Search Results (3,639)

The continued performance scaling of AI gigafactories requires the development of energy-efficient devices to meet the rapidly growing global demand for AI services. Emerging materials offer promising opportunities to reduce energy consumption in such systems. In this work, we propose an electro-optic microring modulator that exploits a graphene (Gr) and transition-metal dichalcogenide (TMD) interface for phase modulation of data-bit signals. The interface is configured as a capacitor composed of a top Gr layer and a bottom WSe${}_2$ layer, separated by a dielectric Al${}_2$O${}_3$ film. This multilayer stack is integrated onto a silicon (Si) waveguide such that the microring is partially covered, with coverage ratios varying from 10% to 100%. In the design with the lowest power consumption, the device operates at 26.3 GHz and requires an energy of 5.8 fJ/bit under 10% Gr–TMD coverage while occupying an area of only 20 $\mathsf{\mu }$m${}^2$. Moreover, a modulation efficiency of $V_{\pi }L=$ 0.203 V$·$cm and an insertion loss of 6.7 dB are reported for the 10% coverage. The Gr-TMD-based microring modulator can be manufactured with standard fabrication techniques. This work introduces a compact microring modulator designed for dense system integration, supporting high-speed, energy-efficient data modulation and positioning it as a promising solution for sustainable AI gigafactories. Full article

Flat soda–lime–silicate glass is the dominant glass type used in contemporary buildings. This paper provides a comprehensive and integrated review of the scientific principles and technological processes that underpin its manufacture, processing, and structural performance. The discussion spans the glass transition and the nature of the glassy state; the network structure of soda–lime–silicate glass, with its inherent lack of long-range order; and its physical and mechanical properties, including fracture. The industrial production of flat soda–lime–silicate glass (melting, float-forming, and annealing) and its subsequent processing (thermal tempering, chemical strengthening, and coating) are described in detail, with emphasis on how they influence residual stresses, surface and edge quality, and structural reliability. Environmental considerations and ongoing advances in energy efficiency and decarbonisation are also examined. By linking the fundamentals of glass science to modern structural design standards, particularly the forthcoming Eurocode 10 for glass structures, the article seeks to equip structural engineers with an informed understanding of glass as a high-performance material for innovative and sustainable design. Full article

Urban rail transit networks in developing countries are rapidly expanding, entering a networked operational phase where accurate passenger flow forecasting is crucial for optimizing vehicle scheduling, resource allocation, and transportation efficiency. In the short term, accurate real-time forecasting enables the dynamic adjustment of train headways and crew deployment, reducing average passenger waiting times during peak hours and alleviating platform overcrowding; in the long term, reliable trend predictions support strategic planning, including capacity expansion, station retrofitting, and energy management. This paper proposes a novel hybrid forecasting model, EEMD-TiDE, that combines improved Ensemble Empirical Mode Decomposition (EEMD) with a Time Series Dense Encoder (TiDE) to enhance prediction accuracy. The EEMD algorithm effectively overcomes mode mixing issues in traditional EMD by incorporating white noise perturbations, decomposing raw passenger flow data into physically meaningful Intrinsic Mode Functions (IMFs). At the same time, the TiDE model, a linear encoder–decoder architecture, efficiently handles multi-scale features and covariates without the computational overhead of self-attention mechanisms. Experimental results using Xi’an Metro passenger flow data (2017–2019) demonstrate that EEMD-TiDE significantly outperforms baseline models. This study provides a robust solution for urban rail transit passenger flow forecasting, supporting sustainable urban development. Full article

The transition to low-carbon energy systems requires scalable and energy-efficient routes for producing liquid biofuels that are compatible with existing fuel infrastructures. This review focuses on bio-oil production from phototrophic microorganisms, highlighting their high biomass productivity, rapid growth, and inherent capacity for carbon dioxide fixation as key advantages over conventional biofuel feedstocks. Recent progress in thermochemical conversion technologies, particularly hydrothermal liquefaction (HTL) and fast pyrolysis, is critically assessed with respect to their suitability for wet and dry algal biomass, respectively. HTL enables direct processing of high-moisture biomass while avoiding energy-intensive drying, whereas fast pyrolysis offers high bio-oil yields from lipid-rich feedstocks. In parallel, catalytic upgrading strategies, including hydrodeoxygenation and related hydroprocessing routes, are discussed as essential steps for improving bio-oil stability, heating value, and fuel compatibility. Beyond conversion technologies, innovative biological and biotechnological strategies, such as strain optimization, stress induction, co-cultivation, and synthetic biology approaches, are examined for their role in tailoring biomass composition and enhancing bio-oil precursors. The integration of microalgal cultivation with wastewater utilization is briefly considered as a supporting strategy to reduce production costs and improve overall sustainability. Overall, this review emphasizes that the effective coupling of advanced thermochemical conversion with targeted biological optimization represents the most promising pathway for scalable bio-oil production from phototrophic microorganisms, positioning algal bio-oil as a viable contributor to future low-carbon energy systems. Full article

