Search Results (4,050)

Solar-driven hydrogen production via photocatalytic water splitting represents a promising route toward sustainable and low-carbon energy systems. Among emerging photocatalysts, porphyrin-based framework materials, specifically porphyrinic metal–organic frameworks (PMOFs) and porphyrinic covalent organic frameworks (PCOFs), have attracted increasing attention owing to their strong visible-light absorption, tunable electronic structures, permanent porosity, and well-defined catalytic architectures. In these systems, porphyrins function as versatile photosensitizers whose photophysical properties can be precisely tailored through metalation, peripheral functionalization, and integration into ordered frameworks. This review provides a comprehensive, design-oriented overview of recent advances in PMOFs, PCOFs, and hybrid porphyrinic architectures for photocatalytic H₂ evolution. We discuss key structure–activity relationships governing light harvesting, charge separation, and hydrogen evolution kinetics, with particular emphasis on the roles of porphyrin metal centers, secondary building units, linker functionalization, framework morphology, and cocatalyst integration. Furthermore, we highlight how heterojunction engineering through coupling porphyrinic frameworks with inorganic semiconductors, metal sulfides, or single-atom catalytic sites can overcome intrinsic limitations related to charge recombination and limited spectral response. Current challenges, including long-term stability, reliance on noble metals, and scalability, are critically assessed. Finally, future perspectives are outlined, emphasizing rational molecular design, earth-abundant catalytic motifs, advanced hybrid architectures, and data-driven approaches as key directions for translating porphyrinic frameworks into practical photocatalytic hydrogen-generation technologies. Full article

Based upon density functional theory (DFT) calculations, we present the basic electronic structure of CuPb₉(PO₄)₆O (Cu-doped lead apatite, aka LK-99), in two scenarios: (1) where the structure is constrained to the P3 symmetry and (2) where no symmetry is imposed. At the DFT level, the former is predicted to be metallic while the latter is found to be a charge-transfer insulator. In both cases the filling of these states is nominally $d^9$, consistent with the standard Cu²⁺ valence state, and Cu with a local magnetic moment of order 0.7 μ_B. In the metallic case we find these states to be unusually flat (∼0.2 eV dispersion), giving a very high density of electronic states (DOS) at the Fermi level that we argue can be a host for novel electronic physics. The flatness of the bands is the likely origin of symmetry-lowering gapping possibilities that would remove the spectral weight from $E_F$. Motivated by some initial experimental observations of metallic or semiconducting behavior, we propose that disorder (likely structural) is responsible for closing the gap. Here, we consider a variety of possibilities that could possibly close the charge-transfer gap but limit consideration to kinds of disorder that preserve electron count. Of the possible kinds we considered (spin disorder, O populating vacancy sites, and Cu on less energetically favorable Pb sites), the local Cu moment, and consequently the charge-transfer gap, remains robust. We conclude that disorder responsible for metallic behavior entails some kind of doping where the electron count changes. Further, we claim that the emergence of the flat bands should be due to weak wave function overlap between the orbitals on Cu and O sites, owing to the directional character of the constituent orbitals. Therefore, finding an appropriate host structure for minimizing hybridization between Cu and O while allowing them to still weakly interact should be a promising route for generating flat bands at $E_F$ which can lead to interesting electronic phenomena, regardless of whether LK-99 is a superconductor. Full article

The electric vehicles (EVs) market keeps growing globally; thus, it is critical to secure the EV charging communication protocols in order to guarantee reliable and fair charging operations among the customers. The Open Charge Point Protocol (OCPP) 2.0.1 supports the communication between the Electric Vehicle Supply Equipment (EVSE) and Charging Station Management Systems (CSMSs); therefore, it becomes vulnerable to several types of attacks, which aim to jeopardize smart charging, billing, and energy management. Specifically, OCPP 2.0.1 allows the self-reporting of the State of Charge (SOC) values, which makes it vulnerable to spoofing-based cyberattacks, which target manipulating the scheduling priorities, distorting the load forecasts, and extending the charging sessions in an unfair manner. In this paper, we try to address this type of attack by providing a comprehensive analysis of the SOC spoofing attacks and introducing a novel unsupervised detection framework based on the One-Class Support Vector Machine (OCSVM) algorithm. Specifically, two types of attack scenarios are analyzed (i.e., priority manipulation and session extension) by deriving engineered features that capture the nonlinear relationships under normal charging behavior. Detailed simulation-based results are derived by utilizing the DESL-EPFL Level 3 EV charging dataset. Our results demonstrate high F1-score and recall in identifying spoofed SOC values and that the proposed OCSVM model demonstrates superior performance compared to alternative clustering and deep-learning based detectors. Full article

