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Windows of opportunity in subseasonal weather regime forecasting: A statistical–dynamical approach
Full text linkThe Madden–Julian Oscillation (MJO) and stratospheric polar vortex (SPV) are prominent sources of subseasonal predictability in the extratropics. It has been shown that the joint interaction of the MJO and the SPV can modulate the preferred phase of the North Atlantic Oscillation (NAO) and the occurrence of weather regimes. However, improving numerical weather prediction (NWP) at 3-week lead times remain underexplored. This study investigates how MJO and SPV phases affect Greenland Blocking (GL) activity and integrates atmospheric state information into a neural network to enhance week 3 weather regime activity forecasts. We define a weather regime activity metric using European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and reforecasts. In reanalyses we find increased GL activity following MJO phases 7, 8, and 1, as well as weak SPV phases, indicating climatological windows of opportunity in line with previous studies. However, ECMWF forecast skill improves only in MJO phases 8 and 1 and weak SPV phases, identifying somewhat different model windows of opportunity. Next, we explore using these findings in postprocessing tools. Climatological forecasts based on MJO/SPV–NAO relationships provide a purely statistical approach to subseasonal GL activity forecasting, independent of NWP models. Notably, MJO-conditioned climatological forecasts show clear signals when evaluated against observed GL activity. Statistical–dynamical models, using neural networks that combine historical atmospheric state data with NWP-derived weather regime metrics, improve weather regime activity forecasts across all regimes considered, achieving an absolute accuracy increase of 5.8 percentage points in forecasting the dominant weather regime compared with ECMWF. This is particularly beneficial to blocking in the European domain, where NWP models often underperform. Atmospheric conditioned and neural network forecasts serve as valuable decision-support tools alongside NWP models, enhancing the reliability of subseasonal predictions
Observation of a low energy nuclear recoil peak in the neutron calibration data of an AlO crystal in CRESST-III
Full text linkThe current generation of cryogenic solid state detectors used in direct dark matter and CENS searches typically reach energy thresholds of (10) eV for nuclear recoils. For a reliable calibration in this energy regime a method has been proposed, providing monoenergetic nuclear recoils at low energies ∼100 eV–1 keV. In this work we report on the observation of a peak at (1113.6) eV in the data of an AlO crystal in CRESST-III, which was irradiated with neutrons from an AmBe calibration source. We attribute this monoenergetic peak to the radiative capture of thermal neutrons on Al and the subsequent deexcitation via single emission. We compare the measured results with the outcome of Geant4 simulations and investigate the possibility to make use of this effect for the energy calibration of AlO detectors at low energies. We further investigate the possibility of a shift in the expected energy scale of this effect caused by the creation of defects in the target crystal
Treatment of Key Aerosol and Cloud Processes in Earth System Models – Recommendations from the FORCeS Project
Full text linkUncertainty in estimations of the net contribution of anthropogenic aerosol particles, particularly of aerosol-cloud interactions (ACIs) to the Earth’s radiation budget, limits our ability to understand past and project future climate change. Earth System Models (ESMs) are among the key tools for assessing the magnitude and impacts of changes in various forcing agents on the global climate system. Hence, improving aerosol and cloud descriptions in ESMs is an important way forward to increase the confidence in estimates of climate impacts of aerosol perturbations in the past, present and future. In the framework of the FORCeS project, experimental and theoretical approaches were combined to bridge the current key gaps in the fundamental understanding of essential aerosol and cloud processes and their descriptions in selected European ESMs. Regarding aerosol types and processes, we focused on organic aerosol, particulate nitrate, absorbing aerosols, and ultrafine aerosol sources including new particle formation and growth. In terms of cloud processes, we targeted cloud droplet activation, hydrometeor growth and evaporation, ice formation and multiplication as well as aerosol processing and scavenging by clouds. The selection was made based on
