Search Results (20,878)

The increasing demand for lithium-ion batteries (LIBs) raises concerns about the security of critical raw material supply and the management of hazardous waste. Efficient recycling can alleviate these issues by transforming spent batteries into high-value secondary materials for the circular economy. Industrial recycling has traditionally focused on the recovery of nickel (Ni) and cobalt (Co), whereas lithium (Li) recovery has often been sidelined due to technical complexities and fluctuating economic incentives. To meet the European Union (EU) Batteries Regulation target of 80% lithium recovery by the end of 2031, technically effective and economically viable lithium recovery strategies are required. This study investigates the use of food-grade sucrose as an organic reductant for the targeted recovery of lithium from NMC622 and NCA battery materials. The process combines sucrose-assisted reductive roasting with selective water leaching. The effects of roasting temperature, holding time, sucrose dosage, and heating rate were systematically evaluated and optimised. Under the best conditions of 600 °C, 15 min, 15 wt% sucrose, and a heating rate of 20 °C/min, lithium leaching efficiencies of 93.2% and 87.6% were achieved for separated NMC622 cathode material and NMC622-derived black mass, respectively. The method was also applicable to NCA-based black mass, reaching 83.7% lithium recovery under the same conditions. Mechanistic analysis revealed that lithium release was strongly controlled by the extent of transition metal reduction. Cobalt was fully reduced to its metallic state under all tested conditions. However, maximum lithium recovery required nickel to be reduced to metallic Ni and manganese-containing phases to be converted to MnO. The sucrose-assisted roasting process was rapid and holding times longer than 15 min decreased lithium recovery. This decrease was caused by the formation of poorly soluble lithium-containing phases, such as LiF and Li₃PO₄. F composition analysis showed the black mass (1.06 wt%) and anode fractions (2.26 wt%) to contain significantly more F than the cathode fraction (0.46 wt%), hence leading to the 5% Li leaching efficiency difference between cathode and black mass fractions under most conditions tested. Overall, these results demonstrate that sucrose-assisted reductive roasting, followed by selective water leaching, provides a rapid and effective route for high-efficiency lithium recovery from NMC- and NCA-based battery materials. Full article

The assessment of seismic performance of existing buildings has traditionally focused on structural safety and damage limitation, often neglecting the explicit quantification of the associated economic consequences. In recent years, performance-based earthquake engineering (PBEE) frameworks have enabled a direct link between structural response and probabilistic loss estimation, allowing economic metrics to be integrated into seismic risk evaluation. Among these, the Expected Annual Loss (EAL) represents a comprehensive indicator that accounts for seismic hazard, structural vulnerability, and exposure over the building’s lifetime. This study presents a performance-based seismic loss assessment of an existing reinforced concrete building, adopting EAL as a global metric for seismic performance evaluation. The case study concerns an existing hospital building designed primarily for gravity loads and representative of a large portion of the Italian building stock. A detailed nonlinear numerical model is developed using OpenSees ver. 3.8.0, incorporating shear-critical behavior through nonlinear link elements. Structural performance is evaluated through modal analysis, pushover analysis, and nonlinear time-history analyses using a set of ground motions selected and scaled according to intensity-based criteria. Seismic losses are estimated following the FEMA P-58 methodology, implemented through the PACT software ver. 3.1.2, integrating structural response demands, component fragility functions, collapse probability, and seismic hazard curves. Probabilistic loss curves are derived, and the EAL is computed as a synthetic indicator of economic seismic performance. The results highlight the effectiveness of EAL in capturing the combined effects of seismic hazard and structural vulnerability, demonstrating its potential as a robust decision-support metric for seismic risk mitigation, retrofit prioritization, and insurance-related applications for existing buildings. Full article

To address the demand for lightweight commercial vehicle suspensions, this study investigates the replacement of traditional spring steel with E-glass fiber/epoxy composite materials. An equal-width, variable-thickness parabolic single-leaf spring was designed, with orthotropic mechanical properties obtained via ASTM standard tests. Finite element analysis (FEA) was combined with multi-objective optimization using a genetic algorithm, adjusting layup parameters to optimize stiffness, strength, and mass. Furthermore, to address the high failure risk at composite joints, a symmetric two-hole bolted end connection and a mid-span clamping structure were designed. The structural integrity was evaluated under vertical load, emergency braking, and steady-state cornering conditions using the Tsai–Wu tensor strength criterion. The optimization results demonstrate an 8.84% mass reduction for the composite spring main body compared to the initial design. The complete composite leaf spring assembly achieved approximately a 60.6% weight reduction relative to the original steel counterpart. The results indicate that the proposed design and optimization methodology effectively fulfills lightweighting objectives while satisfying all suspension performance and operational reliability requirements. Full article

