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Nucleosomes are fundamental units of chromatin in which a length of genomic DNA is wrapped around a histone octamer spool in a left-handed superhelix. Large-scale nucleosome maps show a wide distribution of DNA wrapping lengths, which in some cases are tens of base pairs (bp) shorter than the 147 bp canonical wrapping length observed in nucleosome crystal structures. Here, we develop a thermodynamic model that assumes a constant free energy cost of unwrapping a nucleosomal bp. Our model also incorporates linker DNA—short DNA segments between neighboring nucleosomes imposed by the folding of nucleosome arrays into chromatin fibers and other higher-order chromatin structures. We use this model to study nucleosome positioning and occupancy in the presence of nucleosome "breathing"—partial unwrapping and rewrapping of nucleosomal DNA due to interactions with the neighboring particles. We find that, as the unwrapping cost per bp and the chemical potential are varied, the nucleosome arrays are characterized by three distinct states, with low, intermediate, and high densities. The transition between the latter two states proceeds through an equiprobable state in which all nucleosome wrapping lengths are equally likely. We study the equiprobable state theoretically using a mean-field approach, obtaining an excellent agreement with numerical simulations. Finally, we use our model to reproduce S. cerevisiae nucleosome occupancy profiles observed in the vicinity of transcription start sites, as well as genome-wide distributions of nucleosome wrapping lengths. Overall, our results highlight the key role of partial nucleosome unwrapping in shaping the genome-wide patterns of nucleosome positioning and occupancy. [ABSTRACT FROM AUTHOR]

Developing countries face significant challenges in achieving energy stability due to disruptions in their energy supply chains, which jeopardise their sustainability and survivability. Addressing these issues requires careful consideration of public funding in the energy sector and the design of a robust electricity infrastructure. This study aims to identify long-term infrastructure investment strategies that can strengthen the viability of the energy supply network in developing countries, even with limited public funds. The research is underpinned by an empirical study that shows the successful development of energy infrastructure through the effective implementation of viable energy strategies in developing countries. By adopting these strategies, energy supply networks in developing countries can mitigate supply disruptions and avert economic losses. Further, this study evaluates the effectiveness of the viable energy supply network by incorporating a mix of energy resources based on actual data from Pakistan. The contributions of the study are as follows. We develop a viable energy supply network model that considers crucial elements, such as extraction, transportation, generation, transmission, and supply and facilities decision-making. Additionally, we show that the performance of the energy network is not only driven by electricity supply but also influenced by the overall economic growth of the country. [ABSTRACT FROM AUTHOR]

At present, the concept of green and sustainable development has been recognised by everyone. For industrial applications, the concept is both a matter of energy consumption and a matter of production methods. Based on the hybrid flow shop problem, a multi-energy supply system is constructed, and external renewable energy microgrid is introduced to further improve the low-carbon level. From the perspectives of energy supply and internal load, the output of wind power and photovoltaic, energy storage cost and energy consumption cost in the flow shop on a certain day are analysed under the demand–response electricity price. After considering the natural endowments and demand differences of different microgrids, construct a multi-energy complementarity model, determine the coordination transaction strategy among microgrids and obtain the solution of the subproblem and the equilibrium solution of the whole problem. Finally, an example is given to evaluate the effectiveness of the proposed strategy under time-of-use prices. The results show that the proposed strategy can effectively improve the utilisation rate of renewable energy in the flow shop while reducing the overall operating cost. [ABSTRACT FROM AUTHOR]

The rise of digital technologies and open innovation has revolutionized innovation practices, creating new opportunities for moving born-physical open innovation settings to metaverse-like virtual environments. This study explores a virtual corporate-startup collaboration program in the energy industry to understand how digital feature usage facilitates trusted relationships and enables successful pilots. This article presents a framework that emphasizes the strategic use of digital information and interaction features for targeting and bonding with partners. Program managers can tackle the unrealized metaverse through ubiquitous program management and overcome social barriers through adaptive social engineering of digital interactions. This article also provides an outlook on evolving technologies and hybrid designs. [ABSTRACT FROM AUTHOR]

Using a well-developed reaction coordinate in umbrella sampling, we studied the single peptide permeation through a model cancerous cell membrane, varying the hydrophilicity and the charge of the peptides. Two peptides, melittin and pHD108, were studied. The permeation mechanism differs from a barrel-stave-like mechanism to toroidal pore and vesicle formation based on the number and the placement of the hydrophilic amino acids in the peptide. Membrane curvature changes dynamically as the permeation process occurs. In the case of vesicles, the peptide traverses along a smooth, homogenous pathway, whereas a rugged, steep pathway was found when lipid molecules did not line up along the wall of the membrane (barrel-stave-like mechanism). A mechanism similar to a toroidal pore consists of multiple minima. Higher free energy was found for the permeating terminal containing charged amino acid residues. Vesicle formation was found for pHD108 peptide N-terminal with a maximum membrane thinning effect of 54.4% with free energy cost of 8.20 ± 0.10 kcal mol−1 and pore radius of 2.33 ± 0.07 nm. Insights gained from this study can help to build synthetic peptides for drug delivery. [ABSTRACT FROM AUTHOR]