The transition toward a circular economy (CE) is progressively recognized as a strategic pathway to reconcile economic growth with environmental sustainability. Municipal solid waste management in Jordan remains mostly linear, with over 90% of the generated waste disposed of in landfills and open dumpsites. This study critically examines the prospects of adopting CE principles in Jordan’s waste sector by evaluating current practices, policy frameworks, and potential recycling pathways. A mixed-methods approach was adopted, combining quantitative modeling with qualitative insights from stakeholders and public surveys. Three recycling scenarios were assessed against the baseline scenario: 25%, 50%, and 75% waste recovery by 2034. The U.S. EPA WARM model was used to estimate greenhouse gas (GHG) emissions and energy savings. It was inferred that the net avoided emissions (against the baseline) for Scenarios 1, 2, and 3 are 14.5%, 29.0%, and 44%, respectively, with paper/cardboard contributing most to avoided emissions. Nonetheless, only Scenarios 2 and 3 were deemed environmentally sustainable, as their projected net GHG emissions for 2034 were lower than those recorded in the base year. Socio-economic analysis identified the major barriers as limited public awareness and participation, infrastructural gaps, and financial and institutional constraints. The analysis further reveals that despite the relatively high capital and operating costs associated with advancing toward CE in waste management, the long-term environmental and socio-economic gains are expected to outweigh the associated costs, particularly in terms of avoided GHG emissions and reduced landfill dependency. Full article

The article presents an extensive review of modern technological solutions for pulverized coal combustion, with emphasis on combustion modifiers and biomass co-firing. It highlights the role of coal in the national energy system and the need for its sustainable use in the context of energy transition. The pulverized coal combustion process is described, along with factors influencing its efficiency, and a classification of modifiers that improve combustion parameters. Both natural and synthetic modifiers are analyzed, including their mechanisms of action, application examples, and catalytic effects. Special attention is given to the synergy between transition metal compounds (Fe, Cu, Mn, Ce) and alkaline earth oxides (Ca, Mg), which enhances energy efficiency, flame stability, and reduces emissions of CO, SO₂, and NO_x. The article also examines biomass-coal co-firing as a technology supporting energy sector decarbonization. Co-firing reduces greenhouse gas emissions and increases the reactivity of fuel blends. The influence of biomass type, its share in the mixture, and processing methods on combustion parameters is discussed. Finally, the paper identifies directions for further technological development, including nanocomposite combustion modifiers and intelligent catalysts integrating sorption and redox functions. These innovations offer promising potential for improving energy efficiency and reducing the environmental impact of coal-fired power generation. Full article

This article examines public preferences for a proposed West Coast submarine high-voltage direct current (HVDC) transmission network in South Korea, installed by trenching and burying the cables in the seabed, which is essential for facilitating renewable energy integration and ensuring a stable electricity supply to the Seoul Metropolitan Area. The purpose of this study is to estimate South Korean households’ willingness to pay (WTP) for the proposed West Coast submarine HVDC network using contingent valuation (CV), thereby assessing its social acceptability amid renewable energy integration challenges. Employing a CV survey with a nationally representative sample of 1000 households conducted from late May to late June 2025, the research applies the one-and-one-half-bound spike model to address zero WTP responses and incorporates socio-demographic covariates to account for preference heterogeneity. The analysis estimates an average monthly WTP of KRW 1832 (USD 1.33) per household for the HVDC infrastructure. Results demonstrate statistically significant public support for the submarine HVDC project despite its high capital investment and potential electricity rate increases. These findings underscore notable consumer acceptance and provide valuable welfare insights for policymakers, reinforcing the prioritization of this project within South Korea’s energy transition framework. This paper contributes to the field of energy infrastructure valuation by advancing methodological approaches and offering policy-relevant recommendations for sustainable grid expansion. Full article

