Search Results (1,366)

The accelerating contamination of global ecosystems by heavy metal ions, per- and polyfluoroalkyl substances (PFASs), microplastics and nanoplastics (MNPs), and emerging contaminants demands sensing technologies that are rapid, sensitive, selective, and field-deployable. Quantum dots (QDs) have emerged as leading candidates for environmental sensing; however, their performance is often interpreted empirically rather than through a unified understanding of the underlying excitonic physics. This narrative review presents a mechanistically integrated framework for QD-based environmental sensing, establishing the exciton, the spatially confined electron–hole quasiparticle, as the primary signal carrier in the most analytically powerful QD sensing modalities. A critical distinction is drawn between three categories of signal-generating processes: genuine excitonic transduction (photoinduced electron transfer, trap-state modulation, FRET, charge-transfer exciton formation, and binding energy modulation); non-excitonic optical phenomena, including the inner filter effect and light scattering, which are frequently misattributed as excitonic responses; and partially excitonic processes such as certain electrochemiluminescence pathways. Exciton fundamentals, confinement effects, and the influence of defects, dopants, and surface states are examined across carbon, chalcogenide, perovskite, and III–V QD families. A Defect–Exciton Energy Map is introduced as a rational design tool linking defect characteristics to excitonic response regime and sensing modality. Application of the mechanistic framework to heavy metal ions, PFASs, microplastics, and emerging contaminants demonstrates that sensing performance differences are mechanistically predictable from excitonic parameters rather than being arbitrary outcomes of materials choice. Benchmarking against competing platforms identifies conditions under which QD sensors offer genuine advantages. The roles of density functional theory, molecular dynamics, and machine learning in enabling rational sensor design are assessed. Key challenges, including stability, real-sample validation, standardisation, and toxicity, and future directions, including QD/two-dimensional material heterostructures and circular economy carbon QD platforms, are identified. Full article

The increasing demand for miniaturized, flexible and wearable electronics has accelerated the development of printed electrochemical energy-storage devices capable of combining high performance with scalable and cost-effective manufacturing. Among emerging electrode materials, MXenes have attracted significant attention owing to their exceptional electrical conductivity, hydrophilic surface chemistry, tunable interlayer structure and excellent solution processability, making them particularly suitable for jet printing technologies. In particular, inkjet printing (IJP) and aerosol jet printing (AJP) enable maskless, high-resolution and material-efficient fabrication of micro-scale energy-storage devices while offering excellent compatibility with flexible substrates. This review provides a comprehensive overview of the use of MXene-based inks in jet-printed energy-storage devices, emphasizing the relationships between MXene physicochemical properties, ink formulation, printing processes and electrochemical performance. First, the structural characteristics, synthesis strategies and electrochemical charge-storage mechanisms of MXenes are discussed, together with the rheological, colloidal and stability requirements governing ink printability. The fundamental principles of IJP and AJP are then critically analyzed, highlighting the influence of solvent systems, printability criteria, processing parameters and deposition conditions. Recent advances in jet-printed MXene-based supercapacitors and micro-supercapacitors are comprehensively and critically reviewed, with particular attention to how material design, ink formulation, and printing strategies affect device performance. Battery-related studies, which remain comparatively limited, are discussed as an emerging application area highlighting the broader potential of jet-printed MXenes for electrochemical energy storage. Finally, the major challenges hindering the large-scale implementation of MXene-based printed energy-storage systems, including oxidation stability, restacking, ink shelf life, and manufacturing scalability, are critically discussed. Full article

