Search Results (628)

As states within the United States respond to future grid development goals, there is a growing demand for reliable and resilient nighttime generation that can be addressed by low-cost, long-duration energy storage solutions. This report studies the potential of including concentrating solar power (CSP) in the technology mix to support California’s goals as defined in Senate Bill 100. A joint agency report study that determined potential pathways to achieve the renewable portfolio standard set by the bill did not include CSP, and our work provides information that could be used as a follow-up. This study uses a capacity expansion model configured to have nodal spatial fidelity in California and balancing-area fidelity in the Western Interconnection outside of California. The authors discovered that by applying current technology cost projections CSP fulfills nearly 15% of the annual load while representing just 6% of total installed capacity in 2045, replacing approximately 30 GWe of wind, solar PV, and standalone batteries compared to a scenario without CSP included. The deployment of CSP in the results is sensitive to the technology’s cost, which highlights the importance of meeting cost targets in 2030 and beyond to enable the technology’s potential contribution to California’s carbon reduction goals. Full article

Microbial electrosynthesis (MES) has emerged as a promising bio-electrochemical technology for sustainable CO₂ conversion into valuable organic compounds since it uses living electroactive microbes to directly convert CO₂ into value-added products. This review synthesizes advancements in MES from 2010 to 2025, focusing on the electrode materials, microbial communities, reactor engineering, performance trends, techno-economic evaluations, and future challenges, especially on the results reported between 2020 and 2025, thus highlighting that MES technology is now a technology to be reckoned with in the spectrum of biofuel technology production. While the current productivity and scalability of microbial electrochemical systems (MESs) remain limited compared to conventional CO₂ conversion technologies, MES offers distinct advantages, including process simplicity, as it operates under ambient conditions without the need for high pressures or temperatures; modularity, allowing reactors to be stacked or scaled incrementally to match varying throughput requirements; and seamless integration with circular economy strategies, enabling the direct valorization of waste streams, wastewater, or renewable electricity into valuable multi-carbon products. These features position MES as a promising platform for sustainable and adaptable CO₂ utilization, particularly in decentralized or resource-constrained settings. Recent innovations in electrode materials, such as conductive polymers and metal–organic frameworks, have enhanced electron transfer efficiency and microbial attachment, leading to improved MES performance. The development of diverse microbial consortia has expanded the range of products achievable through MES, with studies highlighting the importance of microbial interactions and metabolic pathways in product formation. Advancements in reactor design, including continuous-flow systems and membrane-less configurations, have addressed scalability issues, enhancing mass transfer and system stability. Performance metrics, such as the current densities and product yields, have improved due to exceptionally high product selectivity and surface-area-normalized production compared to abiotic systems, demonstrating the potential of MES for industrial applications. Techno-economic analyses indicate that while MES offers promising economic prospects, challenges related to cost-effective electrode materials and system integration remain. Future research should focus on optimizing microbial communities, developing advanced electrode materials, and designing scalable reactors to overcome the existing limitations. Addressing these challenges will be crucial for the commercialization of MES as a viable technology for sustainable chemical production. Microbial electrosynthesis (MES) offers a novel route to biofuels by directly converting CO₂ and renewable electricity into energy carriers, bypassing the costly biomass feedstocks required in conventional pathways. With advances in electrode materials, reactor engineering, and microbial performance, MES could achieve cost-competitive, carbon-neutral fuels, positioning it as a critical complement to future biofuel technologies. Full article

Absolute linear encoders have emerged as a core technical enabler in the fields of high-end manufacturing and precision displacement measurement, owing to their inherent advantages such as the elimination of the need for homing operations and the retention of position data even upon power failure. However, there remains a notable scarcity of comprehensive review materials that can provide systematic guidance for practitioners engaged in the field of absolute linear encoder measurement technology. The present study aims to address this gap by offering a practical reference to professionals in this domain. In this research, we first systematically delineate the three fundamental categories of measurement principles underlying absolute linear encoders. Subsequently, we analyze the evolutionary trajectory of coding technologies, encompassing the design logics and application characteristics of quasi-absolute coding (including non-embedded and embedded variants) as well as absolute coding (covering multi-track and single-track configurations). Furthermore, we summarize the primary error sources that influence measurement accuracy and explore the operational mechanisms of various types of errors. This study clarifies the key technical pathways and existing challenges associated with absolute linear encoders, thereby providing practitioners in relevant fields with a decision-making guide for technology selection and insights into future development directions. Moving forward, efforts should focus on achieving breakthroughs in critical technologies such as high fault-tolerant coding design, integrated manufacturing, and error compensation, so as to advance the development of absolute linear encoders toward higher precision, miniaturization, cost reduction, and enhanced reliability. Full article

