Search Results (1,562)

This study aims to develop eco-efficient ceramic tiles through the valorization of recycled glass (GW; soda–lime glass cullet) as a partial raw material substituent, enabling a reduction in sintering temperature and, consequently, a decrease in thermal energy demand, carbon-equivalent emissions, and the depletion of virgin mineral resources. Ceramic tiles were elaborated by partially substituting natural bentonite with 30–50 wt.% GW and fired at 900 °C and 950 °C. Use of GW promoted liquid-phase sintering, driving significant densification evidenced by a marked reduction in open porosity and water absorption. SEM images confirm a denser, more homogeneous structure with reduced porosity, leading to improved mechanical strength and chemical durability. Compositions containing 30–35 wt.% bentonite exhibit the most optimized microstructure, characterized by well-dispersed crystalline phases embedded within a dense vitreous matrix. These findings demonstrate that high-performance ceramic tiles meeting standard classification thresholds can be manufactured at sub-1000 °C firing temperatures through judicious incorporation of recycled glass waste. This approach offers a viable pathway toward reduced energy consumption, diminished reliance on primary mineral resources, and enhanced circularity within the construction ceramics industry. Full article

Renewable energy technologies have historically been offered market support to facilitate their deployment and aid the transition away from fossil fuels. This work shows the costs of subsidising utility-scale renewable electricity generation in the UK, focusing on wind, solar and tidal stream technologies in the Renewables Obligation (RO) and Contracts for Difference (CfD) schemes. The subsidy of each technology is calculated using published data, including an estimate of committed costs over the full project lifetime, which is not always assessed. For the technologies considered, the RO supported 24.8 GW of installed capacity at a lifetime cost of about £103 bn. To date, CfD have been awarded for 45.3 GW of wind, solar and tidal stream, with total lifetime cost of £40 bn, although this is sensitive to future gas generation costs, with a range of £8–71 bn. The CfD scheme offers better value for money to consumers than the previous RO schemes, and this is true for all technologies assessed. By design, the CfD also helps to insulate billpayers from spikes in the wholesale market caused by high fossil fuel prices, decoupling the costs of electricity from gas. Credible scenarios for future deployment out to 2050 are also presented, along with discussion of potential socioeconomic benefits and the mechanisms to achieve these. Full article

Background: Renal ischemia–reperfusion injury (RIRI) is a major cause of acute kidney injury (AKI) and contributes to delayed graft function and progression toward chronic kidney disease. In addition to oxidative stress and inflammation, RIRI induces profound metabolic derangements, particularly suppression of tubular fatty-acid β-oxidation (FAO), leading to energetic stress, lipid accumulation, and maladaptive repair. Peroxisome proliferator–activated receptor-α (PPARα) is a key regulator of tubular FAO, but whether Schisandrin B (Sch B) mitigates RIRI through restoration of a PPARα-associated metabolic program remains unclear. Objective: To determine whether Sch B alleviates RIRI in association with restoration of tubular FAO and attenuation of lipid accumulation and fibrotic remodeling. Methods: A unilateral murine renal I/R model and an HK-2 hypoxia/reoxygenation (H/R) model were used. Mice received Sch B (20 or 40 mg/kg/day) before I/R, and a subset was co-treated with the PPARα antagonist GW6471. Renal function, tubular injury, fibrosis, lipid accumulation, and FAO-related proteins were assessed by serum biochemistry, histopathology, Oil Red O staining, transmission electron microscopy, immunohistochemistry, immunofluorescence, and Western blotting. Bulk RNA-seq and public single-cell RNA-seq datasets were integrated to characterize metabolic pathway remodeling and cell-type-associated PPARα changes. Molecular docking and molecular dynamics simulations were performed to explore the potential interaction between Sch B and PPARα. Results: Sch B significantly improved renal function, reduced tubular injury, and attenuated interstitial collagen deposition after I/R. Sch B also reduced lipid droplet accumulation, preserved mitochondrial ultrastructure, and restored the expression of FAO-related proteins, including CPT1A, CPT2, and ACADM. In vivo and in vitro, Sch B decreased α-SMA, COL1A1, and vimentin expression, indicating attenuation of EMT-associated/profibrotic remodeling. Integrated transcriptomic analyses supported marked metabolic reprogramming after I/R, with enrichment of FAO- and PPAR-related pathways and reduced PPARα expression predominantly in tubular compartments. Sch B was associated with restoration of tubular PPARα expression, while docking and molecular dynamics analyses supported a plausible Sch B–PPARα interaction in silico. GW6471 blunted the beneficial effects of Sch B on fibrosis-related and FAO-related readouts. Conclusions: Sch B alleviates RIRI and limits subsequent fibrotic remodeling in association with restoration of a PPARα-related tubular FAO program, reduced lipid accumulation, and preservation of tubular metabolic homeostasis. These findings identify metabolic reprogramming as an important component of Sch B-mediated renoprotection, although the precise mode by which Sch B regulates PPARα requires further investigation. Full article