the identified knowledge gaps in the scientific understanding of these processes and/or their current representation in ESMs, as well as a novel perturbed parameter ensemble approach to detecting potential structural deficiencies in an ESM. Here, we review the state-of-the-art, outline our approach for arriving at recommendations for improving the representation of key aerosol and cloud processes within ESMs, and then provide such recommendations applicable in models operating at the Earth system scale. The limitations of the recommendations, applicability, as well as alternative approaches and future research directions are discussed. Overall, the findings highlight the need for continuous efforts towards smart ways for representing the aerosol number size distribution as well as consistent representations of key parameters (e.g., liquid water
content and cloud droplet number concentration). Furthermore, we provide guidance for future ESM evaluation emphasising, in particular, the need for exploring the consistency of key parameters, process-based (as opposed to parameter-based), and the complementarity of in-situ and remote-sensed measurements for model evaluation
Data & Metadata in the ROCK-IT Project
Full text linkAn overview of the approach and developments from the data management work package within ROCK-I
Spiking Neural Networks for Communication Systems: Encoding Schemes, Learning Algorithms, and Equalization Techniques
Full text linkKünstliche Intelligenz, insbesondere maschinelles Lernen mit künstlichen neu-
ronalen Netzen (ANNs), bietet Lösungsansätze für die wachsende Komplexität
moderner Kommunikationssysteme und ermöglicht Datenübertragung nahe der
theoretischen Grenze. Die steigende Komplexität geht jedoch mit einem hohen
Energieverbrauch und somit mit energieintensiven Systemen einher.
Gepulste neuronale Netze (SNNs) sind vom menschlichen Gehirn inspirierte Mod-
elle, die durch ereignisgesteuerte Mechanismen energieeffiziente Signalverarbeitung
in Echtzeit ermöglichen. Sie unterscheiden sich von ANNs durch ihre inhärente
zeitliche Dynamik, sowie durch ihre Informationsverarbeitung in Form kurzer
binärer Pulse. Offene Herausforderungen sind insbesondere die Wahl geeigneter
Lernregeln und neuronaler Kodierungen zur Konvertierung realer Signale in Pulse.
Diese Arbeit untersucht den Entwurf SNN-basierter Empfänger für verrauschte
sowie frequenzselektive zeitinvariante Kanäle. Der erste Teil fokussiert sich auf
die Entwicklung eines SNN-basierten Detektors für einen verrauschten Kanal.
Untersucht werden drei Lernregeln: eine biologisch inspirierte und zwei gradien-
tenbasierte, wobei die gradientenbasierte Lernregel “Backpropagation through
time mit Ersatzgradienten” als vielversprechende Lernregel identifiziert wird. Weit-
erhin werden verschiedene neuronale Kodierungen untersucht, wobei drei vielver-
sprechende Kandidaten identifiziert werden, z.B. Quantization encoding (QE).
Der zweite Teil widmet sich SNN-basierten Entzerrern und Demappern. Zwei
Architekturen, mit und ohne Entscheidungsrückkopplung, werden jeweils mit den
drei neuronalen Kodierungen kombiniert. Für das Modell einer nicht-kohärenten
optischen Übertragung werden die Ansätze bezüglich ihrer Leistungsfähigkeit und
der Anzahl generierter Pulse verglichen. Der Einsatz von Entscheidungsrückkop-
plung und QE ermöglicht leistungsfähige Entzerrer mit einer geringen Anzahl an
generierten Pulsen. Bemerkenswerterweise übertreffen SNN-basierte Entzerrer
ANN-basierte deutlich hinsichtlich ihrer Leistungsfähigkeit.
Der dritte Teil nutzt Methoden des verstärkenden Lernens (RL) um eine neue
Lernregel für SNNs sowie der neuronalen Kodierung herzuleiten. Es wird ein
RL-basierter Update-Algorithmus eingeführt, der keine Backpropagation benötigt.
Für den SNN-basierten Entzerrer und Demapper werden mittels des neuen Al-
gorithmus die Parameter der neuronalen Kodierung optimiert, wodurch ohne
Leistungseinbußen die Laufzeit, Komplexität und Anzahl der pro Inferenz gener-
ierter Pulse erheblich reduziert wird.