The growing volume of decommissioned wind turbine blades (WTBs) poses substantial challenges for end-of-life (EoL) material management, particularly within the composite repurposing and recycling strategies. This study investigates the repurposing of EoL WTB segments in a full-scale demonstrator for a photovoltaic (PV) floating platform. The design process is supported by a calibrated numerical model replicating the structure’s behaviour under representative operating conditions. The prototype reached Technology Readiness Level 6 (TRL 6) through laboratory-scale wave basin testing, under irregular wave conditions with heights up to 0.22 m. Structural assessment validates deformation limits and identifies critical zones using composite failure criteria. A comparison between two configurations underscores the importance of load continuity and effective load distribution. Additionally, a life cycle assessment (LCA) evaluates environmental impact of the repurposed solution. Results indicate that the demonstrator’s footprint is comparable to those of conventional PV-floating installations reported in the literature. Furthermore, overall sustainability can be significantly enhanced by reducing transport distances associated with repurposed components. The findings support the structural feasibility and environmental value of second-life applications for composite WTB segments, offering a circular and scalable pathway for their integration into aquatic infrastructures. Full article

Evaluating and enhancing system resilience is essential to strengthen the regional ability to external shocks and promote the synergistic development of environment, economy and society. Taking the Upper Yellow River (UYR) as an example, this paper constructed a resilience evaluation index system for the environment—economy—society (EES) composite system. A three-dimensional space vector model was built to calculate the resilience development index (RDI) of three subsystems and the composite system from 2009 to 2022. Pathways supporting high resilience levels of the composite system were examined using the fuzzy-set qualitative comparative analysis (fsQCA) method from a configuration perspective. The results revealed that (1) the RDI of three subsystems and the composite system in the UYR showed an increasing trend; relatively, the environment and economy subsystems were lower, and their RDI fluctuated between 0.01 and 0.06 for most cities. (2) The emergence of high resilience is not absolutely dominated by a single factor, but rather the interaction of multiple factors. To achieve high resilience levels, all the cities must prioritize both environmental protection and economic structure as core strategic pillars. The difference is that eastern cities need to further consider social development and life quality, while western cities need to consider social development, life quality, and social security. Other cities including Lanzhou, Baiyin, Tianshui, and Ordos should focus on social construction and social security. Exploring the interactive relationship between various influencing factors of the resilience of the composite system from a configuration perspective has to some extent promoted the transformation from a single contingency perspective to a holistic and multi-dimensional perspective. These findings provide policy recommendations for achieving sustainable development in the UYR and other ecologically fragile areas around the world. Full article

The Minimum Spanning Tree (MST) problem addresses the challenge of identifying optimal network pathways for critical infrastructure systems, including transportation grids, communication backbones, power distribution networks, and reliability optimization frameworks. However, inherent uncertainties stemming from disruptive events demand robust analytical models for effective decision-making. This research introduces an uncertainty-theoretic framework to assess MST stability in uncertain network environments through novel constructs: lower set tolerance (LST) and dual lower set tolerance (DLST). Both LST and DLST provide quantifiable measures characterizing the resilience of element sets relative to edge-weighted MST configurations. LST captures the maximum simultaneous risk variation preserving current MST optimality, while DLST identifies the minimal variation required to invalidate it. We evaluate MST robustness by integrating uncertain reliability measures and risk factors, with emphasis on computational methods for set tolerance determination. To overcome computational hurdles in set tolerance derivation, we establish bounds and exact formulations within an uncertainty programming paradigm, offering enhanced efficiency compared with conventional re-optimization techniques. Full article

The ethanol oxidation reaction (EOR) is a key process for direct ethanol fuel cells (DEFCs), offering a high-energy-density and carbon-neutral pathway for sustainable energy conversion. However, the practical implementation of DEFCs is significantly hindered by the EOR due to its sluggish kinetics, complex multi-electron transfer pathways, and severe catalyst poisoning by carbonaceous intermediates. This review provides a comprehensive and mechanistically grounded overview of recent advances in EOR electrocatalysts, with a particular emphasis on the structure–activity relationships of noble metals (Pt, Pd, Rh, Au) and non-noble metals. The effects of catalyst composition, surface structure, and electronic configuration on C–C bond cleavage efficiency, product selectivity (C1 vs. C2), and CO tolerance are critically evaluated. Special attention is given to the mechanistic distinctions among different metal systems, highlighting how these factors influence reaction pathways and catalytic behavior. Key performance-enhancing strategies—including alloying, nanostructuring, surface defect engineering, and support interactions—are systematically discussed, with mechanistic insights supported by in situ characterization and theoretical modeling. Finally, this review identifies major challenges and emerging opportunities, outlining rational design principles for next-generation EOR catalysts that integrate high activity, durability, and scalability for real-world DEFC applications. Full article

