Search Results (496)

We present a comprehensive spectral and kinematic analysis of 27 polluted white dwarfs selected from a published catalog of polluted white dwarf candidates. Using LAMOST DR9 and Gaia DR3 data, we derive the effective temperature ($T_{\mathrm{eff}}$), surface gravity ($\log g$), and radial velocity ($RV$), and we measure the Ca II K line parameters, including equivalent width ($E{W}_{\mathrm{Ca}\mathrm{II}\mathrm{K}}$) and radial velocity ($R{V}_{\mathrm{Ca}\mathrm{II}\mathrm{K}}$). In addition, we estimate cooling ages and determine the three-dimensional Galactic kinematics and orbital parameters. Our results show that the majority of the targets lie above the pure-ISM expectation for the Ca II K line, suggesting that the line primarily originates from circumstellar material (CSM) rather than the interstellar medium (ISM). For DA-type white dwarfs in our sample, the Ca II K absorption is more prominent at lower effective temperatures and becomes significantly weaker toward higher temperatures, consistent with previous studies of metal-polluted white dwarfs. Additionally, DA stars show prominent $E{W}_{\mathrm{Ca}\mathrm{II}\mathrm{K}}$ values primarily in the cooling-age bin of $0.9$–$1.4\mathrm{Gyr}$, whereas DB stars are concentrated in the ${\tau }_{\mathrm{cool}}\lesssim 0.5\mathrm{Gyr}$ range, with a similar trend of first increasing and then decreasing $E{W}_{\mathrm{Ca}\mathrm{II}\mathrm{K}}$ with cooling age. Kinematic analysis reveals no significant differences between the Galactic populations of DA and DB white dwarfs. These findings indicate that metal pollution is common across different disk components of the Galaxy, with evidence for ongoing or recurrent evolution of white dwarf planetary systems within various Galactic structures. Full article

In this study, we introduce a novel clustering-based methodology for mapping lunar surface mineralogy using hyperspectral data from the Moon Mineralogy Mapper (M³). The proposed methodology utilizes the Hapke photometric model to convert reflectance values to Single Scattering Albedo (SSA) values and constructs the distribution/histogram of the positions where the SSA signatures of the pixels in the entire image exhibit absorptions. Then, based on this histogram, an appropriate feature representation for each pixel is defined, oriented to the characterization of the pixel mineral composition. The k-means clustering algorithm is then applied on the new pixel representations. Mineral composition analysis for each cluster is then performed by evaluating whether the absorption features of each pixel match predefined absorption rules based on the spectral characteristics of eight selected typical minerals found on the Moon. Moreover, the proposed methodology provides mineral compositions within each pixel. The methodology is applied on an M³ dataset covering an area at the eastern Mare Serenitatis and the western Mare Tranquillitatis. The main results reveal spatial and compositional variations among clusters, and they are compatible with prior knowledge on various lunar maria basaltic compositions, demonstrating the reliability of the proposed methodology applied on planetary mineral exploration. Full article

Automated recognition of celestial bodies from observational imagery is a cornerstone of autonomous space exploration. However, deploying deep learning models in space environments entails rigorous requirements not only for accuracy but also for reliability (calibration) and safety (anomaly rejection). Traditional Convolutional Neural Networks (CNNs) trained on small-scale astronomical datasets often suffer from overfitting and overconfidence on Out-of-Distribution (OOD) artifacts. In this work, we present a robust classification framework based on DINOv2, a Vision Transformer pre-trained via discriminative self-supervised learning. We curate a high-fidelity dataset of seven planetary classes sourced from NASA archives and propose a two-stage domain adaptation strategy to transfer large-scale foundation model features to this fine-grained task. Extensive experiments show that our method reaches 100% Top-1 accuracy on the canonical split, and remains highly stable under split variation, achieving 99.43% ± 0.85% Top-1 accuracy across R = 5 repeated stratified splits. More importantly, we address the critical issue of model trustworthiness. Through post hoc temperature scaling, our model achieves a state-of-the-art Expected Calibration Error (ECE) of 0.08%, representing a 36-fold improvement over ResNet50 (2.90%) and a 4.5-fold improvement over the EfficientNet-B3 baseline (0.36%). Furthermore, by integrating Energy-based OOD detection, the system effectively rejects non-planetary artifacts with an AUROC of 93.7%. Qualitative analysis using Grad-CAM reveals that self-supervised attention mechanisms naturally focus on intrinsic planetary features (e.g., surface textures and rings) while ignoring background noise, confirming the superior robustness of vision foundation models in astronomical vision tasks. Full article

