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The pursuit of materials with enhanced functionality has led to the emergence of metamaterials—artificially engineered materials whose properties are determined by their structure rather than composition. Traditionally, the building blocks of metamaterials are arranged in fixed positions within a lattice structure. However, recent research has revealed the potential of mixing disconnected building blocks in a fluidic medium. Inspired by these recent advances, here we show that by mixing highly deformable spherical capsules into an incompressible fluid, we can realize a ‘metafluid’ with programmable compressibility, optical behaviour and viscosity. First, we experimentally and numerically demonstrate that the buckling of the shells endows the fluid with a highly nonlinear behaviour. Subsequently, we harness this behaviour to develop smart robotic systems, highly tunable logic gates and optical elements with switchable characteristics. Finally, we demonstrate that the collapse of the shells upon buckling leads to a large increase in the suspension viscosity in the laminar regime. As such, the proposed metafluid provides a promising platform for enhancing the functionality of existing fluidic devices by expanding the capabilities of the fluid itself. 

The rise in smart water technologies has introduced new cybersecurity vulnerabilities for water infrastructures. However, the implications of cyber‐physical attacks on the systems like urban drainage systems remain underexplored. This research delves into this gap, introducing a method to quantify flood risks in the face of cyber‐physical threats. We apply this approach to a smart stormwater system—a real‐time controlled network of pond‐conduit configurations, fitted with water level detectors and gate regulators. Our focus is on a specific cyber‐physical threat: false data injection (FDI). In FDI attacks, adversaries introduce deceptive data that mimics legitimate system noises, evading detection. Our risk assessment incorporates factors like sensor noises and weather prediction uncertainties. Findings reveal that FDIs can amplify flood risks by feeding the control system false data, leading to erroneous outflow directives. Notably, FDI attacks can reshape flood risk dynamics across different storm intensities, accentuating flood risks during less severe but more frequent storms. This study offers valuable insights for strategizing investments in smart stormwater systems, keeping cyber‐physical threats in perspective. Furthermore, our risk quantification method can be extended to other water system networks, such as irrigation channels and multi‐reservoir systems, aiding in cyber‐defense planning.

 

Abandoned agricultural fields (old fields) are thought to accumulate soil organic matter (SOM) after cultivation cessation. However, most research on old fields soil carbon (C) and nitrogen (N) sequestration has focused on the surface (10 or 30 cm depth) and overlooked their dynamics below 30 cm. This study quantified C and N stock change in both the surface and subsurface with repeated inventories over 13 years. We conducted repeated soil surveys in 8 old fields that form a 64-year chronosequence at Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota in 2001 and 2014. On average, soil C and N accumulated by 16.5 ± 14.5 g C m−2 y−1 and 1.0 ± 1.1 g N m−2 y−1 in the surface (0–20 cm). In contrast, we found soil C and N decreased by 78.9 ± 26.3 g C m−2 y−1 and 12.9 ± 2.42 g N m−2 y−1 in the subsurface (20–100 cm). The C and N losses in the subsurface soil were correlated with low deep root biomass; the majority of roots are located in the top 20 cm of soil. Such root distribution may be attributed to the continuing dominance of nonnative and shallow-rooted C3 grasses and the lack of legumes after field abandonment. This study shows that agriculture has a long legacy effect after abandonment on subsurface soil C and N. Some abandoned agricultural fields can continue to lose C and N because surface C and N accumulation does not offset the ongoing deeper soil C and N losses. 