This paper presents the design, structural optimization, and two-dimensional (2D) technology computer-aided design (TCAD) simulation of a gallium nitride (GaN) vertical Merged P-i-N/Schottky (MPS) diode incorporating a multi-drift-layer doping profile, composite SiO₂/Si₃N₄ passivation, and field-plate (FP) termination. The proposed device is constructed on an n⁺-GaN substrate with a three-sub-layer n-type drift region and a p-GaN/p⁺-GaN anode region. Systematic TCAD simulations are performed to investigate the dependences of key performance metrics—including knee voltage (V_knee), specific on-resistance (R_on), breakdown voltage (BV), reverse leakage current (J_leak), and Baliga’s figure of merit (BFOM)—on the Schottky metal work function, multi-drift-layer doping concentration, drift-layer thickness, Schottky-to-PN contact length ratio (γ_w), operating temperature, and reverse recovery switching transients. Results demonstrate that the MPS architecture effectively decouples forward conduction loss from reverse blocking capability, overcoming the conventional R_on–BV trade-off. The optimal doping profile (n_mm = 2 × 10¹⁵, n_m = 2 × 10¹⁵, n = 1 × 10¹⁶ cm⁻³) achieves a BFOM of ~31.97 GW·cm⁻² with BV ≈ 5.98 kV and R_on ≈ 1.12 mΩ·cm². Joint doping–thickness optimization further identifies a graded doping profile (n_mm = 2 × 10¹⁵, n_m = 5 × 10¹⁵, n = 1 × 10¹⁶ cm⁻³) combined with layer thicknesses (T_nmm, T_nm, T_n) = (4.49, 5, 20) μm as the overall optimum, achieving BFOM = 55.36 GW·cm⁻² (BV = 6.61 kV, R_on = 0.79 mΩ·cm²)—a +73% improvement, governed by the punch-through/field-stop design principle. The optimal contact ratio of γ_w = 1.33 yields a BFOM of 38.71 GW·cm⁻². Temperature analysis confirms a positive BV temperature coefficient due to drift-region-limited avalanche breakdown, and the BFOM improves monotonically from 33.31 to 37.82 GW·cm⁻² between 200 K and 450 K. Mixed-mode switching simulations show that increasing γ_w substantially reduces reverse recovery charge (Q_rr), demonstrating the strong potential of the proposed MPS diode for high-voltage, high-frequency, and high-temperature power electronic applications. Full article