English proficiency is vital for non-native speakers’ career development, yet classroom instruction alone cannot meet practical demands, making informal digital learning of English (IDLE) increasingly important. Artificial intelligence (AI), with conversational and multimodal functions, offers new opportunities for IDLE. However, existing research on AI-mediated IDLE has predominantly focused on language majors and often relied on a single methodological lens, neglecting STEM undergraduates and the complex network dynamics among motivational factors. However, research has largely focused on language majors, leaving STEM majors underexplored. Guided by the Hedonic-Motivation System Adoption Model (HMSAM), this study analyzed data from 413 Chinese STEM majors using partial least squares structural equation modeling (PLS-SEM, SmartPLS 4.0) and psychological network analysis (PNA, R 4.5.3). PLS-SEM results showed that enjoyment was the strongest direct predictor of AI-IDLE, followed by focused immersion, perceived usefulness, and curiosity. Control contributed indirectly via focused immersion, while boredom was non-significant. Perceived ease of use influenced AI-IDLE only through cognitive and emotional pathways. The model explained 58.1% of the variance. PNA further identified enjoyment, focused immersion, and control as central nodes, while the link between perceived usefulness and AI-IDLE was non-significant. These findings suggest that Chinese STEM undergraduates’ AI-IDLE is primarily driven by intrinsic hedonic motivations rather than utilitarian evaluations. The study provides empirical support for designing AI tools that enhance enjoyment and control to foster STEM students’ extracurricular English engagement. Full article

The rapid reshoring of semiconductor manufacturing in the United States has introduced large-scale, energy-intensive industrial facilities into metropolitan regions increasingly exposed to climate-related infrastructure pressures. While existing research on industrial development often emphasizes agglomeration-driven economic spillovers, less attention has been given to how the early operational period of such facilities corresponds with surrounding commercial activity, particularly in peri-urban and greenfield suburban contexts. This study examines the spatiotemporal dynamics of localized commercial vitality surrounding semiconductor fabrication facilities in Phoenix, Arizona, and Austin, Texas. High-frequency point-of-interest (POI) mobility data are used to measure localized commercial activity, while regional electricity load records provide contextual information on metropolitan-scale demand conditions. Using a comparative Difference-in-Differences (DiD) framework combined with distance-band analysis and sectoral-temporal stratification, the study evaluates activity patterns between 2020 and 2025. The results indicate that the early operational period of the Phoenix facility is associated with a sustained relative divergence in mobility-derived commercial activity compared with the Austin benchmark trajectory. Spatial analysis identifies a clear distance-dependent gradient, with the largest relative reductions concentrated in intermediate suburban zones rather than immediately adjacent to the facility. Sectoral and temporal analyses further show larger reductions in dining and nighttime activity than in routine retail and daytime activity. Overall, the findings suggest that the early operational period of large industrial mega-projects may be associated with differentiated commercial activity trajectories across surrounding suburban environments. More broadly, the study demonstrates how high-frequency mobility data can be used to examine spatiotemporal variation in commercial vitality around major industrial developments. Full article

Road construction contributes to embodied carbon in infrastructure, with asphalt-bound layers often dominating construction-stage greenhouse gas emissions in flexible pavements. Reclaimed asphalt pavement (RAP) and high-modulus asphalt concrete can reduce virgin material demand and improve structural efficiency, but their sustainability benefit depends on maintaining equivalent pavement performance. This study develops a climate-informed, mechanistic, environmental, and economic Pareto optimization framework for RAP-modified high-performance asphalt concrete (RAP-HPAC) pavement sections in Alberta. The framework couples fitted dynamic modulus master curves, monthly pavement temperature inputs, ALVA layered elastic analysis, Asphalt Institute fatigue and rutting criteria, A1–A5 global warming potential (GWP), and Alberta 2026 installed unit-price cost data. The RAP-HPAC mixture contains 50% RAP and was designed through a balanced mix design to target approximately 80% effective RAP binder activation. Three traffic classes were evaluated: 731, 1300, and 5426 ESAL/day/direction, each with 2% annual compound growth over a 20-year design period. Relative to independently optimized conventional HMA controls, Pareto-selected RAP-HPAC sections reduced P50 construction-stage GWP by approximately 19–30% and first cost by approximately 6–11% at a conservative 0.90× RAP-HPAC cost multiplier. The results show that RAP-HPAC is most beneficial when used as a structural-bound base that replaces conventional asphalt-bound capacity while preserving sufficient granular support. The framework provides a reproducible design-stage approach for comparing recycled high-modulus asphalt mixtures using performance, carbon, and cost criteria simultaneously. Full article

