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Floods cause extensive global damage annually, making effective monitoring essential. While satellite observations have proven invaluable for flood detection and tracking, comprehensive global flood datasets spanning extended time periods remain scarce. In this study, we introduce a deep learning flood detection model that leverages the cloud-penetrating capabilities of Sentinel-1 Synthetic Aperture Radar (SAR) satellite imagery, enabling consistent flood extent mapping through cloud cover and in both day and night conditions. By applying this model to 10 years of SAR data, we create a unique, longitudinal global flood extent dataset with predictions unaffected by cloud coverage, offering comprehensive and consistent insights into historically flood-prone areas over the past decade. We use our model predictions to identify historically flood-prone areas in Ethiopia and demonstrate real-time disaster response capabilities during the May 2024 floods in Kenya. Additionally, our longitudinal analysis reveals potential increasing trends in global flood extent over time, although further validation is required to explore links to climate change. To maximize impact, we provide public access to both our model predictions and a code repository, empowering researchers and practitioners worldwide to advance flood monitoring and enhance disaster response strategies. Analysis of 10 years of satellite radar data with a deep learning model reveals historical flood patterns often missed in prior datasets. This dataset also enables analysis of trends in flooding, showing hints of increases in flood extent over time.

The direct metal deposition (DMD) additive manufacturing process produces high cooling rates within a small melt pool and can lead to high amounts of solute trapping. These high cooling rates limit diffusion and lead to the formation of non-equilibrium phases. In this work, we utilize a numerical model to calculate the degree of solute trapping, defined as non-equilibrium partitioning. A theoretical case with overall composition fixed to 50Cu–50Fe at.%. was performed to observe the influence of increasing solidification rates. We then simulate DMD of equimolar Cu–Fe powder printed on mild steel substrate and the calculated non-equilibrium phase compositions were consistent with experimental observations reported earlier on this alloy composition. For a single deposited track, cooling rates are high enough to yield significant solute trapping. The degree of solute trapping is highest near the free surface and has a gradient that correlates with the cooling rate gradient. Graphical abstract

The combination of soft nanoscale organic components with inorganic nanograins hierarchically designed by natural organisms results in highly ductile structural materials that can withstand mechanical impact and exhibit high resilience on the macro- and nano-scale. Our investigation of nacre deformation reveals the underlying nanomechanics that govern the structural resilience and absorption of mechanical energy. Using high-resolution scanning/transmission electron microscopy (S/TEM) combined with in situ indentation, we observe nanoscale recovery of heavily deformed nacre that restores its mechanical strength on external stimuli up to 80% of its yield strength. Under compression, nacre undergoes deformation of nanograins and non-destructive locking across organic interfaces such that adjacent inorganic tablets structurally join. The locked tablets respond to strain as a continuous material, yet the organic boundaries between them still restrict crack propagation. Remarkably, the completely locked interface recovers its original morphology without any noticeable deformation after compressive contact stresses as large as 1.2 GPa. Hierarchical structural materials combine organic and inorganic components to withstand mechanical impact but the nanomechanics that govern the superior properties are not well investigated. Here, the authors observe nanoscale recovery of heavily deformed nacre that restores its mechanical strength using high-resolution electron microscopy.

Stress localization ahead of a slip band blocked by a grain boundary is measured for three different grain boundaries in unalloyed Mg using high-resolution electron backscatter diffraction (HR-EBSD). The results are compared with a theoretical dislocation pile-up model, from which slip system resistance and micro-Hall–Petch coefficients for different grain boundary types are deduced. The results indicate that grain boundary character plays a crucial role in determining micro-Hall–Petch coefficients, which can be used to strengthen classical crystal plasticity constitutive models to make predictions linked to the effect of grain boundary strengthening.

Atomically ordered bimetal interfaces typically develop in near-equilibrium epitaxial growth (bottom-up processing) of nanolayered composite films and have been considered responsible for a number of intriguing material properties. Here, we discover that interfaces of such atomic level order can also emerge ubiquitously in large-scale layered nanocomposites fabricated by extreme strain (top down) processing. This is a counterintuitive result, which we propose occurs because extreme plastic straining creates new interfaces separated by single crystal layers of nanometer thickness. On this basis, with atomic-scale modeling and crystal plasticity theory, we prove that the preferred bimetal interface arising from extreme strains corresponds to a unique stable state, which can be predicted by two controlling stability conditions. As another testament to its stability, we provide experimental evidence showing that this interface maintains its integrity in further straining (strains > 12), elevated temperatures (> 0.45 Tm of a constituent), and irradiation (light ion). These results open a new frontier in the fabrication of stable nanomaterials with severe plastic deformation techniques.

Globally consistent measurements of airborne metal concentrations in fine particulate matter (PM 2.5 ) are important for understanding potential health impacts, prioritizing air pollution mitigation strategies, and enabling global chemical transport model development. PM 2.5 filter samples (N ~ 800 from 19 locations) collected from a globally distributed surface particulate matter sampling network (SPARTAN) between January 2013 and April 2019 were analyzed for particulate mass and trace metals content. Metal concentrations exhibited pronounced spatial variation, primarily driven by anthropogenic activities. PM 2.5 levels of lead, arsenic, chromium, and zinc were significantly enriched at some locations by factors of 100–3000 compared to crustal concentrations. Levels of metals in PM 2.5 and PM 10 exceeded health guidelines at multiple sites. For example, Dhaka and Kanpur sites exceeded the US National Ambient Air 3-month Quality Standard for lead (150 ng m −3 ). Kanpur, Hanoi, Beijing and Dhaka sites had annual mean arsenic concentrations that approached or exceeded the World Health Organization’s risk level for arsenic (6.6 ng m −3 ). The high concentrations of several potentially harmful metals in densely populated cites worldwide motivates expanded measurements and analyses.