By introducing BaTiO₃ into conventional hydroxyapatite (HA) bioactive ceramic coatings, a novel HA/BaTiO₃ piezoelectric-hydrophilic bioactive ceramic coating was developed. In this research, four groups of composite coatings with BaTiO₃ contents of 0, 10, 20, and 30 wt.% were comparatively fabricated and investigated, which in situ constructs a bioelectric microenvironment on the titanium surface. This strategy achieves the effective integration of electrical stimulation with bioactive ceramic coatings, resulting in a piezoelectric-hydrophilic bioactive ceramic layer that mimics biomineralization-driven osteogenesis. Experimental results demonstrate that, through laser cladding, BaTiO₃ particles can be embedded within the piezoelectric-hydrophilic bioactive ceramic coating, endowing the coating with mechano-electrical conversion functionality. Microdomain piezoelectric responses were successfully generated on the coating surface, and based on the maximum local piezoelectric response, the optimal BaTiO₃ content was determined to be 20 wt.%, yielding a microdomain piezoelectric coefficient of 712.6 pm/V. Furthermore, the piezoelectric-hydrophilic bioactive ceramic coating exhibits excellent bioactivity. Electrostatic interactions between piezoelectric charges and inorganic ions in physiological fluids facilitate the adsorption of calcium and phosphorus salts onto the coating surface, thereby enhancing surface hydrophilicity. This promotes the infiltration of inorganic ions and water molecules at the material interface, which in turn strengthens bioactivity, accelerates bone integration, and expedites the establishment of a robust osseointegration interface between joint prostheses and host bone. Full article

The accelerated deployment of electric vehicles requires planning tools able to quantify how much charging infrastructure can be integrated into distribution systems without violating operational constraints. This paper proposes a multi-scenario optimization framework for the siting and sizing of electric vehicle charging stations in radial distribution networks. The problem is formulated as a mixed-integer nonlinear programming model in which candidate-station slots, binary siting decisions, integer EV assignments, hourly power-flow constraints, voltage limits, thermal limits, charger power factor, and charging strategy are coordinated. The objective function combines hosting capacity maximization with active energy losses and voltage deviation terms through a scalarized formulation. Unmanaged and managed charging strategies are evaluated under weekday and weekend operating scenarios. Four adaptive population-based optimizers are analyzed under identical computational conditions: particle swarm optimization, a population-based genetic algorithm, JAYA, and the multi-verse optimizer. Monte Carlo random sampling is included separately as a non-adaptive baseline without memory or learning. The methodology is tested on a modified 33-bus distribution system using Colombian demand profiles and line-current limits. The campaign includes 720 cases and 7200 independent runs. In the 720-case stochastic campaign, the largest feasible solution serves 765 EVs, equivalent to 5.508 MW, with a minimum voltage of 0.9084 p.u. and a maximum loading of 99.83%. Statistical validation shows no significant Holm-adjusted pairwise differences among the adaptive algorithms in hosting capacity, while PSO provides the most robust feasibility behavior. Supplementary robustness analyses quantify the influence of candidate-site definition, objective scaling, voltage limits, base charging-power scale, and native-load growth. A complementary deterministic 69-bus assessment under a normalized branch-current envelope preserves the qualitative managed-versus-unmanaged trend, with feasible sequential allocations of 779 and 225 equivalent EV charging units, respectively. The proposed framework provides a reproducible basis for identifying robust EVCS locations, estimating hosting capacity, and quantifying tradeoffs among charging capacity, network losses, voltage performance, and computational effort. Full article

With the growing demand for continuous health assessment and early disease screening, biofluids have attracted increasing attention because they provide molecular information that cannot be obtained from conventional physical signals alone. However, practical biofluid analysis remains constrained by limited sample volumes, unstable wet interfaces, complex fluid transport, and dependence on external power sources. Triboelectric nanogenerators and triboelectric nanosensors offer a promising solution by combining mechanical energy harvesting with direct signal transduction. This review provides a critical overview of the theoretical basis of triboelectric biofluid sensing, including working modes, figures of merit, charge-transfer mechanisms, and the differences between solid–solid and solid–liquid electrification. Material selection, interfacial functionalization, fluid collection, wearable configurations, and multimodal integration are further discussed. Recent applications involving sweat, tears, saliva, urine, interstitial fluid, blood, and wound exudate are summarized to clarify how triboelectric devices function as either power sources or active sensing interfaces. Particular attention is given to their potential in early screening, risk assessment, and auxiliary diagnosis. Current limitations associated with biofouling, charge dissipation, individual variability, biosafety, durability, calibration, and clinical validation are also evaluated. Finally, future directions are proposed to improve analytical reliability and accelerate the translation of self-powered biofluid sensors from laboratory prototypes to clinically meaningful healthcare platforms. Full article