Coagulation–flocculation is widely recognized as a fundamental step in wastewater treatment, as it promotes the aggregation and removal of suspended particles and organic contaminants following the addition of a coagulant. In this study, a bio-based coagulant was prepared from prickly pear (Opuntia ficus-indica) seed residues obtained after essential oil extraction. The extraction process for bioactive agents was successfully modeled using Central Composite Design (CCD)-based Response Surface Methodology (RSM). Optimal extraction was reached at pH 13, PPSM of 7.5 g, 0.75 M NaCl, and 40 min of stirring, providing maximum yields of 69.63 g proteins, 217.075 g total sugars, and 81.416 g polyphenols. The optimized extract was subsequently used as a bio-coagulant for the treatment of wastewater collected from the Chalghoum El Aid–Oued El Athmania wastewater treatment plant (Mila, Algeria). The effects of three operating parameters, initial turbidity, solution pH, and bio-coagulant dosage, on the coagulation–flocculation performance were investigated using a Box–Behnken design (BBD). Process efficiency was evaluated in terms of turbidity, chemical oxygen demand (COD), and organic matter (OM) removal. The raw wastewater exhibited initial values of 200 NTU for turbidity, 640 mg/L for COD, and 25 for organic matter. Statistical analysis revealed that the developed quadratic models were highly significant (p ≤ 0.05) and showed excellent predictive performance, with coefficients of determination (R² ≥ 0.97). Optimal treatment conditions were identified at pH 7, a bio-coagulant dosage of 1 mL/L, and an initial turbidity of 200 NTU. Under these conditions, removal efficiencies exceeded 98% for turbidity and COD and reached 88.08% for organic matter. Furthermore, Fourier-Transform Infrared (FTIR) Spectroscopy analysis confirmed the presence of functional groups responsible for the coagulation activity of the bio-coagulant. These findings highlight the potential of prickly pear seed residues as an effective, sustainable, and low-cost alternative to conventional chemical coagulants in wastewater treatment. Full article

Addressing critical bottlenecks in traditional hydrogen refueling station operations—specifically supply–demand imbalances and suboptimal scheduling—this paper presents a systematic review of the advancements and practical implementations of intelligent transportation platforms (ITPs). We explore how these platforms catalyze enhancing operational efficiency within the hydrogen ecosystem. This paper first outlines the technical foundations of Vehicle-to-Everything communication, edge computing, and multi-source data fusion, and provides an in-depth analysis of core challenges, such as demand uncertainty and resource scheduling complexity, as well as existing optimization algorithms. Through typical case studies, the significant value of such platforms in breaking down data silos, reducing equipment idle rates, and achieving end-to-end energy efficiency optimization is demonstrated. This study notes that current bottlenecks include fragmented standards, difficulties in implementing algorithms, commercial challenges, and the retrofitting of existing infrastructure. Moving forward, efforts should shift from isolated technological breakthroughs to ecosystem development. This includes improving demand forecasting accuracy in low-penetration regions, implementing lightweight retrofits to revitalize the existing market, establishing cross-domain data collaboration standards, building a trustworthy cross-platform settlement system, and exploring innovative pathways that integrate “hydrogen, carbon, and computing.” Full article

The significant CO₂ emissions from cement manufacturing and overuse of natural aggregates, especially river sand mining, have been a global environmental concern for decades. This is a review study that aimed to evaluate the solution by reviewing past studies on the incorporation of supplementary cementitious materials (SCMs) and recycled aggregates (RAs) to produce sustainable concrete (SC). Regarding environmental consequences, the results highlighted that the cement industry accounts for a 5–8% carbon footprint. Concurrently, the demand for high-quality river sand has escalated, leading to widespread river degradation, altered channel morphology, and effects on river ecosystems. Past studies’ experimental results indicate that silica fume (SF), as an effective SCM, enhances the strength and durability of sustainable concrete to its optimal levels. However, the higher RA content resulted in reductions in engineering properties. The published studies also reported that lower percentages of SF combined with RAs had a positive effect on the strength and durability of design mix concrete, thereby further strengthening the findings of this review. This factor was found to be missing in most studies. A cost–benefit analysis for combined SCMs and RAs was introduced in this study. This review study evaluated the cost–benefit analysis of 1 m³ of sustainable concrete. The highest benefit was observed at 20.97% in a study when optimized 10%SF + 100 RAs were combined. It showed that the combined use of SCMs with RAs at optimal levels satisfied the strength and durability requirements. In addition, the benefits of sustainable concrete were achieved without any cost increase, a new outcome revealed by this review. Full article