Diese Arbeit leistet einen Beitrag zum erfolgreichen Entwurf von SNN-basierten
Empfängern. Durch die Diskussion zentraler Herausforderungen erleichtert sie
zukünftige Fortschritte im Entwurf und Einsatz energieeffizienter Empfänger auf
Basis von SNNs
Grundlegende Untersuchungen zur magnetisch induzierten Ablösung von Partikelstrukturen von einer Einzelfaser in der Gas-Partikel-Trenntechnik
Full text linkIn der Gasreinigung dienen filternde Abscheider der effizienten Abscheidung fester oder flüssiger
Partikeln aus einem Gasstrom. Mit zunehmender Betriebszeit steigt durch Partikelabscheidung in der
Filtermatrix und/oder dem Aufbau eines Staubkuchens auf der Oberfläche des Filtermediums der
Druckverlust. Dies erhöht den Energiebedarf und erfordert eine periodische Reinigung
(Regeneration) oder den Austausch des Filtermediums. Während Tiefenfilter meist nicht regeneriert
werden, erfolgt die Abreinigung von Oberflächenfiltern üblicherweise durch Druckstöße von der
Reingasseite oder Rückspülen.
Eine Alternative zu diesen Verfahren stellt die magnetisch induzierte Reinigung magnetisierbarer
Kollektoren dar. Dieses innovative Verfahren zur Regeneration von Filtermedien bietet vielseitige
Einsatzmöglichkeiten – insbesondere in Anwendungen, bei denen eine Strömungsumkehr vermieden
und hohe Druckverluste reduziert werden sollen, wie z. B. in Naturzugsystemen. Dabei können
Filterelemente oder gezielt einzelne Kollektoren aus magnetisierbarem Material durch ein externes
Magnetfeld in Bewegung versetzt werden, wodurch nicht-magnetische Partikelstrukturen abgelöst
werden. Das Verfahren ist geräuscharm, kommt ohne zusätzliche mechanische bewegliche
Komponenten im Filter bzw. Gasstrom aus und ermöglicht eine effiziente Ablösung der
abgeschiedenen Partikelstrukturen. Daher eröffnen sich Perspektiven für den Einsatz in
automatisierten Filtersystemen mit adaptiven Reinigungsstrategien.
Ziel dieser Arbeit ist es, ein grundlegendes Verständnis für die magnetisch induzierte Bewegung
eines Kollektors und deren Einfluss auf die Ablösung von Partikelstrukturen unterschiedlicher
Morphologie zu entwickeln
Manufacturability and microstructure of AlSi10Mg/SiC composites with different volume fractions of SiC using laser powder bed fusion
Full text linkIn the present study commercially available AlSi10Mg and SiC powders were mixed in a tumble mixer with resulting compositions of 5, 15 and 25 vol% SiC and processed using laser powder bed fusion. Different process parameters were used to manufacture samples which were characterized by various properties, such as porosity, microstructure and occurring phases to evaluate the manufacturability of the powder mixtures. The samples showed increasing porosity with lowered volumetric energy density and increasing SiC content. Relative densities of about 93.0% (25 vol% SiC), 94.5% (15 vol% SiC) and 98.5% (5 vol% SiC) respectively could be achieved. In addition, the correlation between the used energy density and the retained SiC particles in the samples was investigated. The quantity of retained SiC particles correlates negatively with the achievable density for all compositions, making compromises between these two properties necessary depending on the desired application. It is shown that SiC can get dissolved due to the high absorption of the laser energy resulting in the formation of primary silicon crystals as well as AlC and AlSiC phases. Microstructure characterizations using AFM revealed the influence of the SiC fraction on the eutectic structure and the formation of the new phases. Finally, EDS and TOF-SIMS analysis showed that the formed AlC phase can react with the humidity of ambient air at the surface, leading to localized cracks due to AlOOH formation
Revisiting high-valence dopant mechanisms in Ni-rich cathodes: cation ordering dominates over morphological alignment for enhanced stability