To address the issues of high energy consumption, high carbon emissions, and the waste of associated energy (AE) in coal mine production, which severely hinder global sustainable development goals, this paper proposes a novel low-carbon economic collaborative optimal scheduling model for a coal mine integrated energy system (CMIES) oriented towards sustainable energy transitions. First, a refined utilization model for AE encompassing coal mine gas, ventilation air methane (VAM), and mine groundwater (GW) is constructed, and a tiered carbon emission trading mechanism (TCET) is introduced to constrain carbon emissions and promote ecological sustainability. Second, a concentrated solar power (CSP) plant is integrated to break the rigid “power determined by heat” constraint of a traditional combined heat and power (CHP) unit, thereby enhancing the system’s scheduling flexibility and renewable energy integration. Meanwhile, abandoned mines are retrofitted into solvent storage tanks to construct an integrated flexible carbon capture system (IFCCS), achieving sustainable reuse of mining wastelands. Finally, to tackle the multi-source, heterogeneous uncertainties on both the source and load sides, a hybrid risk assessment method combining information gap decision theory (IGDT) and conditional value at risk (CVaR) is proposed. Case study results demonstrate that, compared to traditional energy supply modes, the proposed model reduces carbon emissions and total costs in the mining area by 66.04% and 15.97%, respectively. This significantly improves resource utilization efficiency and ecological benefits, providing a highly viable pathway for the sustainable development and clean transition of coal mine operations. Furthermore, the proposed hybrid assessment method can effectively assist decision-makers in achieving a refined trade-off between operating costs and system robustness under varying risk preferences. Full article

This study investigates the relationship between renewable energy (RE) expansion and economic diversification in Egypt over 1990–2023 using a nonlinear autoregressive distributed lag (NARDL) framework. Egypt’s fossil fuel share stands at approximately 93% of primary energy supply, yet the country has committed to a 42% renewable electricity target by 2035. Despite quadrupling utility-scale RE capacity from 2.8 GW to 11.2 GW between 2015 and 2023, the Economic Diversification Index (EDI) has remained broadly stagnant. The bounds test confirms long-run cointegration (F = 6.760), exceeding small-sample critical values at the 1% level. Long-run estimates reveal that positive RE shocks are associated with lower diversification (θ⁺ = −0.571, p = 0.035) and negative shocks exhibit a statistically similar adverse effect (θ⁻ = −0.271, p = 0.024). Oil rents exhibit a positive long-run association (β = 0.145, p = 0.003). The error-correction term (−0.569) indicates approximately 57% annual adjustment. The Wald test provides marginal evidence against long-run symmetry (F = 2.999, p = 0.097). To complement the Granger causality analysis and address small-sample concerns, we additionally implement the Toda and Yamamoto augmented VAR procedure, which confirms robust unidirectional temporal precedence from LRE to LEDI (χ² = 23.48, p < 0.001) without reverse feedback (χ² = 2.25, p = 0.133). These patterns are interpreted through the lens of the Green Dependency Paradox—a conceptually distinct framework characterized by three mechanisms absent from classical resource curse theory: technology-mediated capital flight, procurement-induced deindustrialization, and policy-reversible lock-in operating under conditions of high import content, absent local content mandates, and fragmented industrial policy coordination. A tri-phase, evidence-grounded policy framework is proposed. All findings are explicitly conditional on Egypt’s current institutional context. Full article

The efficiency of converting ripe fruits into processed beans is an economically relevant component of Coffea canephora production systems, yet its genetic parameters remain poorly characterized in studies that do not partition the genotype × year (G×Y) interaction. This study estimated genetic parameters for five processing efficiency traits, namely grain proportion (% grain), husk proportion (% husk), fruit fresh mass per grain mass (FWM/GW), fruit fresh mass per bag (FWM/bag), and fruit volume per bag (FVol/bag), in 48 C. canephora genotypes (40 Robusta, 8 Conilon) evaluated over two crop years (2023–2024) in Jaguaré, Espírito Santo, Brazil. Bayesian inference via MCMC (brms) revealed that the genotype × year variance component exceeded the genotypic variance in 79–97% of posterior samples across the 48 genotypes evaluated over two crop years, a result that should be interpreted within the context of this restricted temporal window, with median heritabilities of 0.27–0.50 (95% credible intervals spanning up to 0.66 units, reflecting the uncertainty inherent to the two-year evaluation window) and genotypic correlations of 0.19–0.38 between years, indicating low consistency of genetic merit across crop seasons. Bayesian probability of consistent superiority identified Z21 as the genotype with the highest predictability for FWM/bag (prob. $=0.846$ at 20% selection intensity), while VR3 showed a favorable profile across four traits simultaneously. The multi-trait model with unstructured covariance estimated a negative genetic correlation between % grain and FWM/bag (${\widehat{r}}_g=-0.87$), suggesting potential for indirect selection. UPGMA clustering based on Mahalanobis distance (CCC $=0.813$) yielded six divergence groups that did not coincide with the botanical classification Conilon/Robusta. In this single-location, two-year study, temporal instability was the predominant source of uncertainty in the selection for processing efficiency in C. canephora under restricted evaluation windows. under restricted evaluation windows. Accordingly, the highlighted genotypes should be interpreted as priority candidates for validation in multi-environment, multi-year networks, rather than as definitive cultivar recommendations, given that the short evaluation window limits the generalizability of genotypic rankings. Full article