This study investigates the mechanical properties and corrosion behavior of a Co-free Fe₄₀Ni₃₀Cr₂₀V₈Mo₂ (at.%) multi-principal elements alloy (MPEA) designed for potential applications in aggressive environments. The alloy exhibits a balanced combination of strength and ductility, with a yield strength of approximately 258 MPa, an ultimate tensile strength of about 647 MPa, and a fracture elongation of around 52%, of which deformation is primarily governed by dislocation-mediated plasticity. In terms of corrosion performance, the alloy demonstrates excellent resistance in chloride-containing environments. Potentiodynamic polarization tests reveal a wide and stable passive region of approximately 1.28 V_SCE and a high pitting potential of about 0.975 V_SCE, indicating exceptional stability of the passive film. Electrochemical impedance spectroscopy (EIS) further confirms the high impedance and protective nature of the surface layer. X-ray photoelectron spectroscopy (XPS) analysis reveals that the superior anti-corrosion property is attributed to the formation of a passive film enriched with protective Cr₂O₃ and V, Mo oxides, which collectively construct an effective barrier against chloride-induced attack by reducing donor density. This work provides valuable insights for the development of alternative alloys to replace Co-containing systems in demanding corrosive applications. Full article

With increasing residential electricity demand, hybrid energy systems capable of simultaneously improving affordability, reliability, and environmental performance have become increasingly important. This paper develops an integrated techno-economic and environmental assessment framework for grid-connected residential energy systems under unreliable grid conditions and applies it to a real-world residential case study in Fayoum, Egypt. In the proposed framework, the utility grid is treated as the primary electricity source, while PV, diesel generation, and battery storage are evaluated as backup/support options. Six grid-connected hybrid configurations, namely Grid/Diesel, Grid/PV/Diesel, Grid/PV/Diesel/Battery, Grid/Diesel/Battery, Grid/PV/Battery, and Grid/Battery, were evaluated under identical load, solar resource, and economic conditions to identify the minimum net present cost (NPC)configuration capable of satisfying a specified service level, expressed in terms of the maximum allowable unmet load ratio. The optimization problem was formulated as a single-objective model that minimizes NPC, subject to technical constraints and a service level constraint represented by a zero unmet load requirement in this study. Additional indicators, including levelized cost of energy (LCOE), renewable fraction, CO₂ emissions, and electricity purchased from the grid, were used for comparative performance evaluation. The candidate systems were simulated and optimized under frequent grid outage conditions using HOMER Pro. The results identify the Grid/PV/Battery configuration as the preferred base case backup/support configuration among the evaluated alternatives, achieving the lowest NPC of USD 8949, the lowest LCOE of USD 0.135/kWh, the highest renewable fraction of 55.1%, and the lowest annual CO₂ emissions of 2333 kg/yr, while satisfying the zero unmet load requirement. Compared with the base Grid/Diesel system, the optimal configuration reduces annual operating cost from USD 1204/yr to USD 648.19/yr and lowers emissions by approximately 50%, despite requiring a higher initial capital investment. Sensitivity analysis shows that the preferred solution remains robust across most of the examined financing parameter space. The PV derating factor analysis further indicates that the Grid/PV/Battery configuration remains optimal at higher PV derating levels of 70–80%, whereas the preferred solution shifts toward Grid/Diesel at lower derating levels of 50–60%. Overall, the results demonstrate that combining service-level-constrained NPC minimization with comparative techno-economic and environmental evaluation provides a robust basis for identifying suitable backup-supported grid-connected residential energy solutions under unreliable grid conditions. Full article