Cr-Al composite coatings were fabricated on Ti-6Al-4V alloy substrates via mechanical alloying using a high-energy planetary ball mill. The coatings exhibited a distinctive bilayer architecture comprising an inner layer with coarse reinforcing particles and an outer layer featuring a refined, homogenized microstructure. Systematic investigations were conducted to elucidate the influence of rotational speed on coating formation, microstructural evolution, phase composition, and high-temperature oxidation performance. The findings revealed that insufficient milling speeds failed to facilitate adequate powder deposition, resulting in poor interfacial adhesion and the formation of porous or thin coatings. Conversely, excessive rotational speeds induced surface roughening and coating delamination. Optimization studies identified 250 r/min as the optimal milling speed, yielding dense, well-adherent coatings with superior oxidation resistance. Cyclic oxidation testing at 850 °C demonstrated that coated specimens exhibited significantly reduced mass gain compared to uncoated substrates. Post-oxidation characterization confirmed the formation of a protective corundum-type oxide scale (α-Al₂O₃ and Cr₂O₃) and revealed a four-layered structure in the oxidized coating: (I) a dense oxide film serving as an oxygen barrier, (II) a dense alloyed layer, (III) a porous alloyed layer, and (IV) an inner diffusion zone. These results demonstrate that the mechanically alloyed Cr-Al coatings provide effective protection against high-temperature oxidation for Ti-6Al-4V alloy substrates. Full article

We present new high-dispersion optical spectra of the planetary nebula NGC 2371 obtained with the Manchester Echelle Spectrometer at the OAN-SPM 2.1 m telescope, complemented with 3D morpho-kinematic modelling using ShapeX. The data reveal that the present-day morphology of NGC 2371 is the outcome of multiple episodic mass-loss events rather than a single outflow. Our best-fitting model simultaneously reproduces the direct images and the Position–Velocity (PV) diagrams, and consists of a barrel-shaped shell with younger polar caps, extended bipolar lobes, and a pair of misaligned low-excitation [N ii] knots interpreted as jet-like ejections. The derived kinematical ages of the main structures, spanning ≃1600 to ≃4400 yr, indicate successive episodes of mass loss with different geometries and timescales. The nearly perpendicular bipolar lobes, the absence of a pronounced waist, and the surface distortions of the large-scale structures cannot be explained solely by standard axisymmetric wind interactions. Instead, our results point to a combination of shaping agents, including a late thermal pulse (born-again scenario) possibly related to the H-deficient [WR]-type nature of the central star, binary-driven interactions, and episodic jet activity. NGC 2371 thus provides a particularly instructive case where multiple shaping agents may operate, and where some of the relevant physical processes remain only marginally explored in current models of PN formation and evolution. Full article

Spinning tethered satellite systems represent a promising advancement in the design of spaceborne architectures for Earth and planetary observation. Leveraging the unique advantages of tether technology, such as mass efficiency in deploying large structures and fuel-free formation control, this study explores the feasibility and performance potential of CubeSat-scale spinning tethered formations. These systems consist of multiple spacecrafts connected by a tether, enabling easy dynamic adjustment of inter-satellite spacing and rotational velocity through conservation of angular momentum. Such flexibility facilitates precise, stable formations suitable for a range of remote sensing applications. In this paper, the authors present an overview of the dynamical modelling, deployment strategy, and operational advantages of spinning tether systems, focusing in particular on some key use cases: Earth, Moon and Mars surface observation. Three representative sensing modalities are analysed: (1) stereo imaging, where tethered platforms allow synchronized capture with tuneable baselines; (2) distributed radar sounding, which benefits from mechanically stabilized, spatially dispersed sensors to enhance resolution; and (3) Synthetic Aperture Radar (SAR) interferometry, where tether-induced baseline control improves accuracy and simplifies phase unwrapping. A performance assessment is provided for multiple orbital configurations around the Earth and the Moon. The results demonstrate that, while some issues still need to be explored in more detail, spinning tethered systems can offer competitive or superior observational performance in different mission scenarios compared to current technologies. The main challenges posed by this kind of architecture are discussed, alongside future research directions and development prospects. Full article