Energy utilities play an important role in transitioning to a sustainable energy industry. Data on 8967 transactions by 19 European energy utilities from 1990 to 2019 illustrate when and how utilities invest in sustainable resources and divest traditional resources such as fossil-fuel plants. Utilities transitioning to sustainable energy have greater financial resources and experience with sustainability, are publicly owned, and access sustainable resources of international and inter-industry partners. Utilities adopt a diversified strategy of balancing sustainable and traditional resources. [ABSTRACT FROM AUTHOR]

The coordination strategies of a two-echelon coal supply chain consisting of a coal enterprise and a downstream enterprise are proposed considering market low-carbon preference and carbon emissions reduction. The cleaning and matching degree (CMD) is introduced to measure the quality of commercial coal which have influence on the production cost and energy consumption of the downstream enterprise. Stackelberg models are established to investigate the coordination strategies using cost-sharing contracts. We use backward induction to solve the models and analyse the optimal decisions in four scenarios. It is revealed that promoting CMD level can extend the market portion and realise more profit. The cost-sharing contract can coordinate the supply chain members, obtain profit Pareto improvement in certain condition of cost-sharing ratio and establish a win-win situation. Additionally, the emission reduction is greater than that under decentralised decision-making. [ABSTRACT FROM AUTHOR]

In this study, peptides designed using fragments of an antifreeze protein (AFP) from the freeze-tolerant insect Tenebrio molitor, TmAFP, were evaluated as inhibitors of clathrate hydrate formation. It was found that these peptides exhibit inhibitory effects by both direct and indirect mechanisms. The direct mechanism involves the displacement of methane molecules by hydrophobic methyl groups from threonine residues, preventing their diffusion to the hydrate surface. The indirect mechanism is characterized by the formation of cylindrical gas bubbles, the morphology of which reduces the pressure difference at the bubble interface, thereby slowing methane transport. The transfer of methane to the hydrate interface is primarily dominated by gas bubbles in the presence of antifreeze peptides. Spherical bubbles facilitate methane migration and potentially accelerate hydrate formation; conversely, the promotion of a cylindrical bubble morphology by two of the designed systems was found to mitigate this effect, leading to slower methane transport and reduced hydrate growth. These findings provide valuable guidance for the design of effective peptide-based inhibitors of natural-gas hydrate formation with potential applications in the energy and environmental sectors. [ABSTRACT FROM AUTHOR]

We have performed classical molecular dynamics simulations using the fully polarizable Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) forcefield implemented within the Tinker package to determine whether a more adequate treatment of electrostatics is sufficient to correctly describe the mixing of methane with water under high pressure conditions. We found a significant difference between the ability of AMOEBA and other classical, computationally cheaper forcefields, such as TIP3P, simple point charge–extended, TIP4P, and optimized potentials for liquid simulations–all atom. While the latter models fail to detect any effect of pressure on the miscibility of methane in water, AMOEBA qualitatively captures the experimental observation of the increased solubility of methane in water with pressure. At higher temperatures, the solubility of water in methane also increases; this seems to be associated with the breakdown of the fourfold hydrogen-bonded water network structure: bonding in water is weaker, so the energy cost of solution is lowered. [ABSTRACT FROM AUTHOR]

Energy efficiency has become a major concern for manufacturing systems, due to industry being the largest user of scarce, finite energy sources, and also to recent events which have pushed energy prices to alarming levels. In the present Industry 4.0 context, Reconfigurable Manufacturing Systems (RMS) are therefore one of the most promising manufacturing paradigm. In this paper, we investigate the suitability of one of the most common types of RMS, the Parallel-Serial manufacturing line with Crossover, to help minimise the peak of the electric power consumption. More specifically, the balancing of such a production line is studied, so as to integrate power peak minimisation from the design stage. Thus, we define the Parallel-Serial-with-Crossover Assembly Line Balancing Problem with Power Peak Minimization, a new combinatorial NP-hard problem. We also propose a suitable time-indexed Integer Linear Program that integrates balancing and scheduling decisions and a matheuristic algorithm designed to tackle large-size instances. Both approaches are tested on a wide set of instances. The computational results show that relevant power peak reductions can be achieved (33% on average), opening up promising perspectives from both algorithmic and managerial viewpoints. [ABSTRACT FROM AUTHOR]

Phase separation plays a key role in determining the self-assembly of biological and soft-matter systems. In biological systems, liquid–liquid phase separation inside a cell leads to the formation of various macromolecular aggregates. The interaction among these aggregates is soft, i.e., they can significantly overlap at a small energy cost. From a computer simulation point of view, these complex macromolecular aggregates are generally modeled by soft particles. The effective interaction between two particles is defined via the generalized exponential model of index n, with n = 4. Here, using molecular dynamics simulations, we study the phase separation dynamics of a size-symmetric binary mixture of ultrasoft particles. We find that when the mixture is quenched to a temperature below the critical temperature, the two components spontaneously start to separate. Domains of the two components form, and the equal-time order parameter reveals that the domain sizes grow with time in a power-law manner with an exponent of 1/3, which is consistent with the Lifshitz–Slyozov law for conserved systems. Furthermore, the static structure factor shows a power-law decay with an exponent of 4, consistent with the Porod law. [ABSTRACT FROM AUTHOR]