The global renewable energy sector now represents the world’s fastest-growing sector, with growth projected to more than double by 2030 and expected to exceed 4600 GW between 2025 and 2030. This is driven by falling costs, increasing consumer awareness, sustainable energy production models, and national and international climate commitments. This review study aims to discuss the transformation initiatives in the renewable energy sector with net-zero targets. A total of 89 studies published between 2020 and 2026 were identified for this literature review. The results indicate that digital transformation has the potential to significantly optimize the performance of the renewable energy sector by resolving its sustainability issues. This study discusses the waste types and waste management strategies in the renewable energy sector. It also highlights the indicators, barriers, and drivers of sustainable performance in the renewable energy sector by integrating advanced technological solutions in manufacturing, supply chain management, maintenance, monitoring, and the management of renewable energy equipment. The study findings demand global commitment and policy coordination in achieving the goals of decarbonization. The literature insights highlight future core research fields and can guide international organizations, industrial policymakers, and academic scholars towards a better and more sustainable future. Full article

Recovered graphite from spent lithium-ion batteries is an important secondary resource that can reduce reliance on primary graphite and lower the environmental footprint of battery production. In this work, graphite obtained as a carbon-rich residue after industrial hydrometallurgical leaching of NMC111 black mass (2 M H₂SO₄ + 3% H₂O₂) is subjected to three post-leaching washing treatments to assess how far simple, low-intensity steps can further clean the leach residue while preserving the carbon structure. The washing routes are water washing (GW), water washing with ultrasonication (GU) and mild sulfuric-acid washing with 0.1 M H₂SO₄ (GA). ICP-OES and SEM–EDX show that, relative to the leached black mass, all washing treatments reduce residual transition-metal contents by two to three orders of magnitude, and that the mild acid wash provides the lowest bulk metal levels, with several elements at or below detection limits. X-ray diffraction and Raman spectroscopy indicate graphite-dominated patterns and improved structural order, with the ID/IG ratio decreasing from 0.62 (GW) to 0.11 (GA) and the corresponding in-plane crystallite size increasing from 30.6 nm to 168 nm. Overall, the mild acid washing step is the most effective low-impact post-leaching purification route, yielding a thoroughly cleaned low-metal graphite fraction that preserves the graphite framework and constitutes a suitable intermediate for further upgrading or reuse in secondary applications. Full article

This perspective focuses on the field of solid waste recovery and resource utilization for end-of-life (EoL) wind turbine blades. Wind energy plays a central role in the global transition toward low-carbon energy systems owing to its technological maturity, scalability, and widespread resource availability. As global installed wind power capacity exceeded 1000 GW in 2024, improving the life-cycle energy efficiency and resource productivity of wind energy systems has become increasingly important. In this context, wind turbine blades (WTBs), the most material-intensive components with high embodied energy, are approaching large-scale end-of-life replacement, with global EoL blade waste projected to reach 2–4 million tons by 2030. Although blades may reach the end of their structural service life, they contain substantial quantities of reinforcing fibers and polymeric matrices that embody significant material and manufacturing energy. Integrating blade recycling into the wind energy value chain represents a critical opportunity to reduce dependence on energy-intensive virgin materials and lower life-cycle energy consumption and associated carbon emissions. However, the realization of energy-efficient circular utilization remains constrained by several challenges, including inefficient heat and mass transfer during blade depolymerization, limited valorization of resin-derived products, and performance degradation of recovered fibers. This perspective examines the material characteristics of blades from a life-cycle energy utilization standpoint, assesses existing recycling pathways, and identifies key technological and system-level bottlenecks. Emphasis is placed on process intensification, product upgrading, and design-for-circularity strategies to support the long-term sustainability of wind power systems. Full article