The household is an important locus of decision-making regarding food, energy, and water (FEW) consumption. Changes in household FEW consumption behaviors can lead to significant reductions in environmental impacts, but it can be difficult for consumers to compare the relative impacts of their consumption quantitatively, or to recognize the indirect impacts of their household consumption patterns. We describe two novel tools designed to address this problem: A hybrid life cycle assessment (LCA) framework to translate household consumption of food, energy, and water into key environmental impacts including greenhouse gas emissions, energy use, and water use; and a novel software application calledHomeTrackerthat implements the framework by collecting household FEW data and providing environmental impact feedback to households. We explore the question:How can a life cycle assessment-based software application facilitate collection and translation of household consumption data to meaningful environmental impact metrics?A case study in Lake County, Illinois is presented to illustrate use of theHomeTrackerapplication. Output data describing environmental impacts attributable to household FEW consumption in the study area are shown in order to illustrate key features and trends observed in the case study population. The framework and its associated output data can be used to support experimental research at the household scale, allowing for examination of what users purchase and consume over an extended period of time as well as increased understanding of household behavior trends and environmental impacts, and as future work.

 

In this study, we reported the results of high-resolution (${0{^{\prime \prime}_{.}}14}$) Atacama Large Millimeter/submillimeter Array (ALMA) observations of the 225 GHz dust continuum and CO molecular emission lines from the transitional disk around SY Cha. Our high-resolution observations clearly revealed the inner cavity and the central point source for the first time. The radial profile of the ring can be approximated by a bright narrow ring superimposed on a fainter wide ring. Furthermore, we found that there is a weak azimuthal asymmetry in dust continuum emission. For gas emissions, we detected 12CO(2–1), 13CO(2–1), and C18O(2–1), from which we estimated the total gas mass of the disk to be 2.2 × 10−4 M ⊙ , assuming a CO/H2 ratio of 10−4. The observations showed that the gas is present inside the dust cavity. The analysis of the velocity structure of the 12CO(2–1) emission line revealed that the velocity is distorted at the location of the dust inner disk, which may be owing to a warping of the disk or radial gas flow within the cavity of the dust disk. High-resolution observations of SY Cha showed that this system is composed of a ring and a distorted inner disk, which may be common, as indicated by the survey of transitional disk systems at a resolution of ${\sim}{0{^{\prime \prime}_{.}}1}$.

 

Road dust particles including nanoparticles (NPs), with heterogeneous composition, are significant carriers of metals/metalloids and can be further transported into the atmosphere or surface runoff. However, their elemental composition remains poorly defined. In this study, seven road dust samples were collected from different areas in Shanghai, China and were analyzed for total metal concentrations, particle elemental composition and ratios, morphology, composition, and crystalline phases. Overall, the road dust particles were characterized by high concentrations of Fe, Ti, Al, Cr, Ci, V Ni, Cu, Zn, Sn, and Sb, which varied among the samples. Four potential sources of metals were identified using PCA analysis including natural sources, exhaust and non-exhaust emissions, and vehicle electronics. The bulk elemental ratios of Ti/Nb, Ti/Al, Ti/Fe, Pb/Nb, Sn/Nb and W/Nb in the road dust samples were higher than the corresponding reference ratios indicating that the road dust was contaminated with Ti, Pb, Sn, and W. Anthropogenic Ti, Pb, Sn and W were estimated by mass balance calculation and varied between 0.25 and 1.48 × 10 6 μg kg −1 , 0.19 and 1.21 × 10 5 μg kg −1 , 0.98 and 4.22 × 10 4 μg kg −1 , and 0.12 and 1.01 × 10 4 μg kg −1 , respectively. The number concentration of NPs was determined by SP-ICP-TOF-MS and was 0.66–3.3 × 10 10 particles per g for Ti-containing NPs, 0.23–1.51 × 10 10 particles per g for Pb-containing NPs, 0.28–3.10 × 10 9 particles per g for Sn-containing NPs, and 1.34–9.38 × 10 8 particles per g for W-containing NPs, respectively. TEM analysis further confirmed the occurrence of both natural and anthropogenic Ti- and W-containing NPs and the contamination of Pb- and Sn-containing NPs in Shanghai road dust. These NPs could originate from the non-exhaust emission of vehicles and coal combustion. Overall, this study provides a reliable comprehensive approach for the characterization of road dust particles and new insights into the nature of Ti-, Pb-, Sn-, and W-containing particles in dust samples.