High-precision localization of Mars rovers is essential for safe path planning and efficient navigation toward scientific targets. As planetary rovers traverse the surface, their positional uncertainty accumulates, which can be corrected through global localization by registering rover images to orbital maps. To date, image-based solutions are widely adopted; however, substantial manual intervention is often required, which is time-consuming and limits the range of autonomous navigation. To address these challenges, we propose a two-stage localization framework, comprising the Mars cross-view few-shot training paradigm (MarsCVFP), Mars cross-view feature extraction network (MCVN) trained under MarsCVFP, and a robust template matching algorithm. Specifically, the MarsCVFP model can leverage implicit cross-view feature as guidance without relying on a large amount of high-precision location-level supervision and explicitly annotated, specific learning targets in the scene. MCVN can capture discriminative fine-grained features on the weakly textured and unstructured surface of Mars by constructing the multi-scale feature pyramid structure (MSFPS) and the feature interaction module (FIM). We validate our framework on 85 unit-planned sites and 20 panoramic sites, respectively, as traversed by the Zhurong rover. The experimental results demonstrate that our framework consistently outperforms both the traditional approaches and the representative learning-based methods across diverse terrains, including dunes, bedrock, craters, and flat plains, achieving a localization success rate above 82% while maintaining a localization accuracy of better than 4 pixels, even under coarse prior positions uncertainties spanning 40 m × 40 m. Full article

The McMurdo Dry Valleys (DVs) of South Victoria Land, Antarctica, constitute the largest ice-free region on the continent and one of Earth’s most Mars-analog environments. Their hyper-arid polar desert conditions offer a unique setting for investigating surface weathering and mineralogical processes under extreme climates. This study presents the first regional-scale mapping of alteration and crystalline weathering minerals across the McMurdo DVs. It uses Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral data; visible and near-infrared (VNIR) and shortwave infrared (SWIR) bands were analyzed through a Spectral Hourglass Workflow, endmember extraction, and spectral unmixing with Matched Filtering (MF) and Constrained Energy Minimization (CEM). Inter-algorithm consistency analysis between MF and CEM yielded 78.83% overall agreement with a Kappa coefficient of 0.75, indicating strong methodological consistency in mineral discrimination using ASTER VNIR+SWIR data. It should be noted that this agreement reflects internal algorithmic robustness rather than independent geological validation. Geological reliability is instead supported by documented field observations, lithological map comparisons, and spectral correspondence with the USGS spectral library. Validation employed documented field observations, lithological maps, and the USGS spectral library. Results reveal distinct spatial distributions of hematite-limonite/goethite, jarosite, kaolinite/smectite-illite-pyrophyllite-alunite, muscovite, hydrous silica/sericite/jarosite/hematite, epidote/chlorite, and calcite, closely associated with lithological units and unconsolidated deposits in Taylor, Wright, Victoria, and McKelvey Valleys. An inter-algorithm consistency check achieved 78.83% overall accuracy with a Kappa coefficient of 0.75, underscoring the robustness of ASTER VNIR+SWIR data for Antarctic mineral discrimination despite localized spectral mixing. Beyond refining the geological understanding of the McMurdo DVs, these results establish ASTER as an effective tool for regional mineralogical mapping in inaccessible polar terrains. The findings further strengthen the role of the Dry Valleys as a terrestrial analog for Mars, where similar mineralogical assemblages and spectral ambiguities have been observed, thereby contributing to both Antarctic geoscience and planetary exploration frameworks. Full article

