Search Results (15,341)

Understanding carbon dioxide (CO₂) emissions from buildings is critical for shaping effective policies toward sustainable urban development. Previous studies mainly applied bottom-up methods for small areas or top-down downscaling at national, provincial or grid scales. However, limited research has explored the relationship between building functions and CO₂ emissions at a larger scale. To bridge this gap, this study employed ridge regression to disaggregate monthly CO₂ emissions to the level of different functional buildings across England in 2022 and investigated the relationship between building functions and CO₂ emissions. Results show that commercial buildings rank highest in CO₂ intensity, reaching 1.49 kg per volume in February, while residential buildings rank lowest, reaching 0.25 kg per volume in July at the national scale, and industrial buildings have the largest total emissions. In addition, regional disparities in economic development and industrial structure contribute to emission differences among buildings of the same function. Temporally, all functional buildings exhibited lower emissions during summer compared to winter. Overall, this study offers a scalable and interpretable framework for understanding urban carbon emissions at high spatial and functional granularity. The findings may offer valuable insights to support government decision-making in urban planning and spatial policy design, thereby contributing to low-carbon development goals. Full article

Formic acid (FA) has emerged as a promising liquid hydrogen storage material, yet efficient photothermal dehydrogenation catalysts with high activity and H₂ selectivity remain challenging. Herein, a polymetallic synergistic PdCu/M-ZNC (where M represents the co-doped In, Sn and Mo species) is fabricated by molten-salt-assisted pyrolysis of ZIF-8 precursors followed by metal incorporation. The unique molten salt environment effectively preserves the porous architecture of ZIF-8, enabling the secure anchoring of PdCu alloy nanoparticles onto the carbonaceous matrix enriched with M-Nₓ coordination sites. Under light irradiation, the PdCu alloy sites kinetically accelerated the overall adsorption and activation of FA molecules. Based on empirical observations and corroborated by the established literature, this alloying effect was inferred to facilitate the C-H bond cleavage and HCOO* desorption processes. Concurrently, the M-Nₓ sites act as efficient electron transfer channels, facilitating the rapid coupling of photogenerated electrons with protons (H⁺) to evolve H₂. Consequently, the optimal catalyst exhibits an enhancement in gaseous product yield (404.46 mmol/g/h) and H₂ selectivity (67.49%) at 75 °C. This work offers a catalyst design that aligns with several principles of green chemistry: it maximizes the atom utilization of precious Pd, incorporates synergistic non-precious metals within MOF-derived frameworks to enhance stability, and leverages solar energy to drive hydrogen production under mild conditions, presenting a more sustainable pathway for hydrogen release from liquid carriers. Full article

Lightweight Unmanned Aerial Vehicles (UAVs) have limited space, low payload capacity, and constrained power supply capabilities. Therefore, their payloads are constrained by size, weight, and power (SWaP). Thus, designing edge-side signal processing architectures for the payloads of UAVs faces severe challenges. Traditional ASIC design based on manual optimization struggles to meet the demands of low latency and low resource occupancy in edge-side applications. To address this challenge, this paper proposes a signal processing hardware accelerator architecture design framework with algorithm-hardware co-design. The framework employs a cross-level dataflow graph representation to formally capture task characteristics. Reconfigurable dataflow templates and reusable operator IP components are systematically constructed based on this representation. Through multi-objective design space exploration, the framework achieves Pareto-optimal mapping from algorithmic specifications to hardware implementations. Finally, automatic generation of top-level hardware descriptions enables rapid FPGA-based prototyping and functional validation. Taking synthetic aperture radar (SAR) imaging as a study example, compared with non-reconfigurable architectures, this scheme reduces the equivalent gate count by 51.4% without increasing processing latency. Compared with a conventional reconfigurable dataflow architecture, the design improves energy efficiency from 12.8 MS/J to 16.0 MS/J, representing a 25.4% enhancement, while also scaling the supported data processing size by a factor of 4×. It provides a high-performance and scalable hardware acceleration solution for lightweight edge-side computing platforms. Full article