The HB (homeobox) transcription factor family plays important roles in plant growth, development, morphogenesis, and stress responses; however, its involvement in longan (Dimocarpus longan Lour.) fruit energy metabolism remains unclear. In this study, 32 DlHB family members were identified in the longan genome, and their physicochemical properties, phylogenetic relationships, gene structures, conserved motifs, conserved domains, tissue-specific expression patterns, promoter cis-acting elements, and collinearity relationships were systematically analyzed. The DlHB family was classified into four subfamilies, HD-ZIP I–IV, with substantial divergence in structural composition, expression patterns, and putative regulatory features. Our previous work showed that 1.5% chitosan (CTS) treatment improved postharvest longan fruit quality through modulation of energy metabolism, and the corresponding CTS-treatment transcriptome was therefore used here to screen energy-metabolism-associated DlHB candidates. DlHB22 was selected as a representative candidate, and its CTS-responsive expression was independently confirmed by qRT-PCR. Exogenous ATP treatment was then used as an independent physiological validation of the relationship between energy metabolism and postharvest storability; ATP-treated fruit showed reduced deterioration together with higher ATP, ADP, and AMP contents and higher activities of H+-ATPase, Ca²+-ATPase, cytochrome c oxidase (CCO), and succinate dehydrogenase (SDH) at 15 d, although adenylate energy charge (AEC) was lower than in the control. DlHB22 localized predominantly to the nucleus. Heterologous overexpression of DlHB22 in tomato accelerated fruit color transition and ripening progression and altered ATP, ADP, and AMP contents, AEC, and the activities of H+-ATPase, Ca²+-ATPase, CCO, and SDH. Transcriptome analysis of DlHB22-overexpressing tomato fruit revealed broad transcriptional changes in pathways associated with central carbon metabolism, energy metabolism, glutathione metabolism, hormone signaling, and MAPK signaling, and qRT-PCR validation of six representative DEGs was consistent with the RNA-seq trends. Because tomato is climacteric whereas longan is non-climacteric, the heterologous tomato results demonstrate the regulatory potential of DlHB22 but do not establish an identical native ripening pathway in longan. Overall, DlHB22 is best regarded as a candidate transcription factor associated with longan fruit energy metabolism, whose native regulatory mechanism requires direct validation in longan. Full article

Electric vehicles (EVs) are crucial for mitigating greenhouse gas emissions in urban transportation. However, their integration requires efficient charging infrastructure and allocation strategies. In this paper, five heuristic algorithms were developed to allocate EVs to urban charging stations. This allocation process incorporates critical constraints, such as user preferences and charger type compatibility, while respecting station capacities governed by power output rules. The proposed methods include four initial allocation heuristics, ranging from capacity-centric and nearest-neighbor approaches to random assignments, complemented by a local search algorithm for solution refinement. To evaluate these heuristics, an optimization model minimizing station establishment and vehicle travel costs was adapted from the literature. Computational experiments were performed on both synthetic instances and real-world case studies. The results indicate that the developed heuristics, especially when enhanced by local search, deliver high-quality, near-optimal solutions within highly competitive computational times. Consequently, this study offers a scalable decision-support tool for urban planners, demonstrating how the joint optimization of infrastructure costs and user preferences can foster sustainable urban mobility and accelerate EV adoption. Ultimately, these findings offer actionable insights for scaling heterogeneous EV infrastructure, fostering urban sustainability and mitigating transport-related carbon emissions. Full article

