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We consider space-based radiation damage and its cumulative effect on detector dark counts for satellite-based silicon single-photon detectors, arising from natural radiation as well as from a nuclear disturbed environment caused by a high-altitude nuclear explosion.
Fiber-reinforced thermoplastic composites continue to be implemented in several marketsbecause of their strength capacity and light weight. Especially in the wind industry, wind bladesare made of this material which makes them ideal for wind energy generation, but bladesbecome a problem at end-of-life. Because recycling thermoplastic composites technologiesare still not cost and environmentally effective, research in this space is needed. This paperpresents a case study for coupling repurposed wind turbine blades and 3D printing technology.The purpose is to remanufacture decommissioned wind blades into bus stop roof and seatingsections to then use recycled glass fiber from a decommissioned wind turbine blade to 3Dprint structural and/or fixtures needed in the assembly. We provide an overview of the designprocess, and the development process steps in repurposing and 3D printing the material,delving into key parameters required for a successful implementation.
The marine renewable energy (MRE) industry has faced many challenges in getting projects in the water. In many cases, this is due to long consenting timelines, and occasionally active public opposition, often related to concerns about environmental effects or potential conflicts with other uses of the ocean space. While these concerns are very real, some of them are based on misconceptions or lack of familiarity with MRE devices and how they function (Boudet et al. 2020; Karytsas & Theodoropoulou 2014), or uncertainty or misinformation regarding how MRE devices may affect the environment. These misconceptions are common challenges for other renewable energy sectors or other developments in the ocean (Caporale et al. 2020; Scott 2022; Wiersma & Devine-Wright 2014), though the details of device design, site-specific environmental effects, risk and benefit perceptions, and workforce development may be unique to MRE
Abstract Optimizing nitrogen (N) management is an important factor for sustainable perennial biomass systems. However, N application is costly, both financially and environmentally. Our objectives were to determine: (1) N rate and plant spacing effects on yield and yield components of prairie cordgrass swards and (2) fertilizer N replacement value (FNRV) of kura clover in prairie cordgrass-kura clover binary mixtures. Plots were established in Illinois, Minnesota, South Dakota, and Wisconsin, USA, in 2010. Kura clover was transplanted on 30-cm centers in all treatments in which it was a component; prairie cordgrass seedlings were transplanted within the kura clover on 60- and 90-cm centers. Monoculture prairie cordgrass stands were established at the same population densities of mixed stands and fertilized with 0, 75, 150, or 225 kg N ha -1 . Biomass was harvested in the autumn from 2011 to 2013. N (urea), year, plant spacing, and year × plant spacing affected prairie cordgrass production at all locations. Prairie cordgrass yield increased with N application, but the response varied by location. N application tended to increase prairie cordgrass tiller density and consistently increased tiller mass. Prairie cordgrass yield with 0 N was equal to or less than the yield of prairie cordgrass/kura clover mixtures at all locations in 2011 and 2012; however, kura clover provided a FNRV of 25–82 kg N ha -1 to prairie cordgrass in 2013. Kura clover has potential to provide N to prairie cordgrass in binary mixtures of these two species and on land that may not be easily farmed due to wetness.
The placement and operation of marine energy deployments in the ocean have the potential to change flow patterns, decrease wave heights, and/or remove energy from the oceanographic system. Changes in oceanographic systems resulting from harvesting marine energy, particularly tidal and wave energy, may be of concern. These changes include alterations in nearfield and farfield physical processes, as well as potential secondary environmental effects such as changes in sediment transport patterns, biological processes, or coastal erosion. Knowledge of changes in oceanographic systems associated with marine energy is primarily available from numerical modeling studies, informed by some laboratory tests and very few field measurements. A literature review was conducted using the Tethys knowledge base and other online sources, building on conclusions from the Ocean Energy Systems-Environmental State of the Science report. Potential changes in oceanographic systems that may be caused by marine energy differ between tidal and wave devices because of different extraction mechanisms and siting locations. Numerical models show that tidal extraction on the order of hundreds of megawatts or with significant channel blockage is required to create changes in oceanographic processes that exceed natural variability. Effects from wave energy extraction in arrays are localized and dependent on array spacing and proximity to the shore. Here the available evidence supports the conclusion that the risk of significant environmental effects from such changes could be retired (i.e., less investigation required for every project) for small deployments—those representative of the state of the industry in 2021. Determining changes in oceanographic systems to be low risk for small deployments can thereby streamline environmental consenting by reducing monitoring needs at this early stage in the industry.