The growing global demand for energy and rising greenhouse gas emissions require effective mitigation strategies, including carbon capture and storage (CCS) technologies. This study reviews 16 widely used simulation tools, including Aspen Plus, MATLAB, Fluent, and gPROMS, for steady-state and dynamic modeling of post-combustion, pre-combustion, and oxy-fuel combustion carbon capture processes. The tools are evaluated using five criteria: chemical process simulation capability, dynamic modeling functionality, thermodynamic property management, heat transfer accuracy, and tool integration features. The results reveal distinct strengths across platforms. Aspen Plus and Aspen Plus Dynamics perform strongly in chemical process simulation and thermodynamic property modeling, reflecting their robustness in reaction modeling and property estimation. gPROMS excels in dynamic modeling, demonstrating strong capability for time-dependent and transient process analysis. MATLAB achieves the highest score in tool integration, highlighting its flexibility in coupling with optimization solvers, control systems, and external programming environments. Fluent shows strong performance in heat transfer modeling, particularly for detailed thermal analysis in oxy-fuel combustion systems. Most existing studies focus on individual carbon capture technologies rather than simulation tool capabilities. Following the PRISMA 2020 guidelines, a systematic search of Scopus yielded 53 peer-reviewed papers on CCS simulation, which were analyzed to identify dominant tools and inform the AHP-based evaluation. This work addresses that gap by clarifying tool-specific advantages, supporting informed model selection to improve the efficiency and sustainability of CCS process design. Full article

As hybrid work arrangements become more established in organisations, the need for effective design and implementation strategies has grown significantly. Evidence indicates that employee wellbeing and engagement in hybrid work environments are declining and this presents a critical challenge for human resource management (HRM) professionals. This presents HRM professionals with a critical imperative of improving wellbeing, while maintaining engagement and productivity at work. This aligns closely with the United Nations’ 17 Sustainable Development Goals, particularly those that promote wellbeing and decent work. Through a systematic synthesis of 78 studies, this research investigates the key determinants of employee engagement and wellbeing in hybrid work contexts. The conceptual framework for this study is grounded in existing theoretical perspectives from the Job Demands–Resources model, Saks Frameworks and wellbeing perspective presented by Guest. The analysis identifies five critical factors that influence engagement and wellbeing outcomes in hybrid work, accompanied by evidence-based propositions for practice. These recommendations encompass: establishing well-equipped workspaces with appropriate flexibility in both location and time; developing organisational culture and leadership through enhanced communication and collaboration mechanisms; strategically allocating jobs and tasks whilst fostering effective networks and collaboration tools and implementing targeted training interventions to mitigate technostress and burnout associated with digital workloads. We advocate for future research to develop comprehensive models, frameworks and wellbeing interventions to guide HRM professionals in addressing these challenges at both the local and global levels. Full article

This discussion paper examines the evolution of freshwater distribution networks from smart to intelligent and ultimately meta-intelligent or wise systems, highlighting the transition from human-supervised operation to autonomous adaptive management. Smart systems integrate monitoring, automation and remote control through information technologies. Intelligent systems extend these capabilities by adding predictive analytics, demand forecasting and automated operational optimization. Wise systems further evolve through adaptive learning mechanisms that allow continuous self-improvement while minimizing dependence on operators. Evidence from Greek water utilities demonstrates practical applications and operational outcomes. The analysis discusses implementation challenges including investment costs, system complexity, data governance and resilience. Finally, the paper proposes design principles for scalable adaptive water networks applicable to utilities with different sizes, resources and levels of technological maturity. Full article

The growing demand for low-carbon cementitious materials has increased interest in natural zeolite as a supplementary cementitious material capable of reducing clinker consumption while modifying cement system performance. This study presents an integrated experimental evaluation of natural zeolite-modified cementitious materials by combining rheological behavior, hydration, compressive strength, density, scanning electron microscopy (SEM), and X-ray diffraction (XRD) within a single experimental framework. Natural zeolite was used as a partial replacement for cement at dosages of 5–12.5 wt.%. The results showed that zeolite significantly affected both fresh-state and hardened-state properties. Zeolite increased the rheological resistance of fresh mixtures, shifted the exothermic hydration peak from 12 h to 8–10 h, and reduced the maximum hydration temperature by approximately 8–12%. Among the investigated compositions, the mixture containing 7.5% zeolite exhibited the highest compressive strength (44.9 MPa at 28 days) together with increased hardened density, suggesting more efficient particle packing and matrix development than the reference mixture. SEM observations indicated a more uniform distribution of hydration products in mixtures containing moderate zeolite dosages, while XRD analysis confirmed changes in the crystalline phase assemblage associated with zeolite incorporation. The results demonstrate that moderate natural zeolite replacement, particularly at 7.5%, provides an effective balance between rheological behavior, hydration characteristics, mechanical performance, and microstructural development, highlighting its potential as a sustainable supplementary cementitious material for low-carbon cement-based composites. Full article