Search Results (38,113)

Metal nanoparticles are unique materials with diverse properties and a wide range of paramount applications in various scientific fields, from catalysis and electrochemistry to pharmaceuticals and high-tech composite materials. Among the many methods for producing nanoparticles, those that use renewable plant biomass or its extracts, as well as biogenic approaches for synthesizing nanoparticles within living cells, are particularly promising from the viewpoint of Green Chemistry and sustainable development. These techniques, which are part of the rapidly growing field of Nanobiotechnology, can help solve problems associated with the use of toxic or expensive chemicals and increase the sustainability and affordability of the production of nanoparticles and biohybrid materials based on them. This review explores various methods for creating nanoparticles from both precious and base metals, using a variety of reducing agents and enzymes found in plants and bacteria, as well as promising biochemical approaches involving the reduction of metal salts inside living cells. Full article

The persistent shortage of ICT specialists across the European Union has intensified the strategic relevance of digital human capital as a determinant of labour market resilience and structural competitiveness. This study provides a systematic assessment of how ICT human capital—proxied by ICT tertiary enrolments, graduate output, and specialist employment—shapes the employment prospects of recent tertiary graduates in the EU-27 between 2013 and 2023. Drawing on harmonised Eurostat panel data and fixed-effects estimations with robust corrections for cross-sectional dependence, the analysis disentangles both direct effects and context-specific moderations associated with economic development, urbanisation patterns, and renewable energy penetration. Results demonstrate that ICT enrolments exert a consistently positive influence on graduate employability, whereas the labour market impact of ICT graduates and specialists is heterogeneous, reflecting differentiated absorptive capacities and sectoral saturation dynamics across Member States. Interaction effects further reveal that the urban concentration attenuates marginal returns to ICT education, while the integration of digital and green transitions remains institutionally underdeveloped. Collectively, the findings position digital tertiary education as a core pillar of sustainable employment formation yet highlight the necessity of coordinated policy architectures that align higher education pathways with regional labour market structures and the evolving green-digital policy agenda in Europe. Full article

With the continuous increase in the proportion of renewable energy in the power grid, enhanced operational flexibility of the power system is required. As baseload generators, combined heat and power (CHP) units are prime candidates for flexibility retrofits that guarantee grid stability. Among the available options, molten-salt thermal energy storage (TES) offers an energetically efficient route to decouple heat and electricity production in CHP plants. In this study, a 660 MW ultra-supercritical coal-fired unit is taken as the object of investigation. Sixteen technical routes incorporating steam extraction and electric heating for thermal energy storage and discharging are systematically designed. Results demonstrate that all the combined schemes significantly improve the operational flexibility of the unit. Among them, the C1-S1 configuration exhibits the most outstanding overall economic performance, with a six-hour thermal storage capacity of 294.34 MWh. The system exergy destruction is measured at 6258 kW, while the round-trip efficiency and thermal efficiency are determined to be 81.11% and 45.48%, respectively. Full article

Many cities worldwide face decline due to mineral-resource exhaustion, with mining-induced subsidence and land degradation posing urgent land use challenges. At the same time, carbon neutrality has become a global agenda, promoting ecological restoration, emissions reduction, and green transformation in resource-exhausted cities. However, empirical evidence on how carbon neutrality strategies drive land use transition remains scarce. Taking Xuzhou, China, as a case study, we integrate the GeoSOS–FLUS land use simulation model with a Markov chain model to project land use patterns in 2030 under three scenarios: natural development (ND), land recovery (LR), and carbon neutrality (CN). Using emission factors and a land use carbon inventory, we quantify spatial distributions and temporal shifts in carbon emission and sequestration. Results show that LR’s rigid recovery policies restrict broader transitions, while the CN scenario effectively reshapes land use by enhancing the competitiveness of low-carbon types such as forests and new-energy land. Under CN, built-up land expansion is curbed, forests and new-energy land are maximized, and emissions fall by 4.95% from 2020. Carbon neutrality offers opportunities for industrial renewal and ecological restoration in resource-exhausted cities, steering transformations toward approaches that balance ecological function and carbon benefits. Long-term monitoring is required to evaluate policy sustainability and effectiveness. Full article