The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project that includes characterization of chemical and physical attributes of aerosols from filter samples collected worldwide. This paper discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in fine particulate matter (PM (sub 2.5). Our methods infer the spatial and temporal variability of PM (sub 2.5) in a cost-effective manner. Gravimetrically weighed filters represent multi-day averages of PM (sub 2.5), with a collocated nephelometer sampling air continuously. SPARTAN instruments are paired with AErosol RObotic NETwork (AERONET) sun photometers to better understand the relationship between ground-level PM (sub 2.5) and columnar aerosol optical depth (AOD). We have examined the chemical composition of PM (sub 2.5) at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a background comparison. So far, each SPARTAN location has been active between the years 2013 and 2016 over periods of 2-26 months, with an average period of 12 months per site. These sites have collectively gathered over 10 years of quality aerosol data. The major PM (sub 2.5) constituents across all sites (relative contribution plus or minus Standard Deviation) are ammoniated sulfate (20 percent plus or minus 11 percent), crustal material (13.4 percent plus or minus 9.9 percent), equivalent black carbon (11.9 percent plus or minus 8.4 percent), ammonium nitrate (4.7 percent plus or minus 3.0 percent), sea salt (2.3 percent plus or minus 1.6 percent), trace element oxides (1.0 percent plus or minus 1.1 percent), water (7.2 percent plus or minus 3.3 percent) at 35 percent relative humidity, and residual matter (40 percent plus or minus 24 percent). Analysis of filter samples reveals that several PM (sub 2.5) chemical components varied by more than an order of magnitude between sites. Ammoniated sulfate ranges from 1.1 microns per cubic meter (Buenos Aires, Argentina) to 17 microns per cubic meter (Kanpur, India in the dry season). Ammonium nitrate ranged from 0.2 microns per cubic meter (Mammoth Cave, in summer) to 6.8 microns per cubic meter (Kanpur, dry season). Equivalent black carbon ranged from 0.7 microns per cubic meter (Mammoth Cave) to over 8 microns per cubic meter (Dhaka, Bangladesh and Kanpur, India). Comparison of SPARTAN vs. coincident measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at Mammoth Cave yielded a high degree of consistency for daily PM (sub 2.5) (r squared equals 0.76, slope equals 1.12), daily sulfate (r squared equals 0.86, slope equals 1.03), and mean fractions of all major PM (sub 2.5) components (within 6 percent). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 percent for 8 out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi, and Dhaka) are apparent from high Zn to Al ratios. The expected water contribution to aerosols is calculated via the hygroscopicity parameter kappa (sub v (volume)) for each filter. Mean aggregate values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter mean is 0.20 plus or minus 0.04. Chemical composition and water retention in each filter measurement allows inference of hourly PM (sub 2.5) at 35 percent relative humidity by merging with nephelometer measurements. These hourly PM (sub 2.5) estimates compare favourably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r squared equals 0.67 (number equals 3167), compared to r squared equals 0.62 when v (volume) was not considered. SPARTAN continues to provide an open-access database of PM (sub 2.5) compositional filter information and hourly mass collected from a global federation of instruments.

Additive manufacturing (AM) has provided new possibilities for improving the grain boundary properties of metallic components. However, effectively modifying the microstructure, particularly the grain boundary properties, of laser powder bed fusion (L-PBF) components remains a challenge. Post-processing methods have shown some success in adjusting grain boundary angles, but they have limitations when it comes to complex geometries and internal features. In this study, we propose an innovative in situ heat treatment to control the grain boundary properties of L-PBF components. A model is proposed to predict the thermal cycle at a single point, and it is validated through experiments on 2507 super duplex steel and 316L austenitic steel samples. The results demonstrate that, by applying controlled in situ heat treatment, the dynamic recovery processes can be influenced, and thereby the grain boundary properties of the manufactured parts can be controlled. This proposed method improves our understanding of the impact of in situ heat treatment on grain boundary properties and offers potential for designing and fabricating high-performance L-PBF components. The findings from this study lay the groundwork for the further exploration of grain boundary engineering in metallic components using L-PBF. By leveraging in situ heat treatment, future research can open up new avenues in additive manufacturing, facilitating the production of advanced and high-quality metallic components.

The unit processes of precipitate-dislocation interaction in dilute Mg-Nd alloys are elucidated through in situ indentation experiments in TEM. Results suggest that pinned dislocations can glide along the broad facets of extended β 1 precipitates, a common strengthening phase in Mg- rare earth (RE) alloys. A dislocation-theory based analysis suggests that the shape, spacing and orientation (with respect to the glide plane) of β 1 precipitates may favor glide of pinned dislocations along interfaces as opposed to the classical mechanism of bowing and looping around the precipitate.