Recent management research suggests that firms try to orchestrate conformity and distinctiveness in their behavior to reconcile opposing demands of norm compliance and competitive distinction in order to appear optimally distinct. Whether they succeed or not depends on how audiences perceive the multiple signals they elicit. Extant literature has not fully uncovered how the media combine these different signals to form a representation of firms' behavior and their subsequent reactions to these combinations. We adopt a configurational approach to address this gap in the environmental sustainability context. Drawing on unique proprietary data on 118 cases in the energy utility industry and using fsQCA, we determine that different equifinal signal configurations are associated with positive media coverage regarding environmental behavior or the lack thereof. We then generate five patterns of signals that explain media reactions and disentangle the underlying logics behind them. Our study adds to the research on the multifaceted nature of signal (in)congruence perception by discussing the role of conformity and distinctiveness and highlighting that this perception depends on the signals' credibility. Delivering a balanced orchestration of conformity and distinctiveness signals is possible, but complex, because audiences tend to penalize incongruent postures they cannot associate with a given category. [ABSTRACT FROM AUTHOR]

The free energy cost of forming a cavity in a solvent is a fundamental concept in rationalizing the solvation of molecules and ions. A detailed understanding of the factors governing cavity formation in bulk solutions has inter alia enabled the formulation of models that account for this contribution in coarse-grained implicit solvation methods. Here, we employ classical molecular dynamics simulations and multistate Bennett acceptance ratio free energy sampling to systematically study cavity formation at a wide range of metal–water interfaces. We demonstrate that the obtained size- and position-dependence of cavitation energies can be fully rationalized by a geometric Gibbs model, which considers that the creation of the metal–cavity interface necessarily involves the removal of interfacial solvent. This so-called competitive adsorption effect introduces a substrate dependence to the interfacial cavity formation energy that is missed in existing bulk cavitation models. Using expressions from scaled particle theory, this substrate dependence is quantitatively reproduced by the Gibbs model through simple linear relations with the adsorption energy of a single water molecule. Besides providing a better general understanding of interfacial solvation, this paves the way for the derivation and efficient parametrization of more accurate interface-aware implicit solvation models needed for reliable high-throughput calculations toward improved electrocatalysts. [ABSTRACT FROM AUTHOR]

Zirconium carbide (ZrC) is commonly used for energy sector research, as well as a surrogate for the proposed advanced nuclear fuel candidate uranium carbide. This study investigates structural modifications to nanocrystalline and microcrystalline ZrC resulting from dense electronic excitations induced by swift heavy ion exposure. Samples were irradiated with 946 MeV Au ions to various fluences up to 6 × 1013 ions cm−2 and characterized using synchrotron-based x-ray diffraction. The evolution of the unit-cell parameter and heterogeneous microstrain were evaluated as a function of fluence and compared with those of nanocrystalline and microcrystalline CeO2 (a surrogate for UO2 fuel) irradiated under identical conditions. Distinct differences were observed in the radiation responses of the carbide and oxide across both grain sizes. Most notably, microcrystalline ZrC exhibits swelling characterized by two distinct regimes, which does not result in saturation at the ion fluences achieved. This contrasts with CeO2, which exhibits the well-documented direct-impact defect accumulation mechanism, reaching a steady-state saturation of swelling at higher fluences. Nanocrystalline CeO2 undergoes more pronounced swelling compared with microcrystalline CeO2, in contrast to nanocrystalline ZrC, which exhibits only minimal unit-cell changes. These results demonstrate that swift heavy ion-induced structural changes can be quite different in carbides and oxides, which must be considered when extrapolating fission-fragment type damage in current fuels to advanced fuels. [ABSTRACT FROM AUTHOR]