The Capacitated Quadratic Assignment Problem (CQAP) arises in logistics and network design, requiring the allocation of tasks to agents under quadratic interaction costs and capacity constraints. Classical exact solvers become computationally infeasible for large-scale instances, while heuristic methods such as Genetic Algorithms suffer from scalability limitations and sensitivity to local optima, leaving a gap for principled scalable approximations. In this paper, we address CQAP using the Gromov–Wasserstein (GW) framework, derived from Optimal Transport (OT) theory. In particular, we propose a multi-initialization GW strategy (GW_MultiInit) that mitigates the local optima problem inherent to non-convex GW optimization and scales efficiently to large problem sizes. Computational experiments on synthetic CQAP instances show that GW_MultiInit consistently achieves solutions close to the exact optimum for small- and medium-scale problems, and outperforms heuristic baselines such as the genetic algorithm at large scale in both runtime and solution quality across the benchmarks tested. To validate generalizability, we further evaluate GW_MultiInit On 17 QAPLIB benchmark instances adapted to the CQAP setting, GW_MultiInit achieves the best approximate result on 15 out of 17 instances with an average optimality gap of 0.34%, demonstrating strong generalizability beyond synthetic data. Additional comparisons with Entropic GW and Fused GW highlight practical trade-offs between accuracy, speed, and parameter sensitivity, offering guidelines for real-world deployment. Our results suggest that GW-based methods, and GW_MultiInit in particular, offer a promising and scalable approach for CQAP and related large-scale assignment problems within the problem scales examined. Full article

Quantifying changes in groundwater storage (GWS) remains a fundamental challenge in hydrology, given the sparsity of long-term in situ monitoring networks and the inherent difficulty of direct subsurface observation. Although GRACE and GRACE-FO satellite missions provide a means of tracking total terrestrial water storage at the continental scale, their coarse spatial resolution (~300 km) and monthly temporal sampling limit their direct applicability to regional groundwater studies. Here, we present a spatio-temporal disaggregation and data fusion framework for reconstructing daily GWS anomalies (GWSAs) across the Korean Peninsula, integrating GRACE/GRACE-FO Mascon solutions with the GLDAS Catchment Land Surface Model (CLSM). The approach leverages satellite-derived mass variations to constrain the model’s long-term anomaly structure while retaining the high-frequency temporal dynamics of land-surface modeling. The framework is evaluated against in situ bedrock monitoring well records from five sites: Seoul, Cheongyang, Uiseong, Imsil, and Wonju. Raw time-series correlations range from R = 0.14 to 0.70; upon removal of the monthly climatology to isolate non-seasonal variability, R improves to 0.49–0.72 across all sites, reaching 0.718 in Seoul and 0.707 in Cheongyang, with Cheongyang’s RMSE declining from 8.847 to 7.574 cm. These results indicate that the GRACE-CLSM fusion framework captures genuine sub-monthly groundwater dynamics beyond the dominant seasonal cycle. To our knowledge, this represents the first reconstruction of daily GWS changes for the Korean Peninsula with explicit preservation of spatial mass conservation, and the resulting dataset has direct utility for operational groundwater monitoring in a region subject to hydroclimatic variability. Full article

