Search Results (2,066)

Carbon capture is more and more often seen as a component of an integrated carbon-management system than as a stand-alone separation phase. The practical utility of capture technology depends on the chemical state in which the carbon dioxide is held, the energy and material needs for regeneration, the compatibility of the caught species with downstream catalysis and the lifetime of the resulting carbon-containing product. This paper offers an in-depth framework for integrated CO₂ capture and circular carbon use, including catalytic conversion, bio-integrated processes, biomass-derived materials and fuels, hydrogen-enabled routes, mineralization, and artificial intelligence-assisted process design. Reactive capture techniques that convert carbonate, bicarbonate, carbamate, dissolved CO₂ or surface-bound intermediates without first generating a purified gas stream are contrasted with sequential capture, purification, compression, transport and conversion. The thermocatalytic, electrochemical, photoelectrochemical and biological conversion pathways are compared against common parameters such as working capacity, conversion rate, selectivity, carbon efficiency, regeneration energy, stability and life-cycle greenhouse gas performance. Special emphasis is given on dual-functional materials, interfacial reactors, bio-integrated methanation, carbon mineralization in construction materials and coupling with renewable hydrogen. The review also discusses how machine learning, molecular screening, process simulation, graph-based data architecture, and digital monitoring could speed up material selection and system optimization. Across all pathways, the central design requirement is not maximum capture capacity alone, but a balanced match among binding strength, transport, catalytic reactivity, product separation, durability, and carbon permanence. A reporting framework and research agenda are proposed to guide credible scale-up and comparison of integrated carbon-management technologies. Full article

Upgrading biogas to pipeline-quality methane requires the efficient removal of CO₂, yet conventional physicochemical routes remain energy-intensive. Coupling a CO₂-selective membrane with microalgal photosynthetic fixation offers a green alternative, but is constrained by the low CO₂/CH₄ selectivity of common membranes and the poor adhesion of microalgae to hydrophobic membrane surfaces. Here, a dual-functional composite membrane was developed that simultaneously provides CO₂/CH₄ sieving and a biocompatible interface for microalgal attachment, and was integrated into a microalgae membrane bioreactor (MMBR). A cellulose acetate mixed-matrix membrane incorporating polyethyleneimine-grafted ZIF-8 (CA/PZIF-8(15)) achieved a mixed-gas CO₂ permeability of 122.3 Barrer and a CO₂/CH₄ selectivity of 41.17. An ionic-liquid-modified chitosan (CS/IL) coating, first optimized on a commercial flat-sheet polyethersulfone (PES) membrane used as a model surface for the adhesion study, reversed the surface charge from −30.8 to +3.75 mV, lowered the water contact angle to 51.2°, and increased the day-7 adhesion of Scenedesmus obliquus by ~108%. Transferring the coating onto CA/PZIF-8(15) further raised the permeability to 138 Barrer and the selectivity to 57.31, placing the composite above the 2008 Robeson upper bound. In the MMBR, CH₄ purity reached 95.13% after 48 h; a mass balance on the recirculating gas volume indicated that essentially all of the CO₂ removed from the gas phase permeated the membrane, of which an estimated 2% was fixed into microalgal biomass while the remainder was retained in the liquid phase. This work offers a membrane-design strategy that bridges gas-separation functionality and microalgal carbon fixation for sustainable biogas upgrading. Full article

Smart charging stations require mobile charging robots to respond to dynamically arriving charging requests with heterogeneous priorities, varying travel costs, and uneven workloads while maintaining online scheduling feasibility. Conventional single-layer approaches often optimize task assignment or route ordering separately, which limits their ability to coordinate allocation quality, route efficiency, and workload regulation under real-time constraints. This study proposes a hierarchical improved consensus-based bundle algorithm–ant colony optimization (ICBBA-ACO) framework for dynamic multi-robot task allocation. The upper ICBBA layer combines deterministic task clustering, intra-cluster greedy bundling, conflict resolution, and feedback-guided workload-aware reassignment, while the lower ACO layer refines the visiting order of unstarted tasks under fixed ownership using the same normalized four-objective scheduling cost. Complete decision time is evaluated separately against a $200\mathrm{ms}$ online requirement, and estimated motion energy is retained only as a distance-derived auxiliary indicator. In a five-method comparison over 100 paired scenarios, ICBBA-ACO achieves a mean composite objective of $J=0.663052$, a mean decision time of $33.07\mathrm{ms}$, and 100% deadline compliance. GA-MRTA obtains a lower unconstrained mean objective of $J=0.615790$, but requires approximately $2199.30\mathrm{ms}$ on average and satisfies the $200\mathrm{ms}$ requirement in only $8.89\%$ of the evaluated updates. Thus, ICBBA-ACO provides the lowest mean objective among the compared methods that maintain full deadline compliance, demonstrating a favorable quality–runtime trade-off within the tested operating range. ROS-based engineering verification further completes all 15 repeated trials and all 48 verification tasks with no recorded invariant violations. Full article