The significant environmental impact of carbon dioxide emissions in the energy sector, especially from transportation, calls for exploring alternative energy carriers to reduce these emissions. Promoting hydrogen as an eco-friendly energy vector can significantly lower greenhouse gas emissions from heavy-duty vehicles. Assessing hydrogen production infrastructure is therefore critical. This research evaluates a network of pilot refuelling stations for heavy-duty applications along Highway 401, a key trade route in Canada. A feasibility analysis combines thermodynamic assessment and cost estimation of the 4-step Cu–Cl cycle, addressing a key gap in its techno-economic study. The integrated energy system proposed utilizes solar panels, the grid, wind turbines, and industrial waste heat to produce hydrogen via the Cu–Cl cycle. The findings reveal the substantial impact of location on the optimal solution configuration, emphasizing the importance of considering local weather data. Employing an optimization algorithm, the best hybrid energy system is composed of 1891 kW PV arrays, 3822 kW WTs, 13.22 kgH 2 /hour, a 220 kg H 2 tank, and 1064 kW CNV with a renewable fraction of 98% in Windsor, Ontario. The levelized cost of hydrogen for Windsor, Toronto, Kingston, and Cornwall are $2.78/kgH 2 , $2.79/kgH 2 , $3.25/kgH 2, and $3.22/kgH 2 , respectively. Additionally, a comprehensive sensitivity analysis explores the effects of energy market fluctuations, fleet size variations, and greenhouse gas emissions on key economic and environmental parameters. The levelized cost of hydrogen decreases significantly from $12.48 for a 10-truck fleet size to $1.56 for a 100-truck fleet size. This research contributes to fostering synergies between the transportation sector and electricity networks, advancing the transition towards a net-zero energy future. [Display omitted] • A techno-economic feasibility study on a network of pilot H 2 refuelling infrastructure to serve heavy-duty transportation across Highway 401. • The optimal energy solution is influenced by climate conditions. • 1891 kW PV, 3822 kW WT, 13.22 kgH 2 /hour Cu–Cl unit, and 1064 kW CNV as the optimal system. • The lowest NPC and pertaining LCOH are $7.3 M $2.78/kg for Windsor, Ontario. • The optimal solution emits only about 100 tonnes of CO 2 over the project lifespan. [ABSTRACT FROM AUTHOR]

This study presents the design, construction, and evaluation of a hybrid renewable energy system integrating a wind turbine, proton exchange membrane electrolyzer, and proton exchange membrane fuel cell. The system efficiently converts excess wind power into hydrogen during off-peak hours and utilizes stored hydrogen for electricity generation during peak demand. Laboratory experiments optimized the proton exchange membrane electrolyzer and proton exchange membrane fuel cell, achieving maximum hydrogen production of 55 mL/min at 5 V and a peak fuel cell power output of 1.877 W at 50 °C. Simulation results demonstrated the hybrid renewable energy system's ability to deliver reliable power at an energy cost of $0.6342/kWh under optimal conditions. Two scenarios were analyzed: (1) wind turbine and fuel cell operating concurrently and (2) wind turbine supplying the electrolyzer and fuel cell meeting the load independently. Scenario 1 proved more cost-effective, with the wind turbine generating 660 kW and the fuel cell 200 kW. This research highlights the potential of hybrid renewable energy systems to address energy demand challenges, reduce costs, and improve sustainability, providing practical solutions for off-grid applications. [Display omitted] • Wind/Hydrogen/Fuel Cell system effectively meets energy needs in Koohin region. • PEMELZ performed best with 0.5 M Sulfuric acid as the electrolyte. • FC achieved peak performance with preheated inlet air at 50 °C. • Maximum HYP was 5.4 L/h in the optimized system. • Energy cost was 0.6342 $/kWh when WT and FC worked simultaneously. [ABSTRACT FROM AUTHOR]

Based on a follow-up study of Xizang Autonomous Region’s ecological civilization construction and its clean energy development, this paper takes Chamdo as a case study and uses the SWOT matrix to analyze the basic conditions, challenges, and possible pathways for clean energy development. The purpose is to discuss whether Xizang can play a prominent role in the green and low-carbon transition. It demonstrates that, under the framework of nationwide planning, starting from Xizang’s resource endowments and the practical demands of sustainable development, Xizang can capitalize on external opportunities, such as policy advantages and power assistance, to build a diversified clean energy system that integrates hydropower, wind, solar, and energy storage. By strengthening the coordination between the clean energy sector and other industries, Xizang can promote both local consumption of clean energy and its transmission to other regions. This not only enables Xizang to play a prominent role in the nation’s green and low-carbon transition, but also uses clean energy as a bridge to reinforce collaborative efforts among eastern, central, and western regions in achieving dual carbon goals, while fostering common prosperity, and enhancing national unity. [ABSTRACT FROM AUTHOR]

This study analyzes the potential of renewable hydrogen in industrial and domestic applications, production, storage and transportation methods with a comparative approach. Renewable hydrogen plays an important role in the energy sector with its potential to increase energy supply security, reduce carbon footprint and become independent from fossil fuels. These roles include integration with renewable energy systems, use as a sustainable fuel source and energy storage solutions. In the study, the economic and environmental effects of water electrolysis, thermochemical and photoelectrochemical production methods and hydrogen storage technologies were comprehensively examined. In addition, it was revealed that hydrogen has the potential to be integrated with energy systems, increase energy efficiency and reduce energy costs. The study emphasizes the role of renewable hydrogen in sustainable energy transition and argues that more research should be done in this area. As a result, it is stated that infrastructure investments should be accelerated and appropriate policy supports should be provided for the widespread use of hydrogen technologies. • Renewable hydrogen reduces carbon footprint and enhances energy security. • Water electrolysis supports hydrogen production with zero carbon emissions. • Thermochemical methods balance cost and efficiency for hydrogen generation. • Hydrogen storage includes compressed gas, liquid, and metal hydrides. • Domestic hydrogen use cuts energy costs and boosts energy independence. • Policies support hydrogen integration for sustainable energy systems. • Infrastructure investment accelerates the hydrogen energy transition. [ABSTRACT FROM AUTHOR]