Silicon carbide (SiC) power devices are emerging as an alternative for electrical transportation systems to improve energy efficiency, reduce carbon emissions, increase power density, and enable long-term cost savings throughout the product life cycle. Thus, a fair comparison with state-of-the-art Silicon (Si) technology is required to justify the productization of SiC devices. This work performs a systematic investigation of both technologies at the device and system levels for distinct power module voltage classes (3.3 and 6.5 kV) and circuit topologies. Initially, experimental characterization of state-of-the-art power modules is performed, followed by energy efficiency characterizations at the power converter level. Then, an electrothermal simulation model was built and validated based on experimental results. Accurate system simulations of commercial two- and three-level traction topologies were developed, focusing on efficiency over the entire load range, loadability, potential energy savings under realistic train drive cycles, and a financial comparison of inverter prices per kW. SiC exhibits lower loadability degradation at high switching frequencies (>500 Hz) than Si technology. Energy-saving potentials of 40–70% in the traction inverter with a guaranteed return on investment during the converter’s lifetime are achieved by substituting Si with SiC inverters. In addition, massive energy savings of up to 200 MWh per inverter lifetime can effectively reduce the carbon footprint of railway systems (up to ~76 t CO₂-eq saved during the inverter lifetime). This paper provides essential information for distinct stakeholders to support the decision-making process and design considerations for future railway power conversion technologies. Full article

Tight oil reservoirs are characterized by poor petrophysical properties. After hydraulic fracturing, the low flowback rate of fracturing fluid readily leads to the formation of a water invasion zone in the near-wellbore region, which severely restricts the performance of Carbon dioxide (CO₂) huff-n-puff. To clarify the damage mechanism of the water invasion zone on CO₂ huff-n-puff in tight oil reservoirs and determine the key regulatory parameters, tight cores with a relative water invasion zone length Δδ = 0.3 were adopted as the research subject. Five groups of injection–soaking–production time combinations were designed, and single-factor analysis was implemented using the control variable method. Integrated with numerical simulation and nuclear magnetic resonance (NMR) testing, the influence of the water invasion zone, pore crude oil mobilization characteristics, and parameter regulation effects were systematically explored. The results demonstrate that the water invasion zone occupies effective pore throats to form a continuous water-phase barrier, hindering CO₂ seepage and mass transfer. After four huff-n-puff cycles, the cumulative recovery factor of the water-invaded model is 4.13 percentage points lower than that of the water-free model. After four huff-n-puff cycles, the cumulative recovery factor of the water-invaded model is 4.13 percentage points lower than that of the water-free model. The NMR T₂ spectra of cores with and without water invasion exhibit remarkable discrepancies: the water-free core presents a unimodal structure, while the water-invaded core features a distinctive bimodal structure, with obvious staged characteristics in crude oil mobilization. The recovery factor declines nonlinearly and sharply with the increase of Δδ, verifying that the water invasion zone length is the dominant controlling factor. The regulation effects of injection, soaking, and production time differ significantly: injection time serves as the pivotal parameter for enhancing oil recovery. Prolonging injection time can strengthen displacement intensity and dismantle the water-phase barrier, thereby elevating the recovery factor, whereas soaking time and production time have no significant improvement effect. The results can provide valuable references for the parameter optimization of CO₂ huff-n-puff in water-invaded tight oil reservoirs. Full article

This article analyses how capacity building programmes interact with structural constraints in mission-oriented climate policy, focusing on the Italian pilot Let’sGOv (GOverning the Transition through Pilot Actions) within the EU Mission “100 Climate-Neutral and Smart Cities by 2030”. Using an iterative, reflexive methodology (document analysis, direct observation, and qualitative analysis of questionnaires, workshop outputs, and online training feedback), it examines how municipal actors experience and reinterpret capacity building across three coupled dimensions: internal organisational capacity, external stakeholder relations, and multilevel governance interfaces. The empirical setting is a network of nine Italian Mission Cities (Bergamo, Bologna, Florence, Milan, Padua, Parma, Prato, Rome, Turin) supported by technical partners. The bench-learning pathway combined barrier diagnosis, an intensive in-person workshop, and a codesigned online curriculum structured around three thematic clusters (engagement, data, climate finance). Findings indicate that persistent barriers—departmental silos, resource and time scarcity, rigid human resources and procurement routines, asymmetric data access, and regulatory instability—are not removed by capacity building; rather, they are progressively articulated, specified, and reframed into actionable organisational and policy demands. Bench-learning strengthens diagnostic and relational capacities and enables modest institutional innovations (templates, protocols, internal task forces, shared policy briefs), while “hard” governance infrastructures largely remain unchanged. The paper argues that networked capacity building contributes to the emergence of nascent, project-dependent multilevel interfaces only when it supports collective negotiation with national actors and translates local experimentation into durable multilevel interfaces, mitigating risks of projectification and downward responsibility shifting. Full article