The transition to a hydrogen-based economy requires efficient and sustainable technologies to convert waste into clean energy carriers. This study investigates the production of hydrogen-rich gas through the integrated pyrolysis steam reforming (PSR) and integrated pyrolysis (PYR) and catalytic steam reforming (PCSR) of real municipal solid waste (MSW). PCSR experiments were conducted in a two-stage series reactor system: an initial pyrolysis stage at 500 °C followed by a catalytic steam reforming stage at 900 °C over a commercial Ni/Al₂O₃ catalyst (9.8 wt.% Ni). Three real MSW samples from the Serra Gaúcha region (Brazil) were evaluated: organic-rich (A), polymeric-rich (B), and a mixed real collection fraction (C). Gas yields from PYR to PCSR increased from 0.44 to 1.18 Nm³·kgMSW⁻¹, from 0.66 to 1.54 Nm³·kgMSW⁻¹, and from 0.35 to 1.50 Nm³·kgMSW⁻¹ for (A), (B), and (C) samples, respectively. Hydrogen concentrations of PCSR were between 32% and 39% volume for all samples, with a marked reduction in CH₄ and CO levels due to the promotion of water–gas shift and methane reforming reactions over the nickel active sites. The PCSR process using a Ni/Al₂O₃ catalyst proves to be a highly effective route for maximizing hydrogen production from real MSW, offering a robust technological solution for energy valorization and carbon footprint reduction. Full article

Maritime routes ensure connectivity between nations, carrying a vast flow of goods across borders, while ports serve as the critical junctions within this network, managing a wide spectrum of commodities from raw materials to finished goods. Ports also generate employment across numerous sectors and underpin a broad range of allied industries. A seaport is a maritime facility equipped with docks, cranes, and storage infrastructure for international trade, where ships load and unload cargo, containers, and passengers. Key functions of seaports include customs processing, warehousing, and vessel services, with major global hubs such as Shanghai, PSA Singapore, DP World, and Rotterdam handling immense volumes of cargo each year. In contrast, Bangladesh’s ports, Chittagong, Mongla, and Payra, play a vital role in sustaining regional commerce. Today, ports are widely recognized as essential capital infrastructure and prime movers of economic activity. Smart ports are automated facilities that leverage advanced digital technologies, including sensors, big data analytics, artificial intelligence (AI), machine learning (ML), deep learning (DL), augmented reality (AR), digital twins, the Internet of Things (IoT), and various automation systems, to optimize overall operational efficiency. These tools streamline cargo movement while embedding sustainable practices to protect the environment. Beyond operational gains, smart ports deliver faster, more advanced services to all stakeholders involved in port operations, including shipping companies, customs agencies, local communities, and other relevant parties. Renewable energy sources, electric vehicle charging stations, onshore power supply, and smart logistics infrastructure are among the defining sustainability features of smart ports in the present-day context. This study examines the current status and future development trajectory of Bangladesh’s sea ports in relation to the broader global imperative toward smart port transformation. Full article

Multipath routing in wireless sensor networks (WSNs) improves reliability by providing alternative forwarding paths when a route fails. However, mobile sinks make path maintenance difficult because sink movement can invalidate previously constructed source-to-sink routes. Existing protocols typically depend on either global path reconstruction, which increases control overhead, or footprint-chaining, which accumulates detours through previous sink positions and may weaken path independence. To address this problem, this paper proposes QL-LGMPRP, a reliability-aware local-grid-based multipath routing protocol that combines a sink-centered local grid, two-path delivery, link-quality-aware forwarding, and lightweight tabular Q-learning for waypoint adaptation. Mobility-related route changes are confined to the sink-centered grid, whereas a compact tabular Q-learning policy adjusts the primary-path direction using grid, link-quality, and energy-related state variables. The sink constructs a local grid around its current position, with cells sized to keep in-grid forwarding locally bounded. When an event occurs, the source computes an entry point on the grid perimeter and constructs two greedy paths: a primary path through a Q-learning-selected waypoint near the grid boundary and a backup path toward the current sink position. The Q-learning agent uses a compact tabular state representation that includes the boundary-cell index, residual-energy level, sink-grid position, and local link-quality information, and learns waypoint offsets using a reward that combines delivery success, transmission energy, and delay. This design confines routing adaptation to the sink-centered grid while allowing the waypoint policy to respond to heterogeneous link conditions. Simulation results under different sink speeds and interference conditions show that QL-LGMPRP maintains high delivery reliability while reducing detour-related forwarding costs relative to footprint-chaining and showing lower weak-link exposure than the geometric-forwarding comparison schemes. Full article