Lithium-ion batteries are widely used in electric mobility, renewable energy integration, portable electronics, and renewable–hydrogen hybrid energy systems. Despite significant advances in battery materials and design, long-term degradation remains a major challenge that affects system reliability, efficiency, and economic viability. In renewable–hydrogen hybrid architectures, battery degradation influences not only energy storage performance but also hydrogen production stability, electrolyzer operation, fuel cell utilization, and overall system efficiency. Major degradation mechanisms include solid electrolyte interphase (SEI) growth, electrolyte decomposition, lithium inventory loss, transition-metal dissolution, particle cracking, and structural phase transformations. This review provides a comprehensive assessment of degradation mechanisms affecting lithium-ion battery components and their implications for renewable–hydrogen hybrid systems. Advanced characterization techniques, including in situ and operando X-ray diffraction, electron microscopy, spectroscopy, electrochemical impedance spectroscopy, cyclic voltammetry, and differential capacity analysis, are examined for their ability to reveal chemical, structural, and morphological changes during battery operation. Particular emphasis is placed on the effects of dynamic load variations, partial state-of-charge cycling, temperature fluctuations, and intermittent renewable energy inputs that accelerate degradation in hybrid systems. The review further discusses mitigation strategies such as surface engineering, electrolyte optimization, material doping, thermal management, intelligent energy management systems, predictive maintenance, and machine learning-based prognostics. Key challenges associated with battery–hydrogen integration, including efficiency trade-offs, component ageing, hydrogen production stability, and lifecycle costs, are critically analysed. The adaptability of hybrid systems under varying operating conditions is also explored, highlighting the importance of degradation-aware control strategies, digital twins, and real-time diagnostics. Finally, future research directions are identified, including multiscale characterization, physics-informed machine learning, techno-economic optimization, and life-synergy modelling. These approaches are essential for developing reliable, adaptive, and cost-effective renewable–hydrogen hybrid energy systems capable of supporting long-term decarbonization objectives. Full article

Flooded lead–acid batteries continue to operate in utility-scale battery energy storage systems (BESSs), yet their long-term degradation under grid-frequency regulation remains poorly characterized by field evidence. This paper presents an eight-year, multi-indicator degradation analysis of a flooded Ortsfeste Kupferstreckmetall (OCSM) lead–acid string at the M5BAT hybrid BESS facility (RWTH Aachen University), covering five years of active Frequency Containment Reserve (FCR) operation (2017–2021) followed by three years of low-utilization reserve operation (2022–2025). Four complementary health indicators are derived from a shared one-second-resolution operational dataset: DC internal resistance (DCIR), DC and AC round-trip efficiency, coulombic efficiency, and inverter efficiency. Five years of continuous FCR service produced no statistically detectable degradation across any indicator. In contrast, the transition to prolonged high-state-of-charge, low-throughput standby coincided with a pronounced increase in DCIR and a decline of about 14 percentage points in DC round-trip efficiency (from about 88% in the FCR phase to 74.0% in 2024). Consistent trends across all indicators, together with stable inverter efficiency, attribute the observed deterioration to the electrochemical system rather than the power electronics. These findings indicate that prolonged standby operation, rather than active FCR cycling, coincided with the onset of accelerated aging in this flooded lead–acid string. The published open-access dataset provides a valuable basis for future benchmarking and cross-technology comparisons for stationary battery storage. Full article

Sports e-textiles have emerged as a key component of wearable technology, enabling real-time physiological monitoring and enhanced athletic performance. However, the integration of conventional batteries into sportswear is constrained by their rigidity, weight, limited flexibility, and safety concerns. Textile-integrated supercapacitors have therefore attracted considerable attention as a promising energy storage solution owing to their lightweight design, rapid charge–discharge capability, long cycle life, and excellent mechanical flexibility. This review critically examines recent advances in supercapacitor-based energy storage for sports e-textiles, with emphasis on electrode materials, textile substrates, fabrication and integration strategies, electrochemical performance, and practical applications in sportswear. Particular attention is given to the effects of textile architecture, flexibility, washability, mechanical durability, sweat resistance, and long-term operational stability on device performance. The review also discusses the major challenges limiting commercial adoption, including durability, scalable manufacturing, user comfort, and environmental sustainability. Finally, future research directions are proposed to accelerate the development of high-performance, sustainable, and commercially viable textile energy storage systems for next-generation intelligent sportswear. This review provides a comprehensive reference for researchers, textile engineers, and wearable technology developers working on advanced energy storage solutions for smart sports apparel. Full article