In-space manufacturing is essential for achieving long-term planetary colonization, particularly on Mars, where material transport from Earth is both costly and logistically restrictive. Traditional subtractive manufacturing methods are highly equipment-, energy-, and material-intensive, making additive manufacturing (AM) a more practical and sustainable alternative for extraterrestrial production. Among various AM technologies, laser beam powder bed fusion (PBF-LB) stands out due to its exceptional versatility, precision, and capability to produce dense metallic parts with complex geometries. However, conventional PBF-LB processes rely heavily on inert argon environments to prevent oxidation and ensure high-quality part formation—conditions that are difficult to reproduce on Mars. CO₂ makes up over 95% of the Martian atmosphere, meaning printing in a majority-CO₂ environment is of great interest for in situ manufacturing in a Martian colonization effort. This study investigates the feasibility of using pure carbon dioxide (CO₂) as a potential substitute for argon in PBF-LB manufacturing. Single-track and two-dimensional 316L stainless steel specimens were fabricated under argon, CO₂, and ambient air environments with a wide range of laser parameters to evaluate the influence of atmospheric composition on surface morphology, microstructural cohesion, and oxidation behavior. The results reveal that no single parameter controls the overall part quality; rather, a balance of parameters is essential to maintain thermal equilibrium during fabrication. Although parts produced in CO₂ exhibited slightly inferior surface finish, cohesion, and oxidation resistance compared to argon, they performed significantly better than those fabricated in ambient air in terms of balling effects and overall cohesion. These findings suggest that CO₂-assisted PBF-LB could enable sustainable in situ manufacturing on Mars and may also serve as a cost-effective alternative shielding gas for terrestrial applications. Full article

Estimating future air quality under the warming climate is an urgent task for all populated regions. Often, climate models are evaluated with respect to air temperature and precipitation, but without a focus on other air quality-related meteorological variables. This study evaluated a regional ensemble system over the southeast Australian region driven by five selected CMIP6 global climate models (downscaled by two regional models, making the ensemble size ten) in terms of a range of surface variables relevant for air quality from seasonal to diurnal timescales. Results showed that the two regional climate models, although only differing in their planetary boundary layer (PBL) parameterizations, performed quite differently. In general, the regional model with the MYNN2 PBL scheme (named R3) performed better than the other. While most meteorological variables, including surface wind speed, were verified well, wind direction showed large biases and variability among models. When downscaled (~4 km resolution) atmospheric variables were applied to drive the Community Multiscale Air Quality (CMAQ) model, the ensemble members, particularly the two versions of the regional model, resulted in different chemical species concentrations. A model ranking scheme was developed based on various spatiotemporal timescales and identified slightly superior performance by the regional model R3. The findings provide a valuable reference for selecting optimized model members for future air quality projections. Full article

This study reveals the effects of artificial space-like proton irradiation on three meteorite samples that are Northwest Africa (NWA) 4560 LL3.2 and NWA 5838 H6 chondrite meteorites, as well as the Dhofar (Dho) 007 eucrite. We used low-vacuum scanning electron microscopy (LV-SEM) and Raman Spectroscopy to examine the structure and composition of olivine and pyroxene grains in the meteorites before and after the irradiation events. This article focuses on the strongest and most intense irradiation, which was performed by protons up to 12 keV with a fluence value of 10¹⁹ ions/cm² that lasted ~30 h. According to the Raman spectra, significant lattice disruption in all analyzed silicates occurred, and a more extensive amorphous, glassy layer developed under the strongest irradiation conditions. Relative to the second irradiation, peak 1 (820.0 cm⁻¹) shifts slightly negatively (–0.46 cm⁻¹) with a small FWHM increase (+0.88 cm⁻¹), while peak 2 (850.3 cm⁻¹) shifts positively in both parameters (+0.40 and +4.04 cm⁻¹) in NWA 4560 olivines. In NWA 5838 olivines, both olivine peaks (820.5 and 850.8 cm⁻¹) shift positively (+7.40 and +7.90 cm⁻¹) and broaden (+2.75 and +4.29 cm⁻¹). In Dho 007 pyroxenes, peak 1 (997.1 cm⁻¹) shifts positively (+3.01 cm⁻¹) with an FWHM decrease (−0.46 cm⁻¹), peak 2 (669.7 cm⁻¹) shifts slightly negatively (−0.75 cm⁻¹) while broadening strongly (+29.23 cm⁻¹), and peak 3 (327.7 cm⁻¹) shifts positively (+0.86 cm⁻¹) with reduced FWHM (−4.55 cm⁻¹). Three characteristic amorphous bands appear in all examined meteorite silicates, located at ~550–1000 cm⁻¹, ~1100–1700 cm⁻¹, and ~1700–1850 cm⁻¹. Olivines in NWA 4560 and NWA 5838 exhibited similar responses across all irradiation events. In contrast, Dho 007 pyroxenes showed variable compositional changes without a consistent or well-defined pattern in our SEM dataset. The Fo decrease in our experiments likely results from preferential Mg sputtering in the olivine lattice, leading to relative Fe enrichment, similar to but more pronounced than after the first irradiation. Pyroxenes exhibit a comparable response, with Fs and En increasing and Wo sharply decreasing, reflecting preferential Ca loss relative to Mg alongside Fe enrichment. Investigating these processes improves the interpretation of planetary remote sensing data and advances our understanding of planetary surface evolution, while also clarifying how surface materials respond to space environmental conditions. Full article