Advanced wireless sensor networks powered by artificial intelligence are increasingly required for applications demanding continuous monitoring, autonomous operation, reliable communication, and fast decision support. This systematic review examines recent work from 2023 to 2026 on energy-efficient, AI-enabled wireless sensor networks (WSNs) in mission-critical environments, with particular focus on power electronics and urban infrastructure systems. The authors synthesize a corpus of 50 DOI-indexed studies satisfying inclusion criteria that received qualitative thematic coding and comparative analysis. Other references were only cited to provide historical, methodological, or technical context and were not included in the systematic review corpus. As such, our results show that AI can improve WSN energy behaviour through routing and clustering, edge AI, reinforcement learning, fuzzy logic, metaheuristic optimization, and AI-based security. At the same time, energy efficiency cannot be treated as an isolated performance target. In mission-critical systems, security, latency, and reliability are closely interlinked requirements. The review concludes that future work should move away from optimizing protocols in isolation, and instead focus on building lightweight, explainable, secure, and field-tested AI-driven WSN architectures suited to real operational environments. Full article

Lignocellulosic fruit peel waste represents an abundant, carbon-neutral feedstock for green biohydrogen production via dark fermentation, yet its rigid compact structure and high cellulose crystallinity severely restrict saccharification and fermentative hydrogen yield. In this study, a hydrothermal acidification pretreatment strategy was proposed to boost dark fermentative biohydrogen generation from navel orange peel waste, and systematic investigations were conducted to reveal the regulating mechanisms of key pretreatment parameters (hydrochloric acid concentration, pretreatment temperature, duration) on reducing sugar release and hydrogen-producing performance. Multiscale characterizations including SEM, XRD, FTIR, and TG were integrated to unravel the microstructural and chemical compositional evolution of raw and pretreated substrates. The results demonstrated that hydrothermal acidification effectively disrupted the dense lignocellulosic network of navel orange peel, lowered cellulose crystallinity, and greatly improved substrate accessibility for hydrolytic reactions and microbial adhesion. Under the optimal pretreatment condition (1.0 mol/L HCl, 120 °C, 1 h), the concentration of released reducing sugars reached 10.2 g/L, which was 67.2% higher than that of untreated raw peel. The corresponding maximum cumulative hydrogen yield attained 36.5 mL H₂/g TS, representing a 67.4% improvement relative to the untreated control group. Pearson correlation analysis verified that pretreatment temperature, acid concentration, and duration exhibited strong positive correlations with hemicellulose and cellulose removal efficiencies, while excessive pretreatment (HCl > 1.0 mol/L, temperature > 120 °C, duration > 1 h) generated inhibitory by-products that suppressed microbial hydrogen evolution. This study comprehensively clarifies the structural modification and biohydrogen promotion mechanism of hydrothermal acidification pretreatment on pectin-rich biomass, and delivers a cost-effective, facile technical route for high-value energy valorization and harmless disposal of fruit processing solid wastes. Full article

Two-dimensional transition-metal carbides and nitrides (MXenes) are increasingly adopted in advanced electronic devices, where their metallic conductivity, optical tunability, and chemically addressable surfaces support next-generation multifunctional optoelectronics. Their practical performance, however, depends not only on their intrinsic properties but also on the heterogeneous interfaces where charges, photons, and ions interact. Unlike earlier reviews organized around synthesis routes or separate device categories, this review takes interfacial chemistry as a single organizing principle and follows it from surface terminations through to integrated systems. The structural and surface-chemical characteristics of MXenes are described first, showing how dynamic terminations and interfacial dipoles regulate work functions and energy-level alignment. We then discuss molecular functionalization, defect passivation, and heterojunction formation as strategies for reducing Schottky barriers and improving charge-transfer kinetics. Optoelectronic platforms built on these engineered interfaces, including high-efficiency photovoltaics, broadband photodetectors, and stretchable wearable systems, are subsequently detailed, together with emerging architectures that merge self-powered sensing with neuromorphic visual functions, a scope seldom treated alongside conventional devices in previous surveys. By connecting surface chemistry with device integration, this review outlines a materials-to-systems pathway toward more reliable and scalable MXene-based optoelectronic technologies. Full article