Tungsten is a critical metal for advanced industrial applications, yet its supply is challenged by the depletion of high-grade ores. This study presents a comprehensive optimization and mechanistic analysis of the alkaline fusion process for extracting tungsten from wolframite ((Fe,Mn)WO₄) using sodium carbonate (Na₂CO₃). Experimental investigations systematically evaluated the effects of alkali-to-ore ratio, reaction temperature (650–1000 °C), and reaction duration (30–270 min). Optimal conditions were established at a 2:1 Na₂CO₃-to-ore molar ratio, a reaction temperature of 750 °C, and a holding time of 30 min, achieving a tungsten extraction efficiency exceeding 99.9%. This represents a significant improvement in energy and process efficiency over conventional methods. A novel kinetic analysis reveals a two-stage reaction mechanism, transitioning from a slow, diffusion-controlled solid-state reaction (E_a = 243 kJ/mol) to a rapid, autocatalytic liquid-phase reaction (E_a = 212 kJ/mol) upon the formation of a Na₂WO₄–Na₂CO₃ eutectic above approximately 590 °C. The optimal temperature of 750 °C is rationalized as the point that ensures operation within this kinetically favorable liquid-phase regime. Furthermore, a thermochemical analysis of ore impurities indicates that silicon, lead, sulfur, and calcium are effectively sequestered into the slag phase as stable silicates, insoluble lead compounds, and sulfates, highlighting an intrinsic purification benefit. X-ray fluorescence (XRF) and X-ray diffraction (XRD) analyses confirmed minimal residual tungsten in the processed slag. This streamlined process, supported by a robust mechanistic understanding, reduces alkaline consumption, shortens reaction times, and maintains high yields, offering a sustainable and efficient pathway for leveraging declining wolframite resources. Full article

In the context of the ongoing digital revolution in manufacturing and the simultaneous advancement toward dual carbon objectives, this study investigates the role of intelligent technological advancements, particularly industrial robotics, in improving firm-level energy efficiency. Utilizing panel data from Chinese listed companies spanning the period 2012–2023, the research assesses the relationship between exposure to industrial robots and corporate energy efficiency metrics. The empirical analysis demonstrates that greater exposure to industry-level robotization substantially boosts corporate energy performance, verifying that intelligent modernization and green transition can be mutually reinforcing. This positive effect is particularly pronounced among superstar firms, in more competitive industries, and for capital-intensive enterprises. Mechanism analysis reveals that, first, robotization processes generate a scale effect that effectively dilutes the fixed energy consumption per unit of product. Second, the diffusion of robots intensifies market competition, creating a competition effect that compels all firms within the industry to optimize costs and management with a focus on energy conservation. This study demonstrates that enhancing human capital within organizations significantly amplifies the beneficial impact of robotic integration on energy efficiency metrics. By providing empirical data from an emerging market context, this research not only elucidates the role of industrial robots but also offers policy-relevant insights for developed economies navigating the concurrent challenges of industrial modernization and environmental sustainability. Full article

Geothermal energy is a crucial component of climate adaptation and sustainability transitions, as it provides a dependable, low-carbon source of baseload power that can accelerate sustainable energy transitions and enhance climate resilience. Yet, in East Africa—one of the world’s most promising geothermal regions, with the East African Rift—a unique climate-energy opportunity zone—the harnessing of geothermal power remains slow and uneven. This study examines the contextual conditions that facilitate the successful and sustainable development of geothermal power in the region. Drawing on semi-structured interviews with 17 experienced professionals who have worked extensively on geothermal projects across East Africa, the analysis identifies how technical, institutional, managerial, and relational circumstances interact to shape outcomes. The findings indicate an interdependent configuration of success conditions, with structural, institutional, managerial, and meta-conditions jointly influencing project trajectories rather than operating in isolation. The most frequently emphasised enablers were resource confirmation and technical design, leadership and team competence, long-term stakeholder commitment, professional project management and control, and collaboration across institutions and communities. A co-occurrence analysis reinforces these insights by showing strong patterns of overlap between core domains—particularly between structural and managerial factors and between managerial and meta-conditions, highlighting the mediating role of managerial capability in translating contextual conditions into operational performance. Together, these interrelated circumstances form a system in which structural and institutional foundations create the enabling context, managerial capabilities operationalise this context under uncertainty, and meta-conditions sustain cooperation, learning, and adaptation over time. The study contributes to sustainability research by providing a context-sensitive interpretation of how project success conditions manifest in geothermal development under climate transition pressures, and it offers practical guidance for policymakers and partners working to advance SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action) in Africa. Full article

This paper presents a comprehensive analysis of different energy system configurations for Energy Communities (ECs) supplied by multiple renewable-based technologies, with a specific focus on solar solutions in the Mediterranean region. The authors have studied and then proposed the optimal aggregation of different end-user loads within possible energy system configurations (identifying the most adequate combination of prosumers, i.e., households, municipality offices, commercial activity, and others) in order to narrow the gap between peak/off-peak demand and renewable energy availability by also integrating energy storage technologies, and in order to pursue a sustainable energy transition in urban contexts proposing smart cities at low CO₂ emissions. The study demonstrates that increasing the complexity of the generation mix involves a tangible influence on self-sufficiency and self-consumption, as well as on the mitigation of CO₂ emissions. In fact, a more complex system configuration, including heat pumps and energy storage, allows for up to five months of 100% self-sufficiency and almost 100% self-consumption for the entire year. In terms of greenhouse gas emissions, relevant CO₂ reduction potential is possible, with up to 50% of CO₂ emission reduction, when heat pumps, solar cooling, and energy storage are installed. Full article