Abstract Introduction Rapidly advancing technologies and accumulating information about microbial communities across the globe allow the quantification of microbial properties and functions at a macro‐scale. These emerging microbial biogeographic patterns call for a practical macroecological approach to investigate their underlying mechanisms. Aims The primary aims of this paper are to review the advancements of microbial macroecology in seeking mechanisms governing microbial biogeographic patterns, and to further lay out a roadmap for microbial macroecology in 10 years. Methods We reviewed the progress of microbial macroecology and demonstrated the application of the microbial macroecological approach to microbial biogeographic patterns with three case studies. Results Microbial macroecology provides a platform for understanding microbial abundance, community structure, and functioning across space, time, and taxonomic hierarchy. It emphasizes the integral effects of environmental filtering, microbial responses, diversification, dispersal, and local extinction that drive the microbial biogeographic patterns. The microbial macroecological approach emphasizes the last two stages of the four‐stage scientific method applied to microbial ecology: (a) describing microbial traits across scales to reveal patterns, (b) mathematically representing these patterns, (c) developing and testing conceptual models to build a mechanistic understanding of these patterns from a macroecological perspective, (d) plugging the new knowledge into the theoretical advancements. Three case studies were used to demonstrate the microbial macroecological approach for understanding the global patterns of microbial biomass carbon, microbial composition (fungi : bacteria ratio), and microbial carbon use efficiency. Conclusions Microbial macroecology offers a platform for understanding the mechanisms that drive biogeographic patterns of microbial abundance, diversity and functions. It is likely that these patterns and mechanisms will be increasingly incorporated into predictive models that link climate, carbon dynamics, and biogeochemical processes. A roadmap is outlined for the growing microbial macroecology field; we expect significant progress will be made in five research directions over the next 10 years.
Deep learning (DL) presents new opportunities for enabling spacecraft autonomy, onboard analysis, and intelligent applications for space missions. However, DL applications are computationally intensive and often infeasible to deploy on radiation-hardened (rad-hard) processors, which traditionally harness a fraction of the computational capability of their commercial-off-the-shelf counterparts. Commercial FPGAs and system-on-chips present numerous architectural advantages and provide the computation capabilities to enable onboard DL applications; however, these devices are highly susceptible to radiation-induced single-event effects (SEEs) that can degrade the dependability of DL applications. In this article, we propose Reconfigurable ConvNet (RECON), a reconfigurable acceleration framework for dependable, high-performance semantic segmentation for space applications. In RECON, we propose both selective and adaptive approaches to enable efficient SEE mitigation. In our selective approach, control-flow parts are selectively protected by triple-modular redundancy to minimize SEE-induced hangs, and in our adaptive approach, partial reconfiguration is used to adapt the mitigation of dataflow parts in response to a dynamic radiation environment. Combined, both approaches enable RECON to maximize system performability subject to mission availability constraints. We perform fault injection and neutron irradiation to observe the susceptibility of RECON and use dependability modeling to evaluate RECON in various orbital case studies to demonstrate a 1.5–3.0× performability improvement in both performance and energy efficiency compared to static approaches.