Solar-assisted thermochemical cycles can convert intermittent solar energy into storable chemical fuels. Within the European SULPHURREAL project, elemental sulfur is investigated as a long-term energy-storage medium in a cycle based on H₂SO₄, S, and SO₂. This work investigates an indirect magnesium-mediated route for the disproportionation of SO₂. The proposed cycle consists of three steps: aqueous reaction of SO₂ with MgO to form sparingly soluble MgSO₃; thermal decomposition of MgSO₃ through competing pathways producing elemental sulfur, MgSO₄, MgO, and SO₂; and high-temperature decomposition of MgSO₄ to regenerate MgO and produce sulfur oxides and oxygen. All three steps were experimentally investigated using laboratory-scale reactors, thermogravimetric analysis, X-ray diffraction, ion chromatography, and calorimetric measurements. The sulfur yield was approximately 25% of the theoretical maximum, corresponding to 8.3% relative to the initial SO₂ amount. Complete MgSO₄ conversion was achieved after 90 min at 1100 °C, at which temperature the SO₂-forming pathway accounted for approximately 87% of the gaseous sulfur products. The experimental results were used to establish a preliminary mass and energy balance for the closed-loop process. The calculated gross heat requirement was 5349 kJ mol⁻¹ of sulfur, corresponding to an energy efficiency of 5.5% when heat recovery was not considered. These results demonstrate the technical feasibility of the proposed magnesium-mediated route and provide a quantitative basis for its further development, identifying sulfur selectivity, high-temperature sulfate decomposition, quantitative product recovery, and heat integration as the main priorities for process optimisation. Full article

Synthetic dyes are widely used in industry; however, their release into the environment without adequate treatment poses serious risks because of their toxicity and adverse effects on human health and aquatic ecosystems. Although conventional methods are effective, they are often costly and have limited sustainability. In this context, ATPSs are proposed as an environmentally friendly alternative aligned with the principles of green chemistry, offering an efficient and cost-effective route. In this study, Tartrazine (Tart), an azo model dye, was used to evaluate the efficiency of an ATPS formed by PEG + salt + H₂O. The effects of the cation and anion nature, PEG molar mass, and pH on Tart partitioning were investigated by determining the partition coefficient of Tart (K_Tart) and the Gibbs free energy of transfer (Δ_trG°). The PEG 1500 + Na₂SO₄ + H₂O ATPS at pH 3.0 exhibited the best performance among the systems evaluated, with a spontaneous transfer process evidenced by Δ_trG° values as low as −21.62 kJ mol⁻¹. The extraction efficiency exceeded 99%, and the ATPS was successfully applied to the removal of Tart from river water and wastewater samples, demonstrating high performance and considerable potential as an alternative technology for the removal of this dye from industrial aqueous solutions. Full article

Multi-agent reinforcement learning has emerged as a promising paradigm for cooperative unmanned aerial vehicle (UAV) swarm coordination. However, existing communication-aware MARL methods primarily focus on communication topology, message routing, and message aggregation, while the information content of the exchanged messages is often only implicitly controlled. In realistic UAV networks, inter-agent communication is constrained by limited bandwidth, communication range, energy consumption, and packet loss. It is therefore desirable for each UAV to transmit compact and task-relevant information rather than dense and redundant latent features. In this paper, we propose IB-CEMARL, an information-bottleneck-guided, communication-efficient multi-agent reinforcement learning framework for UAV swarms. We formulate inter-UAV communication as a minimal sufficient message-learning problem in which each UAV encodes its local observation into a stochastic bottleneck message before exchanging information with its neighbors. Cauchy–Schwarz divergence-based quadratic mutual information is adopted as a unified dependence measure to jointly regularize message compression, preserve decision-relevant information, and reduce statistical redundancy among neighboring UAV messages. Extensive experiments demonstrate that IB-CEMARL achieves superior cooperative performance, reduced message redundancy, and stronger robustness compared with representative communication-aware MARL baselines. In particular, IB-CEMARL improves the average return by $4.9\%$ and reduces inter-message dependence by $29.0\%$ compared with the KL-IB-MARL baseline while maintaining efficient communication under constrained bandwidth settings. Full article