Background: An 'energy community' can add socioeconomic components to microgrids and has recently been solidified as the regulatory concept of a 'Citizen Energy Community' by the European Union. Such energy communities can further be supplemented with digital capabilities. This paper provides insights from a 13-month case study on a digitally enabled energy community with prosumers with limited ability to provide manual demand response, who were enabled to engage in peer-to-peer trading of local energy generation. Results: Long-term willingness to pay for local sustainable electricity in the market environment was lower than expected. Overall willingness and ability to provide manual demand response might be low. Participants' use of the provided digital tools were at least partly driven by their desire to control energy costs. Conclusions: Repeat interaction with the energy community's market and its inherent complexities might limit the ability of energy communities to provide technical and economic benefits. This diminishes the appeal of corresponding business models. One direction to make energy communities more attractive to regulators and utilities is the conceptualization, design, and empirical evaluation of systems that lead to low perceived complexity for participants while enabling high levels of external automated control. [ABSTRACT FROM AUTHOR]

In isolated microgrids, distributed energy resources (DERs) such as small-scale generators, energy storage systems, and flexible loads operate independently from the main grid. The challenge is to optimize these resources to minimize user costs while ensuring microgrid stability and efficiency. This paper presents an optimization framework for DERs, leveraging a game-theoretical approach to demand-side management (DSM) in an isolated microgrid environment. Each participant aims to minimize their total cost by strategically managing renewable energy generation, storage, and consumption. The framework models the DSM problem as a noncooperative game, identifying equilibrium points where no user can unilaterally reduce costs. The proximal decomposition algorithm is employed to iteratively update user strategies, ensuring convergence to a Nash equilibrium. Furthermore, a blockchain-based system with smart contracts is integrated to automate critical processes, including registration, event detection, DSM actions, and incentive distribution. This integration enhances transparency, security, and efficiency in the microgrid. During the registration phase, all devices are authenticated and authorized through a secure, transparent blockchain ledger. Event detection is managed by the microgrid Energy Management System (EMS), which continuously monitors voltage and frequency levels, triggering predefined smart contract responses to maintain stability. DSM actions are automatically executed by smart contracts, adjusting energy loads, generation, and storage to balance supply and demand dynamically. The smart contracts also manage the economic incentives that drive participant engagement. They calculate and distribute incentives based on predefined criteria, ensuring accurate and prompt allocation. This process is recorded on the blockchain, providing an immutable and auditable trail of actions and rewards. By leveraging blockchain technology and a game-theoretical approach, the proposed framework ensures continuous optimal operation despite fluctuations in energy demand and renewable generation. This dynamic and adaptive model promotes decentralized and efficient energy management within the microgrid, fostering a resilient and sustainable energy ecosystem. [ABSTRACT FROM AUTHOR]

Introduction: Smart grid technology is a crucial direction for the future development of power systems, with electric vehicles, especially new energy vehicles, serving as important carriers for smart grids. However, the main challenge faced by smart grids is the efficient scheduling of electric vehicle charging and effective energy management within the grid. Methods: To address this issue, we propose a novel approach for intelligent grid electric vehicle charging scheduling and energy management, integrating three powerful technologies: Genetic Algorithm (GA), Gated Recurrent Unit (GRU) neural network, and Reinforcement Learning (RL) algorithm. This integrated approach enables global search, sequence prediction, and intelligent decision-making to optimize electric vehicle charging scheduling and energy management. Firstly, the Genetic Algorithm optimizes electric vehicle charging demands while minimizing peak grid loads. Secondly, the GRU model accurately predicts electric vehicle charging demands and grid load conditions, facilitating the optimization of electric vehicle charging schedules. Lastly, the Reinforcement Learning algorithm focuses on energy management, aiming to minimize grid energy costs while meeting electric vehicle charging demands. Results and discussion: Experimental results demonstrate that the method achieves prediction accuracy and recall rates of 97.56% and 95.17%, respectively, with parameters (M) and triggers (G) at 210.04 M and 115.65G, significantly outperforming traditional models. The approach significantly reduces peak grid loads and energy costs while ensuring the fulfilment of electric vehicle charging demands and promoting the adoption of green energy in smart city environments. [ABSTRACT FROM AUTHOR]