N₂O (Nitrous oxide) is a potent greenhouse gas with a global warming potential nearly 300 times that of CO₂ and poses a critical environmental challenge, particularly in semiconductor and display manufacturing, where it is emitted during plasma processes. However, catalytic N₂O abatement in O₂-rich environments remains inefficient because O₂ competitively occupies active sites and hinders the turnover of surface oxygen species. To clarify how support properties govern this inhibition, Co-based catalysts supported on beta zeolite, CeO₂, and TiO₂, together with unsupported Co₃O₄, were comparatively evaluated for direct N₂O decomposition. Among them, Co/Beta exhibited the highest performance, achieving >95% N₂O conversion at 450 °C in the presence of 5% O₂ with excellent long-term stability. Co/Beta possessed a high specific surface area (649 m² g⁻¹) and a mesoporous framework that favored uniform Co dispersion and reactant accessibility, while its high Co²⁺/(Co²⁺ + Co³⁺) ratio (75.5%) and large fraction of chemisorbed oxygen species (79.9%) promoted oxygen-vacancy formation and facile oxygen exchange. These results indicate that the ability of Co/Beta to maintain high activity in the presence of oxygen stems from support-modulated cobalt surface states and enhanced oxygen turnover behavior. These findings provide a support-design principle for stable N₂O decomposition under oxygen-containing exhaust conditions. Full article

This study presents a comprehensive bibliometric analysis of research on 2xxx series aluminum–copper (Al–Cu) alloys published between 2020 and 2025. A complete analysis of 4380 documents from 747 sources indexed in Scopus reveals sustained research growth, with publications rising from 603 in 2020 to 948 in 2025 at a compound annual growth rate of 9.5%. China dominates global output, contributing 35.7% of publications with Central South University as the leading institution (548 articles). However, China’s international collaboration rate (12.2%) remains notably lower than Western counterparts such as the United Kingdom (62.5%) and Canada (53.2%). Core journals including the Journal of Alloys and Compounds, Materials Science and Engineering: A, and Journal of Materials Research and Technology collectively account for 11.4% of total publications, conforming to Bradford’s Law concentration patterns. Keyword co-occurrence analysis revealed five distinct thematic clusters centered on microstructure–property relationships, friction stir welding and joining technologies, corrosion mechanisms, Al–Cu–Li aerospace alloys, and additive manufacturing. While life cycle modeling (K = 5993; tm = 2022.84) indicates the field is approaching maturity, by identifying emerging frontiers such as machine learning-assisted alloy design, sustainable processing routes, and multi-material joining for electric vehicles, this study offers researchers a quantitative roadmap of the Al–Cu alloy knowledge landscape and highlights strategic opportunities for future investigation. Full article

External stray magnetic fields from permanent magnet synchronous motors (PMSMs) may cause electromagnetic interference to nearby equipment and limit their application in space-constrained systems. To address this issue, this paper investigates the use of laminated Co-based amorphous ribbon shields for stray-field suppression. An efficient equivalent modeling method is proposed for the simulation of such multilayer thin shielding structures, in which the laminated shield is replaced by an equivalent single-layer model while preserving its macroscopic shielding behavior. The method is first assessed in 2-D through comparisons between refined laminated and simplified equivalent models under both linear permeability and nonlinear magnetization-curve descriptions, and is then extended to 3-D PMSM shielding analysis under static and rotating no-load conditions with experimental validation. Results show that the 10-layer amorphous ribbon shield, with a total thickness of 420 μm, achieves a maximum shielding effectiveness of 7.9 dB at a measurement distance of two motor radii. The maximum deviation between simulation and experiment is 7.4%, and the equivalent model reduces computation time by 28% relative to the refined model. This method provides an accurate and efficient approach for the analysis and design of compact low-frequency magnetic shields for PMSMs. Full article