Amid escalating attacks on the diversity, equity, and inclusion, Historically Black Emerging Hispanic-Serving Institutions (HBeHSIs) represent overlooked spaces of resistance in U.S. Higher education. This study examines how faculty and administrators negotiate racial and professional identities within institutions shaped by Black liberatory traditions and exclusionary HSI policy. Guided by Bradley and Tillis’s Afro-Latinidades heuristic, we link psychosocial identity development to institutional praxis and anti-colonial resistance. Interviews with 10 BIPOC professionals reveal identity ork as collective praxis challenging essentialist narratives and affirming servingness beyond enrollment metrics. Five themes illustrate work as collective praxis challenging essentialist narratives and affirming servingness beyond enrollment metrics. Five themes illustrate strategies for sustaining equity-driven missions under racial retrenchment, calling for renewed commitments to justice-centered higher education. Full article

Enhancing system strength to ensure voltage security has become a critical challenge for power systems with high penetration of renewable energy (RE). As China accelerates its clean-energy transition, the conventional grid dominated by synchronous generators is evolving into a dual-high system characterized by both high shares of wind–solar generation and extensive power-electronic interfaces. This shift fundamentally alters the mechanisms of voltage support, rendering traditional short circuit ratio (SCR) index inadequate for describing grid strength. To address this gap, this study proposes a multi-renewable-station short circuit ratio (MRSCR) index that quantitatively evaluates the voltage support strength of RE-dominated systems, and further analyzes the mechanism by which multiple agents on the generation and grid sides affect MRSCR, enhancing the generality and applicability of the proposed index. The MRSCR is further formulated as a voltage security constraint and integrated into an energy storage planning model considering multi-agent collaborative optimization. The proposed model jointly optimizes the siting and capacity configuration of grid-forming energy storage under voltage security constraints. Case studies on the IEEE 14-bus system and a real provincial grid show that incorporating the MRSCR indicator effectively enhances the system’s voltage support performance and operational resilience, achieving these improvements with only a 5.45% increase in daily operating cost compared with baseline planning results. The framework provides a practical offline tool for energy storage planning, enabling both enhanced renewable integration and improved voltage security. Full article

Accurate modeling of proton exchange membrane fuel cells (PEMFCs) is essential for predicting system performance under diverse operating conditions. This study introduces a refined semi-empirical modeling that combines experimental validation with an enhanced parameter estimation method based on the Cloud Drift Optimization (CDO) algorithm. The approach focuses on identifying seven key parameters of the nonlinear PEMFC model by minimizing the difference between experimentally measured and simulated cell voltages. To assess its effectiveness, the proposed CDO-based estimator was compared with several established metaheuristic algorithms, including the particle swarm optimizer and the tetragonula carbonaria optimization algorithm. The evaluation was performed using three commercial PEMFC stacks rated at 250 W, 500 W, and the NedStack PS6, as well as experimental data obtained from the Renewable Energy Laboratory at A’Sharqiyah University. Results demonstrate that the CDO algorithm consistently produced the lowest sum of squared errors (SSE) of 1.0337 and exhibited stable convergence across multiple independent runs with a standard deviation of 1.2114 × 10⁻⁷. Its reliable performance under both normal and degraded conditions confirms the algorithm’s robustness and adaptability, establishing CDO as an efficient and dependable technique for PEMFC modeling and parameter identification. Full article

This paper proposes a novel fractional-order African vulture optimization algorithm (FO-AVOA) for solving the optimal reactive power dispatch (ORPD) problem. By integrating fractional calculus into the conventional AVOA framework, the proposed method enhances the exploration–exploitation balance, accelerates convergence, and improves solution robustness. The ORPD problem is formulated as a constrained optimization task with the objective of minimizing real power losses while satisfying generator voltage limits, transformer tap ratios, and reactive power compensator constraints. The general optimization capability of the FO-AVOA is verified using the CEC 2017, 2020, and 2022 benchmark functions. In addition, the method is applied to the IEEE 30-bus and IEEE 57-bus test systems. The results demonstrate significant power loss reductions of up to 15.888% and 24.39% for the IEEE 30-bus and IEEE 57-bus systems, respectively, compared with the conventional AVOA and other state-of-the-art optimization algorithms, along with strong robustness and stability across independent runs. These findings confirm the effectiveness of the FO-AVOA as a reliable optimization tool for modern power system applications. Full article