This paper uses a systematic approach to constructing a mathematical description of the technological process of aluminum production, aimed at addressing control challenges and improving energy sustainability through a comprehensive analysis of technological parameters. Using expert assessment and correlation–regression analysis methods, the most significant technological parameters were identified, and quantitative relationships among them were established. Based on available statistical data from the current supply subsystem, a regression model was constructed that describes the influence of subsystem parameters on the voltage drop across the straight section of the bus and confirms the key role of transition resistances in welded joints in energy loss formation. Using the obtained dependencies, a conceptual model of the electrolysis process and its mathematical representation describing interactions among the electrical, thermal, and physicochemical subsystems of the electrolyzer was developed. The developed model is applicable to the analysis and prediction of technological modes, the construction of digital twins, and the development of automated control systems. In future work, the model is planned to be experimentally verified using a laboratory aluminum electrolysis setup in order to refine model parameters and assess applicability under industrial electrolyzer conditions. Full article

Digital and green energy transitions are driving an unprecedented demand for Strategic and Critical Raw Materials (S-CRMs), necessitating the identification of alternative sources such as secondary raw materials from exploration and mining residues. This study investigates an integrated, multi-scale approach to map and recover S-CRMs from an abandoned exploration stockpile in Zlatá Baňa, Slovak Republic. A key aspect of the methodology is comprehensive chemical and mineralogical characterization (XRF, PXRD, FTIR, LIBS, and SEM-EDS), which provided scientific validation for the diagnostic absorption features observed in laboratory reflectance spectra. These laboratory-acquired signatures were then used as endmembers to classify Sentinel-2 imagery via the Spectral Angle Mapper (SAM) algorithm. This integration enabled the identification of three distinct residue classes, with classA (jarosite-rich residues) emerging as the most reactive facies. Subsequent bioleaching experiments using Acidithiobacillus ferrooxidans demonstrated that microbial activity more than doubled Zn mobilization compared to abiotic controls. This cross-disciplinary strategy confirms that the synergy between advanced analytical characterization and remote sensing provides a robust, cost-effective pathway for the sustainable recovery of S-CRMs in regions affected by historical and mining activities. Full article

In the context of the “Dual Carbon” goals, achieving synergistic development between digitalization and green transformation in the coal power industry is essential for ensuring a just and sustainable energy transition. The core scientific problem addressed is the lack of a robust quantitative tool to evaluate the comprehensive performance of diverse transition scenarios in a complex environment characterized by multi-objective trade-offs and high uncertainty. This study establishes a sustainability-oriented four-dimensional performance evaluation system encompassing 22 indicators, covering Synergistic Economic Performance, Green-Digital Strategy, Synergistic Governance, and Technology Performance. Based on this framework, a Fuzzy DEMATEL–MultiMOORA–Borda integrated decision model is proposed to evaluate seven transition scenarios. The computational framework utilizes the Interval Type-2 Fuzzy DEMATEL (IT2FS-DEMATEL) method for robust causal analysis and weight determination, addressing the inherent subjectivity and vagueness in expert judgments. The model integrates MultiMOORA with Borda Count aggregation for enhanced ranking stability. All model calculations were implemented using Matlab R2022a. Results reveal that Carbon Price and Digital Hedging Capability (C13) and Digital-Driven Operational Efficiency (C43) are the primary drivers of synergistic performance. Among the scenarios, P3 (Digital Twin Empowerment and New Energy Co-integration) achieves the best overall performance (score: 0.5641), representing the most viable pathway for balancing industrial efficiency and environmental stewardship. Robustness tests demonstrate that the proposed model significantly outperforms conventional approaches such as Fuzzy AHP (Analytic Hierarchy Process) and TOPSIS under weight perturbations. Sensitivity analysis further identifies Financial Return (C44) and Green Transformation Marginal Economy (C11) as critical factors for long-term policy effectiveness. This study provides a data-driven framework and a robust decision-support tool for advancing the coal power industry’s low-carbon, intelligent, and resilient transition in alignment with global sustainability targets. Full article

Graphene oxide (GO) and reduced graphene oxide (rGO) have solidified their role as cornerstone nanomaterials in the pursuit of sustainable technology. This review synthesizes recent advances in harnessing the unique properties of GO and rGO such as their tunable surface chemistry and exceptional electrical conductivity for applications spanning environmental remediation and energy storage. In the environmental domain, they function as superior adsorbents and catalysts for the removal of hazardous pollutants. Concurrently, in the energy sector, their integration into supercapacitors and battery electrodes significantly enhances energy and power density. The adaptability of these materials also facilitates the creation of highly sensitive sensors and biosensors. However, the transition from laboratory research to widespread industrial application is hindered by challenges in scalable production, environmental health and safety concerns, and long-term stability. This review enhances the understanding of GO and rGO’s diverse applications and paves the way for future sustainable technologies in energy and environmental sectors. Full article