The building sector is a major consumer of energy, making it essential to explore innovative strategies for reducing its environmental impact. As we shift our focus toward decarbonization and electrification, the need for advanced building operation techniques and equipment becomes increasingly urgent. These advancements are crucial for maintaining or enhancing indoor environmental quality while simultaneously minimizing energy consumption. This Special Issue aims to showcase cutting-edge technologies in building energy management, alongside effective measurement and verification methods. It will also address fault detection and diagnosis approaches, leveraging both simulation and experimental studies. The ultimate goal is to highlight solutions that not only reduce CO₂ emissions but also improve indoor environmental quality, creating healthier and more sustainable living and working spaces. By presenting a diverse array of research contributions, this Special Issue will provide valuable insights into the latest advancements in building energy technologies. It will drive the discussion around effective strategies for energy efficiency and environmental sustainability in the building sector. These efforts can help transform buildings from energy consumers into more efficient spaces that contribute to reducing our overall carbon footprint.
Current carbon cycle models focus on the effects of climate and land-use change on primary productivity and microbial-mineral dependent carbon turnover in the topsoil, while less attention has been paid to vertical soil processes and soil-dependent response to land-use change along the profile. In this study, a spatial-temporal analysis was used to estimate soil organic carbon (SOC) change in topsoil/A horizon and subsoil/B horizon at National Ecological Observatory Network (NEON) sites, USA over 30 years. To separate the effects of land-use, environmental, and edaphic factors on SOC change, space-for-time substitution was used in combination with the Continuous Change Detection and Classification algorithm and Structural Equation Modeling. Results showed that (a) under natural vegetation, Spodosols and Inceptisols found in the eastern NEON sites had substantial topsoil SOC accumulation (+0.4 to +1.2 Mg C ha –1 year –1 ), while Inceptisols and Andisols in the west had a comparable magnitude of topsoil SOC loss (–0.5 to –1.8 Mg C ha –1 year –1 ); (b) Mollisols and Alfisols in the Central Plains sites were susceptible to significant SOC loss under farming and grazing; (c) Runoff/erosion and leaching potential, vertical translocation, and mineral sorption were the most important factors controlling SOC variation across the NEON sites. Our work could be used to parameterize ecosystem models simulating SOC change.
Local adaptation is an important process in plant evolution, which can be impacted by differential pathogen pressures along environmental gradients. However, the degree to which pathogen resistance loci vary in effect across space and time is incompletely described. As such, to understand how the genetic architecture of resistance varies across time and geographic space, we quantified rust ( Puccinia spp.) severity in switchgrass ( Panicum virgatum ) plantings at eight locations across the central USA for 3 yr and conducted quantitative trait locus (QTL) mapping for rust progression. We mapped several variable QTLs, but two large-effect QTLs which we have named Prr1 and Prr2 were consistently associated with rust severity in multiple sites and years, particularly in northern sites. By contrast, there were numerous small-effect QTLs at southern sites, indicating a genotype-by-environment interaction in rust resistance loci. Interestingly, Prr1 and Prr2 had a strong epistatic interaction, which also varied in the strength and direction of effect across space. Our results suggest that abiotic factors covarying with latitude interact with the genetic loci underlying plant resistance to control rust infection severity. Furthermore, our results indicate that segregating genetic variation in epistatically interacting loci may play a key role in determining response to infection across geographic space.
Net photosynthesis (A N ) is a key component of the global carbon cycle influencing climate feedback over decadal scales. Although plant acclimation to environmental changes can modify A N , traditional vegetation models in Earth system models (ESMs) often rely on plant functional type (PFT)-specific parameterizations or simplified acclimation assumptions limiting generalizability across time, space, and PFTs. In this study, we developed a differentiable photosynthesis model to learn the environmental dependencies of V c,max25 (maximum carboxylation rate at 25°C, representing photosynthetic capacity), as this genre of hybrid physics-informed machine learning can seamlessly train neural networks and process-based equations together. Compared to PFT-specific parameterization of V c,max25 , learning the environment dependencies of key photosynthetic parameters improved model spatiotemporal generalizability. Applying environmental acclimation to V c,max25 led to substantial variations in global mean A N indicating the need to address acclimation in ESMs. The model effectively captured multivariate observations (V c,max25 , A N , and stomatal conductance (g s )) simultaneously with multivariate constraints, improving generalization across space and PFTs. It also learned sensible acclimation relationships of V c,max25 to different environmental conditions. The model explained more than 54%, 57%, and 62% of the variance of A N , g s , and V c,max25 , respectively, presenting a first global-scale spatial test benchmark of A N and g s . These results highlight the potential for differentiable modeling to enhance process-based modules in ESMs and effectively leverage information from large, multivariate data sets.