Full text linkLayered ultra-high-nickel oxides are promising cathodes for high-energy-density lithium-ion batteries but suffer from severe structural degradation. Although high-valence doping is widely employed to enhance stability, the underlying mechanism—whether dominated by morphological alignment or cation ordering—remains contested. Through systematic investigation of W-doped LiNiCoMnO across varied doping concentrations and sintering temperatures, this work demonstrates that cation ordering, rather than morphological alignment, plays the decisive role in electrochemical enhancement. Although W-doping refines primary particles and sustains a radial microstructure even under extreme sintering conditions (up to 850 °C), correlation analysis reveals that cycling stability and specific capacity depend strongly on the suppression of Li/Ni cation mixing, while showing only weak correlation with grain morphology. The 0.75 mol% W doped cathode calcined at 800 °C delivered a high specific capacity of 244.3 mAh g and exceptional long-term cyclability, retaining 91.53% capacity after 1000 cycles in full cells. These findings clarify that high-valence dopants enhance performance primarily via lattice stabilization through cation ordering and highlight the necessity of co-optimizing doping content with synthesis temperature. This work revises the conventional understanding of high-valence doping mechanisms by establishing cation ordering as the primary factor for stability, providing a generalizable principle for designing next-generation ultra-high-nickel cathodes
Kinetochore mutations and histone phosphorylation pattern changes accompany holo- and macro-monocentromere evolution
Full text linkCentromeres are essential for kinetochore assembly and spindle attachment. While chromosomes of most species are monocentric with a single centromere, a minority exhibit holocentricity, with a centromere along the chromatid length. Sporadic emergence of holocentricity suggests multiple independent transitions. To explore this, we compare the centromere and (epi)genome organization of two sister genera with contrasting centromere types: Chamaelirium luteum with large macro-monocentromeres and Chionographis japonica with holocentromeres. Both exhibit chromosome-wide histone phosphorylation patterns distinct from typical monocentric species. Kinetochore analysis reveals similar chimeric Borealin in both species, with additional KNL2 loss and NSL1 chimerism in Cha. luteum. The broad-scale synteny between both genomes supports de novo holocentromere formation in Chi. japonica. Despite sharing features with both centromere types, macro-monocentromeres do not represent a direct link between mono- and holocentromeres. We propose a model for the divergent evolution involving kinetochore gene mutations, altered histone phosphorylation patterns, and centromeric satellite DNA amplification
Conformal Polymer Electrolyte Enabled by Nitrile Coordination for Long‐Cycle Solid‐State Lithium Metal Batteries
Full text linkLithium metal is a highly promising anode for next-generation high-energy-density batteries due to its high theoretical capacity, yet its practical application remains hindered by poor interfacial compatibility with polymer solid-state electrolytes (PSEs). Herein, an in situ solidification PSE that utilizes poly(ethyleneglycol)methyletheracrylate (PEGMEA) and methylated pivalonitrile (PN) is developed (PNF), which forms an conformal and mechanically robust solid electrolyte interphase (SEI) on the lithium metal surface. The coordination between the nitrile group (–C≡N) and Li⁺ regulates interfacial ion transport, while the formed organic–inorganic (hybrid) SEI effectively combines mechanical flexibility and interfacial rigidity to buffer lithium volume fluctuations and inhibit dendrite growth. Benefiting from the enhanced Li hopping sites and improved ionic mobility, the PNF electrolyte exhibits high ionic conductivity, i.e., 3.47 × 10 S cm at 30°C. Li | PNF | Li symmetric cells show exceptional cycling stability, surpassing 1000 h at 0.5 mA cm. Notably, Li | PNF | LiFePO cells achieve a capacity retention of 92.8% after 1000 cycles at 0.5C and 78.9% after 2000 cycles at 1C rate, both at 30°C, highlighting the exceptional conformal properties of the electrolyte resulting in the superior cycling performance. This study establishes a design framework for constructing long-term cycling, solid-state lithium-metal batteries through tailored interfacial engineering of PSEs