Developing efficient heterojunction photocatalysts is essential to address the challenge of degrading persistent organic pollutants. In this study, a multi-scale characterization strategy was employed to investigate the implications of interfacial connectivity between synthesized graphitic carbon nitride (g-C₃N₄) /bismuth oxychloride (BiOCl)e removal of Rhodamine B (RhB) and Methyl Orange (MO). Morpho-structural characterizations, including Scanning/Transmission Electron Microscopy (SEM/TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and N₂ physisorption (Brunauer–Emmett–Teller (BET)) analyses, confirmed the successful construction of an intimate interfacial contact between g-C₃N₄ and BiOCl. The optimized composite (15% g-C₃N₄/BiOCl), prepared via a one-step hydrothermal method, exhibited enhanced photocatalytic performance following pseudo-first-order kinetics described by the Langmuir–Hinshelwood model, with apparent rate constants of 0.166 min⁻¹ for MO and 0.519 min⁻¹ for RhB. Under visible-light irradiation, degradation efficiencies of 98% for MO (120 min) and 99% for RhB (35 min) were achieved, outperforming the pristine components. Complementary optical and electrochemical analyses indicate improved light absorption and charge-separation efficiency in the heterojunction system. In addition, the photocatalyst demonstrated good operational stability over four consecutive cycles, maintaining 91.70% activity for MO and 99.76% for RhB. Overall, this work highlights the synergistic photocatalytic g-C₃N₄/BiOCl heterojunction and provides a valuable insight to guide the design of advanced materials for pollutant remediation. Full article

In this study, we have investigated heterostructural TiO₂/BiVO₄ anodes to determine the effect of the amount and form of BiVO₄ nanoparticles on TiO₂ on the response of photoanodes under UV and visible illumination. BiVO₄ nanopowders were prepared and annealed at temperatures ranging from 200 to 500 °C. Structural and optical characterization indicates that as the annealing temperature is increased, a phase transition from a weakly ordered to a dominant monoclinic BiVO₄ phase is observed, which is accompanied by an increase in visible light absorption. Subsequently, the most crystalline powder was utilized to deposit BiVO₄ on nanostructured TiO₂ either as a compact overlayer (drop-casting) or as a progressively grown nanoparticle (TiO₂@S series) in the successive ionic layer adsorption and reaction process (SILAR). Photoelectrochemical measurements were performed, revealing a morphology-dependent photocurrent response under UV and visible illumination. A further increase in the number of cycles systematically increases the photocurrent in the visible light range while limiting the response to UV radiation. The TiO₂@d photoanode demonstrates the highest relative activity within the visible range; however, it also generates the lowest absolute photocurrent, indicating the presence of significant transport and recombination losses within the thick BiVO₄ layer. The results demonstrate that the presence of BiVO₄ nanoparticles on TiO₂ exerts a substantial influence on the separation of charge between semiconductors and the synergistic utilization of photons from the UV and visible ranges. This research yielded a proposed scheme of mutual band arrangement and charge carrier transfer mechanism in TiO₂@BiVO₄ heterostructures. Full article