In this paper, an event-triggered optimal control strategy is proposed for three-phase grid-connected voltage source inverters (VSIs) based on the voltage-modulated direct power control (VM-DPC) principle. The optimization control problem of VSIs is addressed in the framework of nonzero sum (NZS) games to ensure mutual cooperation between active power and reactive power. To achieve optimal performance, the power components are driven to track their desired references while minimizing the individual performance index function. Accurate tracking of active and reactive powers not only stabilizes the grid but also guarantees compliant renewable integration. An adaptive dynamic programming (ADP) approach is adopted, where the critic neural network (NN) approximates the value function and provides optimal control policies. Moreover, an event-triggered mechanism with a dead-zone operation is incorporated to reduce redundant updates, thereby saving computational and communication resources. The stability of the closed-loop system and a strictly positive minimum inter-event interval are guaranteed. Simulation results verify that the proposed method achieves accurate power tracking, improved dynamic performance, and efficient implementation. Full article

Cannabis sativa L. has been cultivated for millennia as a source of food and fibre. Increasing demand for functional foods has renewed interest in C. sativa seeds (hempseeds), which are rich in essential fatty acids and amino acids. However, a near-global moratorium on C. sativa cultivation and research throughout most of the 20th century has delayed crop improvement using modern breeding approaches. As a result, genetic loci contributing to key agronomic traits, including with respect to maximizing yield as a seed crop, remain largely unknown. In this study, a feminized segregating F₂ mapping population, derived from a tall parent with spacious inflorescences and large seeds and a short-stature parent with compact inflorescences and small seeds, was phenotyped for key seed and agronomic traits related to yield. A mid-density Single Nucleotide Polymorphism (SNP) genotyping panel was used to generate a genetic linkage map of 291.5 cM with 455 SNPs. Quantitative Trait Locus (QTL) mapping identified major loci for hundred-seed weight—qHSW3, 26.59 percent variance explained (PVE), seed volume—qSV1, 33.24 PVE, and plant height—qPH9, 46.99 PVE. Our results provide novel target regions, associated molecular markers, and candidate genes for future breeding efforts to improve C. sativa. Full article

The United Kingdom’s (UK) retrofit revolution is at a crossroads and the efficacy of retrofit interventions is not solely a function of insulation thickness. To truly slash emissions and lift households out of fuel poverty, we must solve the persistent problem of thermal bridging (TB), i.e., the hidden flaws that cause heat to escape, dampness to form, and well-intentioned retrofits to fail. This review moves beyond basic principles to spotlight the emerging tools and transformative strategies to make a difference. We explore the role of advanced modelling techniques, including finite element analysis (FEA), in pinpointing thermal and moisture-related risks, and how emerging materials like vacuum-insulated panels (VIPs) offer high-performance solutions in tight spaces. Crucially, we demonstrate how an integrated fabric-first approach, guided by standards like PAS 2035, is essential to manage moisture, ensure durability, and deliver the comfortable, low-energy homes the UK desperately needs. Therefore, achieving net-zero targets is critically dependent on the systematic upgrade of the building envelope, with the mitigation of TB representing a fundamental prerequisite. The EnerPHit approach applies a rigorous fabric-first methodology to eliminate TB and significantly reduce the building’s overall heat demand. This reduction enables the use of a compact heating system that can be efficiently powered by renewable energy sources, such as solar photovoltaic (PV). Moreover, this review employs a systematic literature synthesis to critically evaluate the integration of TB mitigation within the PAS 2035 framework, identifying key technical interdependencies and research gaps in whole-house retrofit methodology. This article provides a comprehensive review of established FEA modelling methodologies, rather than presenting results from original simulations. Full article

The advent of digital transformation, social learning, and the increasing use of artificial intelligence is driving requisite changes in the development of data centres, which are buildings designed to process and store data. Green innovation is an integral component of the sustainable development of data centre units. Solutions utilising green and blue infrastructure in data centres are being currently introduced with the objective of optimising energy consumption and reducing energy demand. The primary aim of the research is to analyse the utilisation of biomass production and blue–green infrastructure in data centres. The article provides a consolidated set of key performance indicators (KPIs): energy efficiency, water use, waste heat utilisation, renewable energy integration, hourly carbon-free matching, embodied carbon, and land use impacts, that can be used to compare different data centre designs. Traditional PUE-centric evaluations are broadened by added metrics such as biodiversity/green area, intensity, and 24/7 CFE, reflecting the broader, multi-dimensional sustainability challenges highlighted in the current literature. Twelve international case studies described in the literature were compared and the feasibility of the Polish pilot project in Michalowo was assessed to illustrate specific cases related to energy-saving solutions and the use of renewable energy sources in data centres. Full article