The global energy transition and rapid electrification are driving increased demand for copper. However, conventional pyrometallurgical and hydrometallurgical extraction routes are increasingly challenged by declining ore grades and stricter environmental regulations. Bioleaching involves the microbial catalysis of sulfide mineral dissolution and provides a sustainable method for copper recovery from low-grade ores, tailings and secondary resources. This review provides a critical and integrated analysis of copper sulfide bioleaching, covering microbial diversity, molecular mechanisms, mineralogical controls, operational parameters, and industrial applications. This review also examines the functional roles of prominent acidophiles, including the functional roles of prominent acidophiles, including Acidithiobacillus spp., Leptospirillum spp. and thermophilic archaea, in the oxidation of iron and sulfur, mitigation of passivation, and metal solubilization. The molecular underpinnings of these processes are explored by investigating iron and sulfur oxidation gene networks (the rus operon and sox cluster), copper resistance systems (CopA, CusCBA) and biofilm formation pathways. The mineralogical controls on the behavior of chalcopyrite (refractory/passivating), chalcocite (highly reactive) and bornite (intermediate) are critically assessed. The synergistic effects of key operational parameters (temperature, pH, redox potential, aeration and particle size) on leaching kinetics and microbial community dynamics are investigated. The scalability, efficiency and environmental footprint of industrial applications such as heap, dump, stirred-tank and in situ bioleaching are discussed. Despite more than four decades of commercial development, several challenges remain, such as slow chalcopyrite dissolution, passivation, metal toxicity, and scale-up limitations. Emerging solutions such as synthetic microbial consortia, multi-omics technologies, artificial intelligence-assisted optimization, and digital twins are identified as transformative approaches for next-generation biomining. In this review, microbiology, mineralogy, electrochemistry, and process engineering are integrated to demonstrate that biotechnological leaching is among the most promising technologies for the sustainable production of copper and to identify future directions for its industrial application. Full article

Edible Natural Deep Eutectic Solvents (NADES) offer a route to ready-to-use extracts without solvent removal. This study examined how rational formulation design influences physicochemical properties, extraction performance, energy efficiency, thermal behavior, and cytocompatibility during bioactive recovery from Nigella sativa seeds. Twelve formulations spanning malic acid–polyol, citric acid–polyol, binary polyol, and ternary acid–polyol families were evaluated under standardized ultrasound-assisted conditions and compared with ethanolic ultrasound-assisted extraction, Soxhlet extraction, and cold-pressed oils. Selected NADES formulations outperformed the conventional systems. E1 (malic acid:glycerol:water) achieved the highest total phenolic content and lowest specific energy consumption (40.00 kJ mg⁻¹ GAE), below the Soxhlet benchmark (55.17 kJ mg⁻¹ GAE), whereas E9 (glycerol:xylitol:water) exhibited the greatest ABTS activity. Neat-NADES apparent pH and viscosity were inversely associated with total phenolic content, while viscosity and density were inversely associated with ABTS activity. ATR-FTIR showed stable, solvent-dominated fingerprints over 15 days, whereas DSC better differentiated neat NADES from their extracts. Most systems remained cytocompatible at 10,000× dilution, while acid–polyol formulations reduced viability at 500×; partial neutralization of N5/E5 restored viability. NADES performance was formulation- and application-dependent, requiring joint optimization of composition, acidity, viscosity, energy efficiency, and biologically compatible concentration. Full article

Maritime navigation efficiency is commonly assessed using isolated route, speed, energy, or traffic indicators that do not fully represent voyage context. This study proposes a context-aware framework based on GPS–AIS data fusion, planned-route geofencing, metocean information, and encounter-based validation. The Navigation Efficiency Resilience Index (NERI) combines target achievement, trajectory-derived response activity, and disturbance intensity into a bounded, time-resolved diagnostic index. The framework was evaluated using a Singapore–Montevideo container-ship voyage with 30 s position data, surrounding-vessel AIS, corridor-specific cross-track limits, and collocated metocean variables. The voyage-level mean NERI was 0.679, and its 10th percentile was 0.519. Lower values occurred mainly in constrained waters, approach areas, and the metocean-intensive Cape transition, whereas the Indian Ocean and South Atlantic legs achieved higher mean values of 0.704 and 0.736, respectively. For the analysed datasets, the regular own-ship position record produced more stable trajectory-derived indicators than the less regularly sampled own-ship AIS series, without implying an inherent accuracy advantage. The full NERI formulation achieved an AUROC of 0.83 and an AUPRC of 0.41 for CPA/TCPA conflict-window classification. NERI therefore provides a decomposable, plan-relative analytical layer for retrospective voyage monitoring and diagnostics, but it is not a direct safety or collision-risk measure. Full article