This paper explores the emerging synergy between control theory and machine learning in robotics, focusing on methods that combine model-based strategies with data-driven adaptation. The authors highlight how classical techniques, such as model predictive control and adaptive control, are being enhanced by reinforcement learning, imitation learning, and neural models to address challenges in complex, uncertain environments. Emphasis is placed on real-world platforms (e.g., legged systems, aerial robots, and manipulators) with special attention to advanced domains such as multi-agent systems and coordination. The authors, in addition, establish a taxonomy to categorize these hybrid approaches as “learning-for-control”, “control-for-learning”, or “co-designed architectures”. This paper also reflects upon key open problems, including sim-to-real transfer, safety, and the need for verifiable learning-based controllers, all facets that help to outline a roadmap for future research. Full article

To overcome the inherent drawbacks of poly(propylene carbonate) (PPC), such as poor thermal stability, low mechanical strength, and high surface energy, this study introduced, for the first time, 1,1,1-trifluoro-2,3-epoxypropane (TF-PO) as a third monomer into the metal-free TEB/PPNCl catalytic system for the terpolymerization with carbon dioxide (CO₂) and propylene oxide (PO), successfully synthesizing a series of fluorinated PPC (PPCF). The optimal polymerization conditions ($60 °C$, 2.0 MPa, 12 h, n(PO):n(TF-PO) = 100:4) were determined through systematic optimization. Comprehensive structural characterization (FT-IR, NMR, XPS) confirmed the successful incorporation of TF-PO into the polymer backbone. Property evaluation revealed that the PPCF materials exhibited substantial improvements in thermal stability, mechanical strength, hydrophobicity, and dielectric properties compared to unmodified PPC. The optimal sample, PPCF4, achieved a $5\%$ weight-loss temperature ($T_{d,-5\%}$) of $242 °C$, a glass transition temperature ($T_{\mathrm{g}}$) of $42 °C$, a tensile strength of 21.5 MPa, and a Young modulus of 296 MPa. With a $5\%$ TF-PO feed ratio, the material’s water contact angle increased to 102°, and its dielectric constant reached 6.01 at ${10}^4$ Hz. Furthermore, density functional theory (DFT) calculations elucidated the Lewis acidity of the TEB catalyst and the reactive sites of the monomers, leading to a proposed mechanism for the ternary alternating copolymerization. This work provides an effective synthetic strategy and theoretical foundation for preparing high-performance and functionalized PPC materials through molecular structure design. Full article

Glioblastoma (GB) classical treatment with the alkylating drug temozolomide (TMZ) is not effective mainly due to chemoresistance mechanisms, particularly those mediated by O6-methylguanine-DNA methyltransferase (MGMT). In this context, polyethylene glycol (PEG)-coated poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) were developed to deliver tamoxifen (TAX), a clinically approved non-alkylating drug with reported anti-GB activity. The NP formulation was optimized using a factorial design and subsequently functionalized with lactoferrin (Lf) to enhance GB targeting. The Lf-conjugated optimized formulation exhibited a mean diameter of 193 ± 6 nm, a polydispersity index (PDI) of 0.11 ± 0.04, a zeta potential of −18.2 ± 6.8 mV, and an encapsulation efficiency (EE) of 68.6 ± 1.8%. The NPs exhibited a sustained release profile for up to 23 days, and remained stable under physiological conditions. Cell uptake studies, conducted in human GB cells (U87, U251, and T98G) and healthy astrocytes, demonstrated enhanced internalization of Lf-NPs in GB cells compared with non-conjugated NPs, suggesting uptake through Lf-binding site-mediated endocytosis. Cytotoxicity assays further indicated that Lf-conjugation improved the antiproliferative efficacy of TAX-loaded NPs relative to non-functionalized formulations, particularly in GB cells. Moreover, combination studies with TMZ showed that the developed NPs were able to sensitize GB cells to treatment with this alkylating agent. In sum, this work supports the potential of the developed Lf-decorated TAX-loaded PLGA NPs as a nanoplatform for targeted delivery against GB. Full article