Demand for energy and the environmental consequences associated with fossil fuel emissions has created a need for alternative energy sources. To avoid conflict over the conversion of existing agricultural land from food production to fuel production, bioenergy crops could instead be cultivated on marginal land. Here, this study compared the performances, biomass yield, tiller density, and lignocellulosic bioenergy feedstock composition of four prairie cordgrass populations with two-row spacings cultivated on a waterlog-prone marginal land, as well as three other bioenergy candidate crops used as controls: big bluestem, M. × giganteus , and switchgrass. Across all populations and spacings, annual biomass yield of prairie cordgrass was 13 Mg ha −1 . Row spacing had significant impacts on prairie cordgrass productivity, with higher biomass yields observed in the 45 cm spacing than in the 90 cm spacing. Feedstock composition (cellulose, hemicellulose, ADL, and ash concentration) was not influenced by row spacing and did not deviate from expected values for growth on agricultural lands. However, biomass yields of the control species M . × giganteus and switchgrass planted in 45 cm spacing were higher than the prairie cordgrass. Our results provide evidence that prairie cordgrass could be a good energy crop with comparable biomass yield production to the energy crops M . × giganteus and switchgrass on waterlogged marginal land.
Understanding how protective coatings respond to the harsh low-Earth orbit (LEO) environment is essential for ensuring the safety, longevity, and cost-effectiveness of spacecraft. In particular, identifying environmentally friendly, non-chromate alternatives that can maintain performance under such conditions has both technological and regulatory significance. This study investigates the environmental stability of zirconium-based hybrid conversion coatings with Cu additives (Cu10 and Cu20) applied to cold-rolled steel, tested in the Materials International Space Station Experiment (MISSE) outside the International Space Station (ISS). Chemical and morphological analyses were carried out using a combination of electron microscopy and X-ray spectroscopy techniques, including scanning electron microscopy (SEM), scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy (STEM-EDS), X-ray photoelectron spectroscopy (XPS), and X-ray absorption near-edge structure (XANES) spectroscopy. After exposure outside the ISS, all coatings remained structurally intact, with all exhibiting a uniform Zr-rich matrix and embedded Cu-rich clusters, while a thin Si-rich surface layer developed from interaction with space environments. Depth-resolved XPS showed a layered structure with CuO on the surface, Cu 2 O, and partial Zr(IV) reduction near Cu-rich sites, evidence of Atomic Oxygen (AO)-driven surface oxidation. These results demonstrate that Cu–Zr coatings maintain their chemical integrity and microstructure in harsh space environments, offering a non-chromate alternative for long-term aerospace protection. These insights provide valuable guidance for developing next-generation protective coatings that combine environmental sustainability with the reliability required for future aerospace and orbital applications.
Diamond offers unique properties for radiation detection, including high radiation hardness, very low gamma sensitivity, and fast response. Conventional diamond detectors rely on charge collection, but this approach requires ultra-pure single crystals and suffers from radiation-induced degradation. Here, in this work, we demonstrate an alternative approach using diamonds as scintillators for detection of charged particles and thermal neutrons. Prototypes were fabricated from commercially available diamond powders bonded to glass substrates and coupled with 6 LiF converters and silicon photomultipliers (SiPMs) and conventional PMTs. We characterized their scintillation properties under alpha particle excitation, x-ray photoluminescence, and thermal neutrons. The tryout detectors exhibit strong scintillation light signals, nanosecond-scale response times, and neutron detection efficiencies up to approximately 14 %, evaluated by comparison to conventional 3 He detector with known efficiency. These results demonstrate the feasibility of cost-effective, lightweight and robust diamond scintillation detectors for applications in space and planetary science, nuclear security, safeguards and environmental monitoring requiring efficient, robust, gamma-blind neutron detectors.