The integration of artificial intelligence (AI) in the manufacturing industry is increasingly prevalent, presenting both ongoing opportunities and challenges for organizations while also significantly impacting worker behavior and psychology. Drawing on data from 405 workers in China, this study employs hierarchical regression analysis and fuzzy-set qualitative comparative analysis (fsQCA) to investigate the influence mechanism of AI-enabled job characteristics on work-related flow. Key findings reveal that: AI-enabled job characteristics positively predict work-related flow by increasing perceived challenge stress, yet simultaneously exert a negative influence by exacerbating perceived hindrance stress; techno-efficacy significantly alleviates the relationship between AI-enabled job characteristics and perceived hindrance stress but does not moderate the path via perceived challenge stress; fsQCA identifies four distinct causal configurations of antecedents leading to high work-related flow. This research elucidates the complexities of AI-enabled job characteristics and their dual-faceted impact on work-related flow. By integrating AI into the study of worker psychology and behavior, it extends the contextual scope of job characteristics research. Furthermore, the application of fsQCA provides novel insights into the antecedent conditions and configurational pathways for achieving work-related flow, offering significant theoretical and practical implications. Full article

With accelerating digital transformation, firms must renew how they create, deliver, and capture value to remain competitive and to advance sustainable competitiveness. This study examines how ambidextrous market orientation drives digital business model innovation (DBMI) through the mediating role of digital resource bricolage and the moderating effect of environmental turbulence. Using survey data and structural equation modeling (SEM), we find that both proactive and responsive market orientations positively affect DBMI. Digital resource bricolage partially mediates both relationships, with a stronger mediation effect for responsive orientation. Environmental turbulence strengthens the association between ambidextrous market orientation and digital resource bricolage. Complementing variable-centric tests, fuzzy-set qualitative comparative analysis (fsQCA) identifies three configurational pathways sufficient for high DBMI, revealing alternative routes to business-model renewal under different contextual conditions. The findings extend ambidextrous market orientation research to digital contexts, enrich the resource-recombination perspective on DBMI, and provide actionable guidance for firms seeking to orchestrate data, platforms, and legacy assets to reconfigure activity systems. By clarifying when and how market sensing and shaping translate into effective digital recombination, this study informs strategies for sustainable competitiveness in turbulent environments. Full article

This work presents a theoretical investigation of ionic conductivity in cubic zirconia (c-ZrO₂) doped with magnesium, using density functional theory (DFT) with the hybrid B3LYP functional as implemented in the CRYSTAL23 software package. It was found that the spatial arrangement of magnesium atoms and oxygen vacancies significantly affects the energy barriers for oxygen ion migration. Configurations with magnesium located along and outside the migration path were analyzed. The results show that when Mg²⁺ is positioned along the migration trajectory and near an oxygen vacancy, stable defect complexes are formed with minimal migration barriers ranging from 0.96 to 1.32 eV. An increased number of Mg atoms can lead to a further reduction in the barrier, although in certain configurations the barriers increase up to 3.0–4.6 eV. When doping occurs outside the migration path, the energy profile remains symmetric and moderate (0.9–1.1 eV), indicating only a weak background influence. These findings highlight the critical role of coordinated distribution of Mg atoms and oxygen vacancies along the migration pathway in forming efficient ion-conducting channels. This insight offers potential for designing high-performance zirconia-based electrolytes for solid oxide fuel cells and sensor applications. Full article

Water and energy are strongly intertwined, especially in wastewater treatment plants (WWTPs) whose electrical loads can strain local grids. This work evaluates the technical, economic, and environmental feasibility of powering the WWTP attached to the smart building of Ibn Tofail University (Morocco) with building-integrated photovoltaics (PV) and a complementary wind turbine. Using the HOMER Pro optimizer, two configurations were compared: (i) stand-alone PV and (ii) a hybrid PV/wind system. The hybrid design raises the renewable energy fraction from 8.5% to 17.9%, cutting annual grid purchases by 8% and avoiding 47.9 t CO₂ yr⁻¹. The levelized cost of electricity decreases from 1.08 to 0.97 MAD kWh⁻¹ (≈0.11 to 0.10 USD kWh⁻¹), while the net present cost drops by 6%. Sensitivity analyses confirm robustness under grid electricity tariff and load-growth uncertainties. These results demonstrate that modest wind additions can double the renewable share and improve economics, offering a replicable pathway for WWTPs and smart buildings across the MENA region. Full article