Flocculation is a physicochemical process with critical relevance to industrial and environmental operations, including potable water production, wastewater remediation, mineral processing, papermaking, and food manufacturing. The efficiency of flocculation is determined by the chemical nature, molecular structure, and physicochemical interactions of flocculants with suspended colloidal matter. Conventional synthetic polyacrylamides, available in nonionic, anionic, and cationic forms, function predominantly via electrostatic neutralization, polymer chain bridging, and sweep flocculation induced by precipitated hydroxides. Their high molecular weight, customizable charge density, and cost-effectiveness have consolidated their industrial dominance. However, the inherent resistance of polyacrylamides to biodegradation in combination with its monomer’s toxicity and increasing regulatory pressure have accelerated research toward sustainable alternative materials. Recent developments include functionalized natural polysaccharides (e.g., chitosan, cellulose derivatives, starch esters), bio-based copolymers, and nanoengineered hybrid systems incorporating inorganic domains to enhance colloid destabilization and sedimentation kinetics. This review systematically examines the physicochemical principles underlying flocculation, evaluates the performance parameters and limitations of polyacrylamides, and highlight emerging strategies for sustainable flocculant design. Prospects for the next generation of flocculation technologies are discussed in the context of mechanistic optimization, ecological safety, and compliance with evolving environmental regulations. Full article

Artificial intelligence (AI) is transforming lithium-ion battery (LIB) research by linking heterogeneous data, predictive modeling, mechanistic interpretation, and experimental validation within a closed-loop paradigm. AI does not uniquely enable nonlinear representation; rather, it complements electrochemical, statistical, and control models by learning high-dimensional relationships among composition, structure, processing, interfacial chemistry, operating history, and performance. This review critically examines three connected domains: AI-assisted materials discovery, battery state prediction, and trustworthy intelligent management. To distinguish this contribution from recent topic-specific surveys, we organize methods along four complementary axes—model architecture, learning strategy, physics integration, and deployment strategy—and compare landmark studies using quantitative evidence such as independent cell count, validation design, reported error, experimental budget, and closed-loop acceleration. Materials applications include cathodes, anodes, liquid and solid electrolytes, and electrode-electrolyte interphases; operational applications include state of charge, state of health, remaining useful life, degradation diagnosis, safety warning, and digital twin-enabled management. The critical synthesis identifies data leakage, inconsistent metadata, domain shift, uncalibrated uncertainty, black-box reasoning, computational constraints, and limited external validation as recurring barriers. Future progress will depend less on model complexity alone than on FAIR data, cell-independent evaluation, physics-informed learning, uncertainty-aware decisions, autonomous experimentation, human oversight, and deployment-aware design. These elements define an evidence chain for moving LIB AI from proof-of-concept prediction toward reproducible, closed-loop, and trustworthy battery innovation. Full article

The use of Mg-based alloys as anode materials in nickel–metal hydride (Ni–MH) batteries is significantly limited by rapid capacity loss during charge–discharge cycles. This study conducts a comprehensive examination of how variations in the concentrations of Mg and Pd impact the microstructural characteristics and electrochemical behavior of Mg–Pd–Ni ternary alloys, aiming to enhance cyclic durability and uncover the fundamental degradation mechanisms. This work demonstrates that increasing the Mg content tends to reduce the reversibility of electrochemical hydrogenation/dehydrogenation reactions and exacerbates the corrosion behavior of the milled Mg–Pd–Ni alloy electrodes, thus accelerating their capacity decay. On the contrary, raising the Pd content contributes to improving the reversibility of electrochemical hydrogenation/dehydrogenation reactions and the kinetic behavior of the alloys, yet it does not enhance corrosion resistance. Full article