Global warming (GW) contributions from feedbacks and feedback loops are projected to rise from ≈54% (loops: 29%) in 2024 to ≈71% (loops: 50%) under faltering RCP pathways without Solar Geoengineering (SG) by about 2100. A critical threshold, RCP_Critical, defined as the point at which feedback loops account for more than half of GW, is projected to occur between 2075 and 2125. Beyond this point, reversing warming becomes severely constrained, and climate tipping points become more likely. From these trends, an average mitigation difficulty and cost increase rate (MDCR) of ≈1.33–1.5% per year is estimated. By 2100, absent mitigation, the effort required to offset global warming would roughly double relative to today, approaching an unsustainable mitigation critical threshold. Current feedback levels may already be driving nonlinear warming behavior. These diagnostic estimates align with three key indicators: a minimum-feedback baseline from 1870, an equilibrium climate sensitivity (ECS) range of 3.1 °C–4.3 °C (potentially reached by ≈2082), and consistency with IPCC AR6 confidence bounds. In response, this study proposes Annual Solar Geoengineering-PLUS pathways (ASG+Ps) as supplemental measures. These include Earth Brightening, targeted Arctic Stratospheric Aerosol Injection (SAI), and feasible L1 Space Sunshade systems designed to reduce feedback amplification and extend mitigation timelines. The “PLUS” component refers to the use of increased mitigation levels with a focus on high-amplification regions, particularly the Arctic and the tropics, to help reverse local feedbacks and promote negative feedback loops. These moderate ASG+P pathways directly address AR6 concerns while avoiding many governance challenges of full-scale SG. ASG+Ps are less controversial and provide ≈14× stronger cooling potential per Wm⁻² than Carbon Dioxide Removal (CDR), while allowing variable regional targeting. Meanwhile, RCP2.6 has already been missed, placing RCP4.5 and RCP6 at risk. In 2024, atmospheric CO₂ rose by ≈23 Gt (≈3 ppm), while forest tree losses exceeded afforestation gains by 2×, yielding a 2 GtCO₂ sink loss, further diminishing CDR’s effectiveness. Declines in planetary albedo since 1998 continue to amplify warming. Urbanization accounts for roughly 13% of total surface GW, affecting 60% of the population, underscoring the mitigation potential of urban Earth Brightening. New results here also show major Space Sunshading area reductions, at ≈32× less than prior flawed estimates (detailed here) and ≈1600× less under the ASG+P method, substantially improving feasibility and the importance of space agencies’ needed mitigation role. A coordinated global ASG+P strategy, supported by IPCC working groups and space agencies like NASA/SpaceX, are needed to provide a critical supplemental pathway for climate stabilization. Given the shrinking intervention window, rising MDCR, and the escalating risks to civilization, prioritizing timely work in this area is essential; the investment is minor compared to the trillions in climate financial damages that could be avoided. Full article