As the global population continues to grow, so does the demand for energy resources. As a consequence, using renewable energy sources as an alternative to fossil fuels has become mandatory to reduce the environmental footprint of the energy sector. Biofuels represent a renewable source of energy, but their production has raised concerns regarding their possible impacts on food security. Indeed, the current biofuel production primarily relies on food crops and arable lands. That is in conflict with the need to produce more food for an increasing world population. To overcome this incongruence, it is proposed to cultivate second-generation biofuel crops on marginal lands, since this option could bring benefits in terms of food security and sustainability. Based on the scientific literature, we addressed the following critical points: (i) whether marginal land worldwide can be considered a reasonable alternative to arable lands for biofuel production; (ii) evaluate the sustainability of biofuel production with respect to unintended negative consequences of crop cultivation such as indirect land use change, social insecurity and loss of biodiversity. It was concluded that the amount of land for growing plants can possibly sustain both food and biofuel production if marginal land are included. In this context, it becomes a priority to select biofuel crops with high productivity on marginal lands and pronounced resilience and adaptability traits. Underutilized crops such as Carthamus tinctorius, Ricinus communis, Brassica carinata, Camelina sativa etc. may fit the purpose and may represent a valuable alternative to first-generation feedstock because they require minimal agronomical input. Using underutilized crops on marginal lands can also provide important ecological services, including improving soil fertility and water regulation, increasing biodiversity and reducing soil erosion. To fully exploit this option, it will be critical to calibrate plant growth models to estimate the potential biofuel production on marginal land from second-generation feedstock and to create tools for a more rational management of this land. [ABSTRACT FROM AUTHOR]

This paper, which presents highlights of the World Energy Employment report 2023 published by the International Energy Agency with the support and analytical contribution of Enel Foundation, provides an overview of the impacts of decarbonization process on the energy workforce at a global level. Data collected and estimated with deep granularity across the entire value chain shows that increasing investments in the power sector, electric vehicles and other clean technologies are fuelling workforce growth in the energy sector: nearly 67 million people were employed in the energy sector worldwide in 2022, an increase of 3.4 million jobs compared to 2019. Projections under several energy transition scenarios demonstrate that the energy transition will have a net positive effect on jobs through 2030, with job additions in clean energy sectors far outweighing declines in sectors associated with fossil fuels. However, a more detailed analysis of the most in-demand skills within the energy sector reveals that skills shortages in some sectors are preventing the workforce from growing as quickly as needed. Across the energy industry, employers are reporting difficulty hiring and retaining workers with the skills needed to deploy clean energy technologies. To relieve this bottleneck, the paper identifies key intervention areas to build a pipeline of skilled labour (e.g., through reskilling and upskilling initiatives, along with energy transition-focused education) and thus minimize employment-related delays in the decarbonization process. [ABSTRACT FROM AUTHOR]

The paper analyzes the problem of entropy in the moments of transition from a normal economic situation (2015–2019) to the Pandemic period (2020–2021) and the period of Russia's attack on Ukraine (2022–2023). The research in the article is based on the analysis of electricity, oil, coal, and gas prices in 27 countries of the European Union and Norway. The daily data cover the period from January 1, 2015, to March 30, 2023, and were analyzed using two-dimensional sets of electricity and commodity prices. The work uses the time dependent James-Stein estimator of the Shannon informational entropy. [ABSTRACT FROM AUTHOR]

Industry 4.0 has transformed manufacturing with the integration of cutting-edge technology, posing crucial issues in the efficient task assignment to multi-tasking robots within smart factories. The paper outlines a unique method of decentralizing auctions to handle basic tasks. It also introduces an improved variant of the improved Binary Particle Swarm Optimization (IBPSO) algorithm to manage complicated tasks that require multi-robot collaboration. The main contributions we make are: the design of an auction decentralization algorithm (AOCTA) which allows for an efficient and flexible task distribution in dynamic contexts, the optimization of coalition formation in complex jobs by using IBPSO and improves the efficiency of energy and decreases the cost of computation as well as thorough simulations that show that our proposed method significantly surpasses conventional methods for efficiency, task completion rates in terms of energy usage, task completion rate, and scaling of the system. This research contributes to the development of smart manufacturing through providing an effective solution that aligns with the sustainability objectives and addresses operational efficiency as well as environmental impacts. Addressing the challenges posed by dynamic task allocation in distributed multi-robot systems, these advanced technologies provide a comprehensive solution, facilitating the evolution of innovative manufacturing systems. [ABSTRACT FROM AUTHOR]

Due to deregulation energy market has stimulated the need for optimizing its bidding strategies in order to achieve economic benefit in the competitive market. It is important to investigate bidding strategy of microgrid (MG) in electricity, heat and natural gas market based on MG's clearing price. The paper discusses about optimum day-ahead heat, power and natural gas market bidding strategy for MG assimilated battery swapping stations (BSSs) considering carbon capture. MG includes PVT panels, wind turbine generators, small hydro power plants, biomass fired micro-cogeneration units (BFMCUs), micro pumped hydro energy storage, BSSs, local electricity, heat and natural gas loads. Carbon capture unit, hydrogen storage unit, electrolyzer and methanation unit have been utilized for supplying natural gas demand. Natural gas is generated by utilizing carbon dioxide which is captured from BFMCUs and hydrogen produced by electrolyzer. Demand response program (DRP) is applied to level demand curves. Snow ablation optimizer, self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, differential evolution and grey wolf optimization are used to solve this problem. It is realized that total profit of MG achieved from optimum bidding without DRP is less than that of achieved with DRP. Maximum profit acquired with DRP is almost 9.6% higher than maximum profit acquired without DRP. [Display omitted] • Day-ahead optimum bidding for sustainable power, heat and natural gas is studied. • Carbon capture of biomass fired micro-cogeneration units is taken into account. • Battery swapping station and micro pumped hydro energy storage are considered. • Demand response program has been taken into account. [ABSTRACT FROM AUTHOR]