Non-radiative carrier loss originating from material defects together with slow charge migration act as two major limiting factors heavily suppressing the power output performance of organic bulk-heterojunction (BHJ) photovoltaic devices (OSCs). Herein, two-dimensional (2D) CdSe nanoplatelets (NPLs) are introduced into conventional P3HT:PCBM and high-efficiency PBDB-T:PCBM photoactive films as multi-purpose doping additives, aiming to finely tune film microstructures, refine interfacial energy level matching, accelerate carrier migration, and eliminate native trap sites inside the active layer. Statistical measurement data verify that 3 mg CdSe NPLs as the ideal doping dosage can realize concurrent performance upgrades for the two distinct OSC architectures investigated here. As for devices built on P3HT:PCBM blend films, the component modified with optimized CdSe NPL additives delivers boosted charge mobility rising from 0.87 × 10⁻⁵ cm²/V·s up to 2.58 × 10⁻⁵ cm²/V·s. Meanwhile, trap site concentration drops markedly from 7.41 × 10¹⁵ cm⁻³ to 4.33 × 10¹⁵ cm⁻³, which lifts the device power conversion efficiency (PCE) from 2.77% to 3.15%. Even more noticeable improvements are observed in PBDB-T:PCBM photovoltaic units; the refined doping recipe raises carrier mobility from 5.42 × 10⁻⁴ cm²/V·s to 8.69 × 10⁻⁴ cm²/V·s and cuts trap density down from 7.13 × 10¹⁶ cm⁻³ to 3.15 × 10¹⁶ cm⁻³, thus bringing about a substantial PCE boost ranging from 6.52% to 9.14%. The present study confirms the bifunctional advantages possessed by 2D CdSe NPLs, which can adjust BHJ microphase separation and electronic characteristics simultaneously. This research offers a simple and broadly applicable route to fabricate organic photovoltaic cells with superior efficiency. Full article

Hierarchical titanium dioxide (TiO₂) has emerged as a promising photocatalytic material owing to its excellent chemical stability, environmental benignity, low cost, and high density of surface-active sites. Nevertheless, its practical application is constrained by rapid photogenerated charge-carrier recombination and poor visible-light utilization resulting from its wide bandgap. In the present study, a hierarchical TiO₂/CdS quantum dot (QD) nanocomposite was engineered through a facile and cost-effective pseudo-successive ionic layer adsorption and reaction (p-SILAR) technique with controlled CdS QD deposition. The structural, morphological, optical, and electrochemical properties of the synthesized photocatalysts were systematically investigated using SEM, TEM, XRD, XPS, UV-Vis spectroscopy, photoluminescence (PL), and electrochemical impedance spectroscopy (EIS). The results confirmed the successful deposition of highly dispersed CdS QDs onto the hierarchical TiO₂ framework without altering its morphology or crystal structure. The formation of the heterojunction significantly enhanced visible-light absorption and reduced the optical bandgap from 3.19 eV for pristine TiO₂ to 2.37 eV for the TiO₂/CdS QD nanocomposite. Furthermore, PL and EIS analyses demonstrated suppressed electron–hole recombination and improved interfacial charge-transfer characteristics, respectively. Owing to these synergistic effects, the optimized TiO₂/CdS QD photocatalyst achieved 85.3% degradation of methylene blue under visible-light irradiation within 120 min, exhibiting substantially superior performance to pristine hierarchical TiO₂. Radical scavenging experiments revealed that superoxide radicals ^●O₂⁻ and photogenerated holes (h⁺) were the dominant reactive species governing the degradation process. The enhanced photocatalytic activity is attributed to the combined effects of efficient visible-light harvesting, accelerated charge separation, and effective interfacial charge migration across the TiO₂/CdS QD nanocomposite. These findings highlight the potential of hierarchically structured TiO₂/CdS QD nanocomposites as efficient and economically viable photocatalysts for environmental remediation and wastewater treatment applications. Full article