Polyaniline (PANI), characterized by its proton-coupled redox mechanism and multicolor reversibility, is widely investigated for adaptive optical interfaces. Compared to inorganic oxides, PANI offers advantages in cost-effectiveness, mechanical flexibility, and molecular tunability; however, its practical implementation faces challenges related to kinetic limitations and environmental instability. This review presents a comprehensive analysis of PANI-based electrochromic materials, examining the intrinsic correlations among synthesis methodologies, microstructural characteristics, and optoelectronic performance. Synthesis strategies, including chemical oxidative polymerization, electrochemical deposition, and template-assisted techniques, are evaluated. Emphasis is placed on resolving the trade-off between optical contrast and switching kinetics by constructing high-surface-area porous nanostructures and inducing chain ordering via functional dopants to shorten ion diffusion paths and reduce charge transfer resistance. Fundamental electrochromic properties are subsequently discussed, with specific attention to degradation mechanisms triggered by environmental factors, such as pH drift, and stabilization strategies involving electrolyte engineering and composite design. Furthermore, the review addresses the evolution of applications from single-band monochromatic displays to dual-band smart windows for decoupled visible/near-infrared regulation and multifunctional integrated systems, including electrochromic supercapacitors and adaptive thermal management textiles. Finally, technical challenges regarding long-term durability, neutral color development, and large-area manufacturing are summarized to outline future research directions for PANI-based optical systems. Full article

This paper presents the design and fabrication of a triboelectric nanogenerator based on a Quadruple Parallel-cavity Helmholtz Resonator (4C–HR TENG) for the efficient harvesting of noise energy in marine engine room environments. The device utilizes sound waves to drive periodic contact and separation between polytetrafluoroethylene (PTFE) particles in the resonant cavity and the vibrating diaphragm as well as the upper electrode plate, thereby converting sound energy into mechanical energy and finally into electrical energy. The device consists of an acoustic waveguide with a length of 350 mm and both width and height of 60 mm, along with a Helmholtz Resonator with a diameter of 60 mm and a height of 40 mm. Experimental results indicate that under resonance conditions with a sound pressure level of 109.8 dB and a frequency of 110 Hz, the device demonstrates excellent output performance, achieving a peak output voltage of 250 V and a current of 4.85 μA. We analyzed and investigated the influence mechanism of key parameters (filling ratio, sound pressure level, the height between the electrode plates, and particle size) on the output performance. Through COMSOL Multiphysics simulation analysis, the sound pressure enhancement effect and the characteristic of concentrated diaphragm center displacement at the first-order resonance frequency were revealed, verifying the advantage of the four-cavity structure in terms of energy distribution uniformity. In practical applications, the minimum responsive sound pressure level corresponding to the operating frequency range of the 4C–HR TENG was determined. The output power reaches a maximum of 0.27 mW at a load resistance of 50 MΩ. At a sound pressure level of 115.1 dB, the device can charge a 1 μF capacitor to 4.73 V in just 32 s and simultaneously illuminate 180 LEDs in real-time, demonstrating its potential for environmental noise energy harvesting and micro-energy supply applications. This study provides new insights and experimental evidence for the efficient recovery of noise energy. Full article

Ions in liquid helium exist in their simplest form in two configurations, as negatively charged “electron bubbles” (electrons in a void of about 35 Å in diameter) and as positive “snowballs” (He⁺ ions surrounded by a sphere of solid helium, about 14 Å in diameter). Here, we give an overview of studies with these ions when they are trapped at interfaces between different helium phases, i.e., the “free” surface between liquid and vapor, but also the interfaces between liquid and solid helium at high pressure and between phase-separated ³He-⁴He mixtures below the tricritical point. Three cases are discussed: (i) if the energy barrier provided by the interface is of the order of the thermal energy k_BT, the ions can pass from one phase to the other with characteristic trapping times at the interface, which are in qualitative agreement with the existing theories; (ii) if the energy barrier is sufficiently high, the ions are trapped at the interface for extended periods of time, forming 2D Coulomb systems with intriguing properties; and (iii) at high electric fields and high ion densities, an electrohydrodynamic instability takes place, which is a model for critical phenomena. Full article