Speed is a key determinant of crash risk and injury severity, particularly on urban and secondary roads with frequent interactions between vulnerable road users. Traffic calming measures (TCMs) encompass physical, regulatory, perceptual, and technological interventions and aim to reduce operating speeds and improve safety and liveability. This study systematically evaluates the effectiveness of TCMs in reducing speed and improving safety outcomes on urban roads, following PRISMA 2020 guidelines. It encompasses the identification, screening, and synthesis of articles from the Scopus, ScienceDirect, and SpringerLink databases, published between January 2020 and February 2026. Risk of bias in the included studies was assessed qualitatively by the co-authors. The assessment was conducted independently, with discrepancies resolved through discussion. A total of 91 studies were included in the review. Evidence from field studies, driving simulator experiments, and analytical, simulation, and computation-based evaluations is reviewed and structured within a three-cluster taxonomy comprising physical and geometrical measures, regulatory and perceptual interventions, and digital and technological approaches. The synthesis indicates that physically self-enforcing measures yield the most consistent reductions in speed. At the same time, regulatory and digital interventions can deliver meaningful safety benefits when implemented at scale with credible governance. Perceptual and advisory measures show more varying and context-dependent effects. The evidence base is limited by heterogeneity in study designs, short-term evaluations, and inconsistent reporting across studies. Full article

Over the past three decades, artificial intelligence (AI) has substantially reshaped marketing research and practice, yet the discipline has not established a systematic understanding of its evolutionary trajectory and intellectual structure. A bibliometric analysis of 1923 Scopus publications (1992–2025) was conducted using CiteSpace to explore collaboration patterns, conceptual development, and thematic organization. It identified six evolutionary stages with accelerating innovation cycles, starting with neural networks (1992–2000) and ending with generative AI (2024–2025), with research attention per stage compressing from approximately 9 years to just 2 years. The analysis of the collaboration network shows that the key contributors are India, China, the USA, and the UK. Co-citation analysis indicates that there are three thematic dimensions with seven clusters, namely: (i) AI technological foundations and capabilities, (ii) AI marketing applications and transformation, and (iii) responsible AI governance and ethics. It suggests a Three-Force Evolutionary Framework, which combines technology-push, market-pull, and governance-moderator forces to describe the dynamics of the field. This framework shows that the Regulatory Awakening of 2018 (e.g., GDPR and the Cambridge Analytica incident) guided, not limited, innovation, and highlighted the critical personalization–privacy paradox on which modern developments are based. It identifies three priority research directions: generative AI in creative marketing, consumer trust in the personalization–privacy paradox, and organizational adaptation to fast innovation cycles. This study provides scholars with a comprehensive knowledge map, practitioners with strategic imperatives for responsible AI adoption, and policymakers with evidence that well-designed regulation accelerates innovation by balancing commercial value with societal concerns. Full article

Increasing load demand and localized constraints are driving the need for cost-effective alternatives to traditional network reinforcement. However, existing Non-Wires Alternative (NWA) planning approaches often rely on simplified assumptions or computationally intensive full-year optimization, limiting their practical applicability. This study proposes a planning-oriented method integrating 8760-h Direct Load Flow (DLF)-based assessment, worst-case screening, and Mixed-Integer Linear Programming (MILP)-based resource sizing for the coordinated deployment of Energy Storage Systems (ESSs), Demand Response (DR), and Photovoltaic (PV) resources, along with building-scale microgrid candidates. The proposed microgrid candidates are modeled as grid-connected, building-scale configurations in which PV, ESSs, and DR are co-located at a single node, representing integrated resource units within the distribution system. The results show that voltage constraints are the dominant limiting factor and that NWAs primarily function as an investment deferral strategy rather than a full replacement for traditional reinforcement, delaying constraint violations by approximately 2 to 14 years. An ESS provides the most direct contribution to constraint mitigation, while DR and PV offer complementary support. The results also highlight the importance of locational deployment. In particular, a co-located microgrid configuration (MG_111) is selected as the optimal portfolio under moderate load growth conditions (Case B, 2%), demonstrating the practical feasibility of integrated DER deployment at a single node. Economic feasibility is found to be highly sensitive to incentive design, with profitability achieved only under favorable compensation conditions. These results demonstrate that coordinated DER portfolios can effectively extend deferral periods and provide practical insights into cost-effective NWA planning under realistic operating conditions. Full article