Communities across the Southwestern United States (US) and Northern Mexico are making critical decisions regarding how they create long-term water resilience, including by reducing water demand and diversifying water supplies in the face of scarcity. There are several emerging frameworks encouraging collaborative governance approaches to water scarcity, such as Collaborative Water Governance and Adaptive Water Governance; however, examples of ongoing implementation of these frameworks by local governments in academic literature are less prevalent. This paper addresses this gap in the literature by sharing case studies and practitioner recommendations resulting from Growing Water Smart (GWS)—a training and assistance program for local communities to conduct collaborative water resilience action planning across jurisdictional borders, as well as between the historically separated disciplines of water resources management and land use planning. This paper presents and assesses the GWS curriculum as a model for local, cooperative responses to water scarcity, grounded in Collaborative Water Governance, Adaptive Governance, and related frameworks. This paper utilizes primary GWS program documents, firsthand participant perspectives, and direct practitioner experiences to present three case studies of GWS communities working across disciplinary and jurisdictional borders: a regionally collaborative facilitation process and intergovernmental agreement regarding water exports in the San Luis Valley of Colorado; a regional GWS workshop and emerging county-wide convening of jurisdictions within the Verde Watershed of central Arizona; and binational collaboration across the US-Mexico border through a workshop between the cities of Douglas, Arizona and Agua Prieta, Sonora, resulting in a deepened understanding of shared effluent flows. Finally, this paper posits that the GWS model initiates more collaborative and informed decision-making, builds capacity for localities through the support of third-party conveners and facilitators, and maximizes the limited financial and human resources available to local jurisdictions—resulting in a valuable and replicable process to advance water resilience across disciplinary and jurisdictional borders. Full article

This paper concerns the production of a high-frequency stochastic gravitational wave background (SGWB) generated during the reheating epoch through gravitational decays of the inflaton field. Our analysis focuses on scenarios in which the inflaton predominantly decays into pairs of vector particles. Within this framework, we find that the resulting gravitational wave (GW) energy density spectrum exhibits a peak amplitude in the range of ${10}^{-8}$ to ${10}^{-6}$. The corresponding GW strain amplitude spans from ${10}^{-33.3}$ to ${10}^{-30}$ across the high-frequency band of ${10}^8$–${10}^{11}$ Hz. To assess detectability, we consider the electromagnetic (EM) detection scheme and derive the associated transverse perturbative photon flux (PPF) and the signal-to-noise ratio (SNR). Our results demonstrate that both the PPF and the SNR generated by this SGWB exceed those predicted for relic GWs from canonical single-field slow-roll inflation by approximately four to five orders of magnitude. This significant enhancement suggests that high-frequency stochastic gravitational waves (HFSGWs) produced during reheating provide a more promising target for experimental detection. Our findings highlight the potential of electromagnetic (EM) detection methods as viable probes of early-universe dynamics beyond the standard inflationary paradigm. Full article

Hope is an important emotion for fostering action regarding global warming (GW). This article’s experiment utilizes (a) a cognitive hope theory that combines agency and pathways-thinking and (b) prior (numerically driven inferencing) research on how estimating germane quantities, followed by surprising numeric feedback, impacts one’s beliefs and decision-making. We designed and assessed a short intervention that focally had 226 Americans estimate quantities regarding the impact/uptake of three GW solutions: sustainable (e.g., solar) electrification, energy efficiency (e.g., recycling), or reduced meat consumption. Changes in climate-change hope and GW beliefs represented the intervention’s effectiveness. (Nationalism, etc., were also assessed.) The intervention was generally successful—statistically significantly increasing participants’ (1) hope about humanity’s ability to tackle climate change and (2) GW acceptance/concern. Our results demonstrate climate-change hope’s close relationship with various constructs (particularly, acceptance of GW’s reality)—and that central facts can quickly modify such hope. We further replicated findings that core/surprising statistics can spawn environmental conceptual changes. Our results additionally support earlier-identified phenomena that people revise GW beliefs upon encountering salient, valid, surprising information. The findings (a) increase our laboratory’s (now 12) ways in which brief materials will boost GW acceptance/concern, and (b) imply that GW messaging should balance climate-dangers explications with hopeful solutions. Full article