Ethylene glycol oxidation (EGOR) transforms waste plastic-derived chemicals into high-value products, representing an upcycling strategy that enhances resource efficiency. Pt-based electrocatalysts have shown promise for oxidizing ethylene glycol (EG) to high-value glycolic acid (GA), but they still suffer from high Pt usage, limited activity and stability, and poor low-potential selectivity. In this work, we report a highly dispersed PtBiCoAgSn multi-component alloy (MCA) electrocatalyst (denoted as MCA-PtBiCoAgSn) with outstanding catalytic activity and deactivation resistance, demonstrating a remarkable EGOR mass activity of 16.65 A ${mg}_{Pt}^{-1}$ at 0.76 V vs. RHE, which is 8-fold higher than that of commercial Pt/C (2.03 A ${mg}_{Pt}^{-1}$). Also, it can maintain an EGOR current density of 4.89 A ${mg}_{Pt}^{-1}$ after an extended long-term stability test. Additionally, it shows superior Faradaic efficiency (FE) for C2 products compared to Pt/C across the potential window of 0.5~0.9 V vs. RHE, with the FE of GA being up to 91% at a very low potential of 0.5 V vs. RHE. Moreover, in situ electrochemical infrared spectroscopy in a thin-layer configuration confirmed that EGOR proceeds via the C2 pathway on MCA-PtBiCoAgSn surfaces. This work may provide new insights into the design of high-efficiency and low-cost EGOR catalysts. Full article

Through atomic-scale characterization of a single cobalt atom anchored in a pyridinic N₃ vacancy of graphene (Co-N₃-gra), this study computationally explores three interconnected functionalities mediated by cobalt’s electronic configuration. Quantum-confined molecular prototypes extend prior bulk models, achieving a competitive catalytic activity for CO oxidation via Langmuir–Hinshelwood pathways with a 0.85 eV barrier. These molecular prototypes’ discrete energy states facilitate single-electron transistor operation, enabling sensitive detection of NO, NO₂, SO₂, and CO₂ through adsorption-induced conductance modulation. When applied to lithium–sulfur batteries using periodic Co-N₃-gra, cobalt sites enhance polysulfide conversion kinetics and suppress the shuttle effect, with the Li₂S₂→Li₂S step identified as the rate-limiting process. Density functional simulations provide atomic-scale physicochemical characterization of Co-N₃-gra, revealing how defect engineering in 2D materials modulates electronic structures for multifunctional applications. Full article

This work introduces the Reverse Steam Rising Process (RSRP), a novel dissolution method, for the preparation of highly homogeneous organo-nickel composites. This approach enables gradual material dissolution, resulting in improved material integration. We investigate two distinct synthetic pathways: a direct organic material–nickel composite and a surfactant-assisted variation. Our findings demonstrate that the inclusion of a surfactant significantly improves the properties of the resulting organo-nickel composite. The RSRP method differs from traditional synthesis methods in that it utilizes reverse steam condensation to create a highly porous, multi-level structure. This unique structure significantly boosts the material’s electrocatalytic performance, particularly for the oxygen evolution reaction (OER). The Ni-MOF-CTAB catalyst exhibits an overpotential of 397 mV at 10 mA cm⁻² and a Tafel slope of 183 mV dec⁻¹, outperforming pristine Ni-MOF. The hierarchical design promotes superior ion and gas transport, while the distinctive organometallic configuration optimizes electronic interactions critical for OER activity. This innovative process enables precise control over both the micro- and nanoscale morphology of the nickel-based catalyst, ultimately leading to superior performance metrics. This advancement offers a new pathway for developing high-performance nickel organometallic materials for diverse electrocatalytic applications. Full article

Exploring the influencing factors and mechanisms of willingness to adopt GAI for collaborative decision-making in the generative artificial intelligence context is of significant importance for advancing the application of collaborative decision-making between human intelligence and generative AI. This study builds upon the traditional Technology Acceptance Model (TAM) and the Task–Technology Fit (TTF) models by introducing factors of human–GAI trust and collaborative efficacy to construct a theoretical model of the influencing factors of willingness to adopt GAI for collaborative decision-making. Empirical analysis is conducted using Structural Equation Modeling (SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA). The results show that perceived usefulness and collaborative efficacy emerge as key determinants of willingness to adopt GAI for collaborative decision-making. Attitude and human–GAI trust exert significant direct positive effects, while perceived ease of use and task–technology fit demonstrate significant indirect positive influences. The fsQCA results further identify three distinct configuration pathways: perceived value-driven, functional compensation-driven, trust in technology-driven. Full article