Owing to the substantial polarity difference and weak interfacial interaction, the large-scale application of fly ash (FA) in rubber materials still faces substantial challenges. To solve this issue, this study prepared a modified hybrid SSBR@FA filler through a solution mechanochemical reaction between solution-polymerized styrene-butadiene rubber (SSBR) and FA in a lab planetary ball mill. Fourier transform infrared spectroscopy (FTIR) and energy-dispersive spectroscopy (EDS) analyses demonstrated the in situ grafting-neutralization between the carboxyl in the SSBR chains and metal oxides in FA. Transmission electron microscopy (TEM) showed that surface-grafted SSBR formed a rubber-constrained layer on FA particle surfaces, which can reduce their surface energy and improve the wettability between FA and SBR matrix. Compared with the SBR vulcanizate, the mechanical properties, thermal conductivity, and flame-retardant properties of the SBR/SSBR@FA vulcanizates were obviously improved. This was because of the uniform distribution of FA and the improved interfacial interaction between FA and the rubber matrix. For example, the tensile strength, tear strength, and elongation at break increased by 66.3%, 52.9%, and 17.7%, respectively. This easy, efficient, and environmentally modified method for FA was expected offer a practical and creative solution for its application in rubber manufacturing. Full article

Flooding episodes caused by a heavy rainfall event have become more frequent, especially during the rainfall season in Botswana, which poses some socio-economic and environmental risks. This study investigates the capability of the Weather Research and Forecasting (WRF) model in simulating a heavy rainfall event that occurred on 26 December 2023 in Mahalapye District, Botswana. This event is one among many that have negatively impacted the lives and infrastructures in Botswana. The WRF model was configured using the tropical-suite physics schemes, i.e., (Rapid Radiative Transfer Model, Yonsei University planetary boundary layer scheme, Unified Noah land surface model, New Tiedtke, Weather Research and Forecasting Single-Moment six-class) on a two-way nested domain (9 km and 3 km grid spacing) and was initialized with the GFS dataset. Gauged station data was used for verification alongside synoptic charts generated using ECMWF ERA5 dataset. The results show that the WRF model simulation using the tropical-suite physics schemes is able to reproduce the spatial and temporal patterns of the observed rainfall but with some notable biases. Performance metrics, including RMSE, correlation coefficient, and KGE, showed moderate to good agreement, highlighting the model’s sensitivity to physical parameterization and resolution. The results of this study conclude that the WRF model demonstrates promising potential in forecasting extreme rainfall events in Botswana, but more sensitivity tests to different parameterization schemes are needed in order to integrate the model into the early warning systems to enhance disaster preparedness and response. Full article

Accurate global mapping of lunar iron oxide (FeO) abundance is essential for understanding the Moon’s geological evolution and for supporting future in situ resource utilization (ISRU). While hyperspectral data from the Moon Mineralogy Mapper (M3) provide a unique combination of high spectral dimensionality, hectometre-scale spatial resolution, and near-global coverage, existing FeO retrieval approaches struggle to fully exploit the high dimensionality, nonlinear spectral variability, and planetary-scale volume of the Global Mode dataset. To address these limitations, we present an integrated machine learning pipeline for estimating lunar FeO abundance from M3 hyperspectral observations. Unlike traditional methods based on raw reflectance or empirical spectral indices, the proposed framework combines Discrete Wavelet Transform (DWT), deep autoencoder-based feature compression, and ensemble regression to achieve robust and scalable FeO prediction. M3 spectra (83 bands, 475–3000 nm) are transformed using a Daubechies-4 (db4) DWT to extract 42 representative coefficients per pixel, capturing the dominant spectral information while filtering high-frequency noise. These features are further compressed into a six-dimensional latent space via a deep autoencoder and used as input to a Random Forest regressor, which outperforms kernel-based and linear Support Vector Regression (SVR) as well as Lasso regression in predictive accuracy and stability. The proposed model achieves an average prediction error of 1.204 wt.% FeO and demonstrates consistent performance across diverse lunar geological units. Applied to 806 orbital tracks (approximately $3.5\times {10}^9$ pixels), covering more than 95% of the lunar surface, the pipeline produces a global FeO abundance map at 150 m per pixel resolution. These results demonstrate the potential of integrating multiscale wavelet representations with nonlinear feature learning to enable large-scale, geochemically constrained planetary mineral mapping. Full article