With the widespread adoption of electric vehicles, commercial charging stations (CCS) have grown rapidly as a core component of charging infrastructure. Due to the concentrated and high-power charging load characteristics of CCS, a ‘peak on peak’ phenomenon can occur in the power distribution network. Demand response (DR) serves as an important and flexible regulation tool for power systems, offering a new approach to addressing this issue. However, when CCS participates in DR, it faces a dual dilemma between operational revenue and user satisfaction. To address this, this paper proposes a bi-level, multi-objective framework that co-optimizes station profit and nonlinear user satisfaction. An asymmetric sigmoid mapping is used to capture threshold effects and diminishing marginal utility. Uncertainty in users’ charging behaviors is evaluated using a Monte Carlo scenario simulation together with chance constraints enforced at a 0.95 confidence level. The model is solved using the fast non-dominated sorting genetic algorithm, NSGA-II, and the compromise optimal solution is identified via the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Case studies show robust peak shaving with a 6.6 percent reduction in the daily maximum load, high satisfaction with a mean of around 0.96, and higher revenue with an improvement of about 12.4 percent over the baseline. Full article

The emerging urbanization and the extensive increase of the transportation sector are responsible for the significant increase in carbon dioxide emissions. Therefore, replacing traditional cars with Electric Vehicles (EVs) is a promising solution, offering a clearer alternative. EVs are becoming more and more well-known and are being quickly used worldwide. However, the exponential rise in EV sales has also raised a number of issues, which are becoming important and demanding. These challenges include the need of driving security, the battery degradation, the inadequate infrastructure for charging EVs, and the uneven energy distribution. In order for EVs to reach their full potential, intelligent systems and innovative technologies need to be introduced in the field of EVs. This is where business intelligence (BI) can be employed, along with artificial intelligence (AI), data analytics, and machine learning. In this paper, we provide a comprehensive survey on the use of BI strategies in the EV transportation sector. We first introduce the EVs and charging station technologies. Then, research works on the application of BI and data analysis techniques in EV technology are reviewed to further understand the challenges and open issues for the research and industry community. Moreover, related works on accident analysis, battery health prediction, charging station analysis, intelligent infrastructure, locating charging stations analysis, and autonomous driving are investigated. This survey systematically reviews 75 peer-reviewed studies published between 2020 and 2025. Finally, we discuss the fundamental limitations and the future open challenges in the aforementioned topics. Full article

Starch systems and their extrudates can be used as edible films, carriers, and encapsulants for bioactive substances in various industries, primarily the food, medicine, and pharmacy industries. Using appropriate modification methods, it is possible to alter their physicochemical properties to improve specific functional parameters, thereby enhancing their application potential. The aim of this study was to characterize potato starch extrudates enriched with two types of edible oils (rapeseed or sunflower) at concentrations of 3%, 6%, and 9%. Chemical modification was carried out using K₂CO₃ as a catalyst. The structure of native and modified starch extrudates was examined using optical/confocal microscopy, FTIR, and LTNA (low-temperature nitrogen adsorption). Analogous starch dispersions were studied using static and dynamic light scattering, SLS/DLS, nephelometric methods, and electrophoretic mobility measurements to determine surface charge levels and stability. Additionally, viscosity curves were determined as a function of time and temperature. It was found that starch extrudates with 6% sunflower oil content showed optimal functional properties, characterized by greater stability, higher structural order, and better oil complexation. These findings directly translate into significant potential applications, including the development of functional products in the food industry. Full article

Calculating the pH values of carbonic acid solutions is an important task in studies of chemical equilibria in freshwater systems, with applications to environmental chemistry, geology, and hydrology. These pH values are also highly relevant in the context of climate change, since increasing atmospheric CO₂ affects the concentration of dissolved carbon dioxide and carbonic acid, collectively denoted as [H₂CO₃*] = [H₂CO_3(aq)] + [CO_2(aq)]. Solving equilibrium systems to obtain analytical functions is particularly useful when such functions are required, for example, in data fitting. We show here that, although exact or near-exact solutions typically result in third- to fourth-order equations that must be solved numerically, reasonable approximations can be derived that lead to analytical second-order equations. In this framework, the chosen approximations need to meet the boundary conditions of the systems, particularly for c_T → 0 and for high c_T values (where c_T = [H₂CO₃*] + [HCO₃⁻] + [CO₃²⁻]). Finally, we provide exact solutions for a closed system containing both H₂CO₃* and alkalinity, which enables the description of virtually any aquatic environment without assuming equilibrium with atmospheric CO₂. Implications for pH calculations in natural waters are also briefly discussed. Full article