This study presents a scenario-based modeling framework to evaluate potential decarbonization pathways for Portugal’s road transport sector. The model simulates the evolution of a light-duty vehicle (LDV) fleet under varying degrees of electrification and biofuel integration, accounting for energy consumption, CO₂ emissions and market shares of alternative propulsion technologies. Coupled with projected energy mix trajectories, the framework estimates final energy demand and well-to-wheel (WTW) emissions for each scenario, benchmarking outcomes against national and European climate targets. A key structural limitation identified is the long vehicle survival rate—averaging 14 years—which constrains fleet renewal and delays the transition to full electrification. Diesel-powered light commercial vehicles exhibit even slower replacement dynamics, rendering the Portuguese targets of full electrification by 2030 highly improbable without targeted scrappage and incentive programs. Scenario analysis indicates that even with accelerated electric vehicle (EV) uptake, battery electric vehicles (BEVs) would comprise only 12% of the fleet by 2030 and 77% by 2050. Electrification scenario raises electricity demand fortyfold by 2050, stressing generation and infrastructure. Scenarios that consider diversification of energy sources reduce this strain but require triple electricity for large-scale green hydrogen and synthetic fuel production. Full article

Photovoltaic systems (PV) are increasingly recognized as fundamental to the worldwide adoption of renewable energy technologies. Nonetheless, the efficiency and longevity of solar panels can be compromised by various anomalies, ranging from physical defects to environmental impacts. Early and accurate detection of these anomalies is crucial for maintaining optimal performance and preventing significant energy losses. This study presents SolarAttnNet, a novel convolutional neural network (CNN) architecture with integrated channel and spatial attention mechanisms for solar panel anomaly detection. The proposed model addresses the critical need for automated detection systems, which are crucial for maintaining energy production efficiency and optimizing maintenance. This approach leverages attention mechanisms that emphasize the most relevant features within thermal and visual imagery, improving detection accuracy across multiple anomaly types. SolarAttnNet is evaluated on three distinct solar panel datasets, demonstrating its effectiveness through comprehensive ablation studies that isolate the contribution of each architectural component. Experimental results show that SolarAttnNet achieves superior performance compared to state-of-the-art methods, with accuracy improvements of 3.9% on the PV Systems-AD dataset (94.2% vs. 90.3%), 3.6% on the InfraredSolarModules dataset (92.1% vs. 88.5%), and 3.5% on the RoboflowAnomalies dataset (89.7% vs. 86.2%) compared to baseline ResNet-50. For challenging subtle anomalies like cell cracks and PID, the proposed model demonstrates even more significant improvements with F1-score gains of 4.8% and 5.4%, respectively. Ablation studies reveal that the channel attention mechanism contributes a 2.6% accuracy improvement while spatial attention adds 2.3% across datasets. This work contributes to advancing automated inspection technologies for renewable energy infrastructure, supporting more efficient maintenance protocols and ultimately enhancing solar energy production. Full article

This article presents research on developing a synthetic measure to assess the readiness of individual EU countries to store energy from renewable energy sources. The authors developed individual measures that describe both the technical aspects of energy storage and the systemic and strategic aspects related to energy security and energy transition. These measures enabled the development of a synthetic measure, the Energy Storage Readiness Index (ESRI-BESS), and scenarios for the development of energy storage facilities in the European Union. TOPSIS and Monte Carlo methods were used. In the research presented, the authors focused their analyses on how the system interacts with storage facilities, rather than on what is installed. A quantitative set of indicators was constructed, embedded in the 4A energy security model. The resulting indicator measures not only whether storage facilities exist but also whether the system is prepared to ensure the country’s energy security. The results obtained indicate the need to build a flexible regulatory framework adapted to the growing role of storage facilities, that is, to facilitate and accelerate the process of connecting storage facilities to the grid. In the context of 4A, it is important to note that energy storage facilities can strengthen all four pillars of energy security when infrastructure development is paralleled by reforms and grid integration. The ability to store and flexibly manage energy is becoming a new dimension of energy transformation. Full article