The integration of hydrogen energy systems (HESs) into power systems offers a significant opportunity to reduce reliance on fossil fuels and enhance system flexibility. The HES comprises hydrogen generation systems, hydrogen travelers, and hydrogen refueling stations. This study introduces a comprehensive framework for incorporating HESs within an active distribution network. A dual-stage optimization strategy is proposed: the first stage focuses on determining the optimal power bids for the day-ahead (DA) energy and flexible ramp product (FRP) markets, alongside identifying the optimal locations for mobile energy storage systems (MESSs). The second stage addresses the cost-effective routing of MESSs and hydrogen travelers, incorporating traffic uncertainties and insights gained from the initial stage. The presented model evaluates the significance of adopting hydrogen generation systems beside stationary energy storage systems (SESSs) and MESSs in delivering FRPs and energy services in day-ahead markets. A novel time-based traffic model for MESSs and hydrogen travelers is developed to minimize transportation costs, which ultimately influence the pricing of the energy carrier. The optimization framework is validated using the IEEE 37-bus benchmark and an associated transportation network. Results indicate that the proposed two-stage optimization approach significantly enhances the profits of the distribution system operator through active market engagement. Ultimately, this study highlights the importance of integrating electricity and hydrogen for achieving a sustainable energy future. • Presenting a two-stage network-constrained model for mixed hydrogen-power systems. • Developing an in-depth flexible ramp product model for hydrogen generation systems. • Assessing the flexibility capability of hydrogen storage beside flexible resources. • Proposing a novel, time-based routing framework for travelers and mobile storages. [ABSTRACT FROM AUTHOR]

Large-scale production of hydrogen using clean electricity from renewable energy sources (RESs) is gaining more momentum in attempts to foster the growth of the nascent hydrogen energy market. However, the inherited intermittency of RESs constitutes a significant challenge for the reliable and economic operation of electrolysers and consequently the overall hydrogen production plant. This paper proposes a power allocation control strategy to regulate the operation of a multi-unit electrolyser plant fed by a solar power system, for improved efficiency and economic hydrogen production. Proper implementation of the proposed control strategy can decrease the number of switching times, increase hydrogen production, raise the efficiency, and extend the operational lifespan of the utilised electrolyser units. A solar-hydrogen system comprising a 1 MW electrolyser plant and a battery system is designed, and implemented in MATLAB/Simulink environment to validate the efficacy of the proposed control strategy in improving the performance and reliability of an Industrial Green Hydrogen Hub (IGHH). The simulation results showed an improvement of 52.85% in the daily production of hydrogen with an increase of 71.088 kg/day, a 68.67% improvement in the efficiency, and an enhancement of more than 80% in the utilisation factor of the IGHH compared to other control techniques (traditional choppy control). • Coordinating the operation of multi-unit multi-MW electrolysers is investigated. • A BESS is integrated to suppress the fluctuations in renewable energy output. • Segmented control is used to control the operation of large multi-unit electrolysers. • The utilised control improved the yield and efficiency of green hydrogen production. • The utilised control enhanced the utilisation of the renewable power-to-X systems. [ABSTRACT FROM AUTHOR]

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In modern buildings, windows and facades are significant sources of energy inefficiency that account for 40% of the energy cost of the entire building due to the thermal energy loss during both summer and winter in terms of heat gain and heat loss. This further increases the energy expenditure of the heating, ventilation, and air-conditioning (HVAC) system. To address this issue, double-glazed windows are converted into liquid-filled tunable window systems, where the heat in-flux and out-flux to the room can be regulated by adjusting flow properties. Researchers have recently focused their attention on integrating microfluidic technologies into fluidic windows for the transport of fluid, as it demonstrated superior performance in terms of energy recovery and adaptive lighting. The objective of this review is to summarize engineering perspectives and recent progress in the design and efficiency of fluidic window systems with a particular emphasis on the advantages of integrating microfluidics. In this study, a comprehensive metadata analysis was conducted based on the obtained literature from the Scopus database. A description of the numerical methods, experimental setup, material properties, influence of microfluidic integration to the building's facade system, advantages, disadvantages, and future perspectives of these fluidic window systems is provided in detail. [ABSTRACT FROM AUTHOR]