Modulating the electronic structure and surface properties of graphitic carbon nitride (g-C₃N₄) by chemically phosphorus doping is an effective strategy for improving its photocatalytic performance. However, in order to benefit from practical applications, the cost-effectiveness, efficiency, and optimization of the doping level need to be investigated further. Herein, we report a structural doping of P into g-C₃N₄ by in situ polymerization of the mixture of dicyandiamide (DCDA) and phosphorus pentoxide (P₂O₅). As an alternative to previous studies that used complex organic phosphorus precursors or post-treatment strategies, this work proposed a one-pot thermal polycondensation method that is low-cost, scalable, and enables controlled phosphorus substitutions at carbon sites of the g-C₃N₄ heptazine structure. Most of the structural features of g-C₃N₄ were well retained after doping, but the electronic structures and light harvesting capacity had been effectively altered, which provided not only a much better charge separation but also an improvement in photocatalytic activity toward H₂ evolution under irradiation of a simulated sunlight. The optimized sample with P-doping content of 9.35 at.% (0.5PGCN) exhibited an excellent photocatalytic performance toward H₂ evolution, which is over 5 times higher than that of bulk g-C₃N₄. This work demonstrates a facile one-step in situ route for producing high-yield photocatalysts using low-cost commercial precursors, offering practical starting materials for studies in solar cells, polymer batteries, and photocatalytic applications. Full article

Under China’s “dual-carbon” strategic goals and the advancement of smart city development, the rapid adoption of electric vehicles (EVs) has deepened the spatiotemporal coupling between transportation networks and distribution grids, posing new challenges for integrated energy systems. To address this, we propose a collaborative optimization framework for power–transportation coupled networks that integrates multi-modal data with physical priors. The framework constructs a joint feature space from traffic flow, pedestrian density, charging behavior, and grid operating states, and employs hypergraph modeling—guided by power flow balance and traffic flow conservation principles—to capture high-order cross-domain coupling. For prediction, spatiotemporal graph convolution combined with physics-informed attention significantly improves the accuracy of EV charging load forecasting. For optimization, a hierarchical multi-agent strategy integrating federated learning and the Alternating Direction Method of Multipliers (ADMM) enables privacy-preserving, distributed charging load scheduling. Case studies conducted on a 69-node distribution network using real traffic and charging data demonstrate that the proposed method reduces the grid’s peak–valley difference by 20.16%, reduces system operating costs by approximately 25%, and outperforms mainstream baseline models in prediction accuracy, algorithm convergence speed, and long-term operational stability. This work provides a practical and scalable technical pathway for the deep integration of energy and transportation systems in future smart cities. Full article

Nowadays, the automotive industry is primarily driven by the CO₂ policy that targets net zero carbon emissions by 2035 from passenger cars and commercial vehicles. The main path to achieve this goal is the implementation of electric powertrains with the energy stored in batteries, as the case for battery electric vehicles (BEV). However, this technology still faces some difficulties in terms of energy density, overall weight, charging time, and vehicle autonomy. From the other point of view, fuel cell electric vehicles (FCEV) offer the same advantages as BEV in terms of CO₂ reduction, providing better autonomy and lower refueling time. The energy demand by the electric powertrain strongly depends on the vehicle driving conditions as it directly affects energy consumption. In that context, the article aims to study the electrical energy demand of an ultra-energy efficient vehicle intended for a Shell eco-marathon competition in order to minimize hydrogen consumption. The study was carried out over a single lap on the racing track in Nogaro, France while applying the race rules from the competition in 2023. It includes a numerical evaluation of the vehicle resistance forces in different driving strategies and experimental validation on the propulsion test bench. Full article