The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. Furthermore, the effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.
Next-generation communication technology will be made possible by cooperation between terrestrial networks with nonterrestrial networks (NTNs) composed of high-altitude platform stations (HAPSs) and satellites. Further, as humanity embarks on the long road to establish new habitats on other planets, the cooperation between NTNs and deep-space networks (DSNs) will be necessary. In this regard, we propose the use of reconfigurable intelligent surfaces (RISs) to improve coordination between these networks given that RISs perfectly match the size, weight, and power (SWaP) restrictions of operating in space. Here, a comprehensive framework of RIS-assisted nonterrestrial and interplanetary communications is presented that pinpoints challenges, use cases, and open issues. Furthermore, the performance of RIS-assisted NTNs under environmental effects, such as solar scintillation and satellite drag, is discussed in light of simulation results.
High-entropy alloys (HEAs) have emerged as a promising class of bifunctional electrocatalysts capable of simultaneously driving the hydrogen evolution reaction (HER) and the oxygen reduction reaction (ORR) with high activity and durability. Their near-equiatomic multicomponent compositions give rise to unique physicochemical characteristics, including lattice distortion, sluggish diffusion, high-entropy stabilization, and pronounced electronic heterogeneity, that collectively generate diverse and synergistic active sites inaccessible in conventional alloys. This review summarizes recent progress in HEA-based bifunctional electrocatalysis, with a focus on the fundamental mechanisms governing HER and ORR activity, stability, and selectivity. We discuss advances in synthesis strategies, ranging from confined growth and step-alloying to scalable continuous-flow methods, that enable precise control over composition, size, and surface structure. Complementary computational and data-driven approaches, including density functional theory, machine-learning-assisted screening, and descriptor development, are highlighted as essential tools for navigating the vast HEA design space and establishing structure−property relationships. Particular attention is paid to adsorption-energy distributions, multisite cooperativity, and environmental effects under realistic electrochemical conditions. Finally, we outline current challenges and future opportunities for integrating mechanistic understanding with AI-guided, closed-loop design frameworks to accelerate the discovery of next-generation HEA bifunctional electrocatalysts for sustainable energy conversion.
To ensure the rapid development, deployment, and use of advanced nuclear technologies, faster qualification approaches are needed. Typically, the primary pathway uses traditional data packages consistent with the American Society of Mechanical Engineers Boiler and Pressure Vessel Code, which does not consider the environmental effects the material will experience such as corrosion and radiation damage. Examining radiation effects requires a significant amount of space in US facilities at the Advanced Test Reactor and the High Flux Isotope Reactor (HFIR) and suffers from natural gradients in temperature and neutron flux profiles. Ion irradiation may enable rapid assessment of radiation-induced damage to a material and is proposed as part of an accelerated materials qualification framework through the Advanced Materials and Manufacturing Technologies program. To enhance the utility of ion irradiation as an examination tool, this report provides the initial assessment of engineering-relevant properties of microstructures produced from ion irradiation in the near-surface volume. Nanoindentation, Vickers hardness, and known tensile properties were brought together with simple mathematical models and experimental data for an initial equivalence study of the mechanical performance of irradiated laser powder bed fusion (LPBF) 316 stainless steels across length scales. Direct observation of the calculated ion irradiation yield stress and measured neutron irradiation yield stress at 2 dpa showed that both datasets exhibit the same trend with irradiation temperature and overlap within an acceptable band of stress values. Ion irradiations at 10 dpa serve as a prediction of properties to compare to postirradiation examination of HFIR-irradiated LPBF 316H further in the program. This work is a significant demonstration of the Licensing Approach with Ions and Neutrons, which uses ion irradiations to generate mechanical property information more rapidly than through neutron irradiations.