In an era where energy transitions are critical for addressing climate change and ensuring economic stability, energy policy uncertainty (EGU) emerges as a crucial factor influencing energy consumption patterns. This study investigates the complex relationship between EGU and various forms of energy consumption, including fossil fuels, renewables, and total energy use across G7 countries from 1996 to 2022. Utilizing FMOLS (fully modified OLS) and DOLS (dynamic ordinary OLS) models, long-term relationships among variables were established and robustness was checked by employing ARDL (autoregressive distributed lag) model. Our findings reveal that EGU significantly hampers fossil fuel consumption, impedes renewable energy uptake, and affects total energy consumption adversely. These effects underscore the broader implications of policy uncertainty on energy strategies. Specifically, the robustness checks confirm that these relationships hold across different model specifications and periods. In addition, analysis reveals the dynamic impact of control variables including FDI inflow, institutional quality, banking development, and inflation rates on specific energy consumptions. Policy implications are profound: governments must prioritize the stabilization of energy policies to enhance investor confidence and facilitate the transition to sustainable energy sources. Additionally, targeted interventions to mitigate uncertainty can promote the development of renewable energy infrastructure and support more predictable energy markets. This study provides new insights into the impacts of policy uncertainty on energy consumption and offers a foundation for strategic policy formulation aimed at achieving a balanced and sustainable energy future. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polymer (CFRP) composites exhibit excellent characteristics such as light weight, high specific strength, specific stiffness, and chemical stability, making them customizable to meet the specific demands of various sectors such as the automotive, aerospace, defense, biomedical, and energy industries. However, the inert surface of carbon fibers (CFs) results in a poor interface compatibility with polymer matrices, leading to numerous interfacial defects and pores in prepared CFRP composites. These drawbacks significantly limit the application of CFRP composites in high‐end fields. The higher surface area and smaller size of nanomaterials provide multiple advantages for high‐performance CFRP composites that enhance the mechanical properties, impact resistance and interface adhesion between the fiber and the matrix. Hence, this review firstly summarizes the interfacial behavior and interface enhancement mechanisms for CFRP composites. Subsequently, we comprehensively review the recent advances in various nanomaterials‐modified CFRP composites, including carbon‐based nanoparticles, silicon‐based nanomaterials and metal nanomaterials, et al. Besides, we also present the applications of CFRP in emerging fields, such as military, aerospace, automotive, sports equipment, and medical, etc. Finally, we also prospected the challenges and future development trends of CFRP composites, aiming to provide new ideas and insights for future research on nanomaterial modifications and promote the development of high‐performance CFRP composites. Highlights: The interface reinforced theory of CFRP is comprehensively summarized.Different types of nanoparticles that can be used for reinforcement in CFRP composites and nanomaterials modification methods are reviewed.Application of CFRP composites in various fields is presented.Challenges and future development directions of preparation of high‐performance CFRP composites are proposed. [ABSTRACT FROM AUTHOR]

Workflow tasks in the cloud environment are the abstraction and decomposition of large‐scale and complex tasks in real‐world scenarios, so cloud workflow scheduling problems have important research significance. However, most of the existing cloud workflow scheduling schemes are aimed at a single workflow, and do not make reasonable use of the commonality or complementary knowledge between similar tasks. Moreover, most cloud workflow scheduling models mainly focus on a few objectives such as time or cost, which is not comprehensive enough. Therefore, this paper first proposes a multi‐objective cloud workflow scheduling model, which solves the maximum completion time, execution cost and energy consumption as three objectives during task execution. Secondly, to efficiently handle multiple similar cloud workflow scheduling tasks at the same time, this paper treats various cloud workflow scheduling issues as distinct tasks, establishes a multi‐task cloud workflow scheduling framework that aims for the same goal while accommodating workflows of differing scales, and a multi‐objective evolutionary multi‐task optimization algorithm based on elite selection (MOEMT‐ES) is designed to solve the above scheduling model. Finally, through algorithm comparison experiments on the CEC2017 evolutionary multi‐task optimization competition benchmark problem and multi‐workflow test problem, MOEMT‐ES shows superior competitiveness. [ABSTRACT FROM AUTHOR]

Covalent organic frameworks (COFs) represent a highly versatile class of crystalline porous materials, formed by the deliberate assembly of organic building units into ordered two-dimensional (2D) and three-dimensional (3D) structures. Their unique combination of topological precision and tunable micro- or mesoporous architectures offers unmatched flexibility in material design. By selecting specific building units, reactive sites, and functional groups, COFs can be engineered to achieve customized skeletal, porous, and interfacial properties, opening the door to materials with optimized performance for diverse applications. Among recent advances, high-connectivity 3D COFs have emerged as a particularly exciting development, with their intricate network structures enabling unprecedented levels of structural complexity, stability, and functionality. This review provides a comprehensive overview of the synthesis strategies, topological design principles, structural characterization techniques, and emerging applications of high-connectivity 3D COFs. We explore their potential across a broad range of cutting-edge applications, including gas adsorption and separation, macromolecule adsorption, dye removal, photocatalysis, electrocatalysis, lithium–sulfur batteries, and charge transport. By examining these key areas, we aim to deepen the understanding of the intricate relationship between structure and function, guiding the rational design of next-generation COF materials. The continued advancements in this field hold immense promise for revolutionizing sectors such as energy storage, catalysis, and molecular separation, making high-connectivity 3D COFs a cornerstone for future technological innovations. [ABSTRACT FROM AUTHOR]