our findings indicate that electronic correlations result in a larger electronic density at the Fermi level, a bigger superconducting gap, and softer vibrational modes associated with hydrogen atoms. Together, the inclusion of these correlation signatures increases the Migdal-Eliashberg superconducting critical temperature from 47 K to 96 K, close to the measured 95 K. Our results reconcile experimental observations and theoretical predictions for CeH₉ and herald a path towards the quantitative modeling of phonon-mediated superconductivity for interacting electron systems
Development and application of a physico-chemical equilibrium model for systematic struvite precipitation from post-aerated municipal anaerobically digested sludge
No full textPhosphorus is a crucial fertilizer for modern agriculture and therefore a key component of our nutritional security, but due to its limited availability, phosphorus recycling is becoming increasingly important. Thus, given the high dissolved phosphorous concentrations (ortho–P) of treatment processes such as anaerobically digested sludge from anaerobic sludge treatment, municipal wastewater treatment with enhanced biological phosphorus removal (EBPR) creates an economically viable opportunity for phosphorus recovery. One approach involves precipitating dissolved phosphorus as struvite (NH₄MgPO₄*6H₂O) by adding magnesium such as MgCl₂*6H₂O in post-aerated, anaerobically digested sludge. The phosphorus can then be recovered from the ash after sludge incineration. However, the physico-chemical processes governing struvite precipitation in post-aerated anaerobically digested sludge have not been thoroughly investigated. To address this gap, the present study develops a physico-chemical equilibrium model for struvite precipitation in post-aerated anaerobically digested sludge using the SIMBA# 3.2 software. The model aims to predict phosphorus recovery in post-aerated anaerobically digested sludge and prevent unwanted precipitation that could clog pipes in downstream processes. The study used three batch experiments with real anaerobically digested sludge (a’ 260 L) to calibrate and validate the model. Results showed good agreement between simulated and measured values for pH, Mg²⁺, Ca²⁺, PO₄-P, and NH₄-N, with deviations generally below 5 %. These findings suggest that the model can support the efficient operation and design of struvite precipitation plants, improving phosphorus recovery and minimizing operational issues without costly trials
Growth mechanisms and mechanical response of 3D superstructured cubic and hexagonal Hf₁₋ₓAlₓN thin films
No full textTransition metal aluminum nitrides are a technologically important class of multifunctional ceramics, however, the HfAlN system remains largely unexplored. We investigate phase stability, nanostructure design, and mechanical behavior of Hf₁₋ₓAlₓNᵧ thin films deposited on MgO(001) substrates using ion-assisted reactive magnetron sputtering. Compared to growth temperature and ion assistance, backscattered Ar neutrals are shown to have a dominant influence on the film structure. The Al-rich (x > 0.41) films form a nanocrystalline morphology consisting of Hf- and Al-rich nanodomains in a wurtzite-hexagonal(h) 0001 fiber-texture exhibiting about 22 GPa hardness, considerably higher than that of a binary AlN. For low Al contents, x directions and the size increases linearly from 9 to 13 Å with rising Al content. Consequently, the nanoindentation hardness increases sharply from 26 GPa for HfNᵧ, to ∼38 GPa for c-Hf₁₋ₓAlₓNᵧ, due to dislocation pinning at the superstructure strain fields. Micropillar compression of c-Hf₀.₉₃Al₀.₀₇N₁.₁₅ shows a considerably higher yield stress compared to HfNᵧ and controlled brittle fracture occurs via {110} slip systems, attributed to superstructure inhibited dislocation motion. In contrast, nanocrystalline h-Hf₀.₅₉Al₀.₄₁N₁.₂₃ exhibits a high yield stress and limited plasticity before strain burst failure
X-Ray-Induced Quenching of the Th²⁹⁹ Clock Isomer in CaF₂
No full textRecent studies have shown that the lifetime of the isomeric ²⁹⁹Th doped in crystals can be shortened by x-ray or laser irradiation, a phenomenon referred to as isomer quenching. We investigate the temperature dependence of x-ray-induced quenching in²⁹⁹T: CaF₂ and identify a correlation with the afterglow of the host crystal. These results suggest a mechanism in which x-ray-induced electrons migrate through the lattice and are captured at Th sites, enabling isomer deexcitation via internal conversion through electron–nucleus coupling. This mechanism links nuclear decay to charge carrier dynamics in the host crystal, providing a new interface between nuclear and solid-state physics. The findings offer a pathway to optimize the performance of solid-state nuclear clocks
Recycling rigid polypropylene from mixed waste: Does the origin affect mechanical recyclate quality?
No full textThe increasing demand for plastic and the shortcoming of overall plastic recycling rates underscore the necessary transition towards a circular economy. In Austria, more than half of the generated plastic waste, especially non-packaging waste, is incinerated because of its disposal in mixed wastes. This highlights a vast untapped potential for recycling. While prior research has primarily focused on recycling plastic packaging waste from mixed waste origin, this study addresses a critical gap by exploring the recycling of non-packaging plastics in different concentrations by specifically examining rigid polypropylene (PP) sourced from a mixed waste material recovery facility. The methodology involves mechanical pre-processing of plastics, such as washing and sink-float separation, followed by polymer processing to evaluate the recyclates' tensile (impact), thermal, morphological and rheological properties. Results indicate that the dirt content of rigid PP after sorting is comparable to that of separately collected waste. Furthermore, homogeneous recyclates with minor polyethene impurities were produced, the quality of which is comparable to commercially available recyclates regarding elastic modulus and yield stress. Although further research on odour contamination, substances of concern, long-term applicability and environmental and economic aspects is necessary, this study demonstrates that a substantial amount of PP can be recovered from mixed wastes in Austria. Ultimately, recycling such plastics can considerably contribute to circularity efforts
Temperature change can solve the Deutsch-Jozsa problem: An exploration of thermodynamic query complexity
No full textWe demonstrate how a single heat exchange between a probe thermal qubit and multiqubit thermal machine encoding a Boolean function can determine whether the function is balanced or constant, thus providing a thermodynamic solution to the Deutsch-Jozsa problem. We introduce a thermodynamic model of quantum query complexity, showing how qubit thermal machines can act as oracles, queried via heat exchange with a probe. While the Deutsch-Jozsa problem requires an exponential encoding in the number of oracle bits, we also explore a restricted Bernstein-Vazirani problem, which admits a linear thermal oracle and a single thermal query solution. We establish bounds on the number of samples needed to determine the probe temperature encoding the solution for the Deutsch-Jozsa problem, showing that it remains constant with problem size. Additionally, we propose a proof-of-principle experimental implementation to solve the three-bit Bernstein-Vazirani problem via thermal kickback. This work bridges thermodynamics and complexity theory, suggesting that quantum thermodynamics could provide an unconventional route to computing beyond classical computation
Density and speed of public charging infrastructure rollout: Accelerating the electrification of the passenger car stock at the federal state level
No full textA focal point in the ``Smart Mobility Strategy'' published by the European Commission is the expansion of public charging infrastructure as a key driver for the electrification of the passenger vehicle stock. Quantified targets have been set for the coming years. In the scientific literature, the geographic allocation of charging stations and the short- and long-term expansion of public charging networks have been frequently studied. These studies typically emphasize high geographic resolution of street networks and traffic flows, while assuming an exogenously determined electrification pathway for passenger cars. Another strand of literature focuses on modeling the adoption of battery-electric vehicles (BEVs), based on detailed representations of consumer decision-making, as well as developments in costs and technical performance. The objective of this work is to bridge these two perspectives by modeling the interaction between charging infrastructure expansion strategies and vehicle adoption. This is done from the viewpoint of a policy-maker operating at the federal state level, aiming for system-cost-optimal decision-making. We focus on two crucial aspects of public charging infrastructure expansion: network density and expansion speed. Additionally, we analyze income-dependent adoption behavior and cross-regional effects between subregions of a federal state. The case study is the Basque Autonomous Community. Preliminary results indicate that early increases in charging site density have a significant positive impact on BEV adoption, particularly among the middle-income population
Strategische Übertragbarkeit bei der Inferenz von Armutsverteilungskarten
Full text linkMaschinelles Lernen bietet eine vielversprechende Lösung für die Erstellung hochauflösender Armutskarten, doch wird seine Anwendung in datenarmen Regionen wie Subsahara-Afrika häufig durch begrenzte verfügbare Erhebungsdaten und unvollständige Geodaten erschwert. Diese Arbeit befasst sich mit diesen Herausforderungen, indem Strategien untersucht werden, um die Übertragbarkeit von Modellen zwischen Ländern zu verbessern und den Umgang mit fehlenden Daten für eine präzise Armutsschätzung zu optimieren. Anhand von Daten aus sechs unterschiedlichen subsaharischen Ländern und vier Datenquellen (Nachtlichter, Bevölkerung, Mobilfunk und Infrastruktur) werden CatBoost-Modelle eingesetzt, um die Rolle der Ländersimilarität für den Modelltransfer zu evaluieren, optimale Strategien zum Umgang mit fehlenden Daten zu bestimmen und die Wirksamkeit verschiedener Transfer-Learning-Techniken zu vergleichen.Die Ergebnisse zeigen, dass die Transferleistung stark von der Ländersimilarität abhängt, wobei der Jones Country Similarity Index besonders aussagekräftig ist. Zudem spielt die Auswahl der Länder, die für das Modelltraining genutzt werden, eine zentrale Rolle: Die Hinzunahme ähnlicher Länder kann die Leistung verbessern, während die Einbeziehung unähnlicher häufig zu negativem Transfer führt. Die Modelle zeigten eine hohe Robustheit gegenüber teilweisem Datenverlust, während sich die Rekonstruktion fehlender Featurekategorien als weniger wirksam erweist. Unter den Transfer-Learning-Methoden zeigte Feature Augmentation die höchste Wirksamkeit und übertraf in fünf von sechs Ländern die Baseline-Ergebnisse. Die Ergebnisse sind in einem praxisnahen Entscheidungsrahmenwerk für die Armutskartierung in datenarmen Umgebungen zusammengefasst.Machine learning offers a promising solution for high-resolution poverty mapping, but its application in data-scarce regions like sub-Saharan Africa is often hampered by limited ground-truth survey data and incomplete geospatial features. This thesis addresses these challenges by investigating strategies to enhance model transferability and manage missing data for accurate poverty estimation. Using data from six diverse sub-Saharan African countries and four feature sources (nighttime lights, population, cell towers, and infrastructure), this study employs CatBoost models to evaluate the role of country similarity in model transfer, determine optimal strategies for handling missing data, and benchmark the effectiveness of various transfer learning techniques.The findings show that transfer performance is strongly influenced by country similarity, with the Jones Country Similarity Index proving most predictive. Moreover, the choice of source countries matters greatly: adding data from similar countries can improve performance, whereas including dissimilar ones often introduces negative transfer. Retraining on available features consistently outperformed reconstructing missing ones, indicating model robustness to partial data loss. Among transfer learning methods, Feature Augmentation was most effective, outperforming within-country baselines in five of six countries. The study contributes a practical framework for poverty mapping in data-scarce environments