Search Results (167)

The electrochemical performance of Li-ion batteries employing LiFePO₄ (LFP) cathodes supported by bio-sourced activated carbon derived from millet cob (MC) and water hyacinth (WH) were systematically investigated. Carbon activation was carried out using potassium hydroxide (KOH) at varying mass ratios of KOH to precursor material: 1:1, 2:1, and 5:1 for both WH and MC-derived carbon. The physical properties (X-ray diffraction patterns, BET surface area, micropore and mesopore volume, conductivity, etc.) and electrochemical performance (specific capacity, discharge at various current rates, electrochemical impedance measurement, etc.) were determined. Material characterization revealed that the activated carbon derived from MC exhibits an amorphous structure, whereas that obtained from WH is predominantly crystalline. High specific surface areas were achieved with activated carbons synthesized using a low KOH-to-carbon mass ratio (1:1), reaching 413.03 m²·g⁻¹ for WH and 216.34 m²·g⁻¹ for MC. However, larger average pore diameters were observed at higher activation ratios (5:1), measuring 8.38 nm for KOH/WH and 5.28 nm for KOH/MC. For both biomass-derived carbons, optimal electrical conductivity was obtained at a 2:1 activation ratio, with values of 14.7 × 10⁻³ S·cm⁻¹ for KOH/WH and 8.42 × 10⁻³ S·cm⁻¹ for KOH/MC. The electrochemical performance of coin cells based on cathodes composed of 85% LiFePO₄, 8% of these activated carbons, and 7% polyvinylidene fluoride (PVDF) as a binder, with lithium metal as the anode were studied. The LiFePO₄/C (LFP/C) cathodes exhibited specific capacities of up to 160 mAh·g⁻¹ at a current rate of C/12 and 110 mAh·g⁻¹ at 5C. Both LFP/MC and LFP/WH cathodes exhibit optimal energy density at specific values of pore size, pore volume, charge transfer resistance (R_ct), and diffusion coefficient (D_Li), reflecting a favorable balance between ionic transport, accessible surface area, and charge conduction. Maximum energy densities relative to active mass were recorded at 544 mWh·g⁻¹ for LFP/MC 2:1, 554 mWh·g⁻¹ for LFP/WH 2:1, and 568 mWh·g⁻¹ for the reference LFP/graphite system. These performance results demonstrate that the development of high-performing bio-sourced activated carbon depends on the optimization of various parameters, including chemical composition, specific surface area, pore volume and size distribution, as well as electrical conductivity. Full article

Earthquakes remain among the most destructive natural hazards, causing severe loss of life and property in seismically active regions such as Nepal. Major events such as the 1934 Nepal–Bihar earthquake (M_w 8.2), the 2015 Gorkha earthquake (M_w 7.8), and the 2023 Jajarkot earthquake (M_L 6.4) have repeatedly exposed the vulnerability of Nepal’s built environment. In response, the Ready-to-Use Detailing (RUD) guideline (NBC 205:2024) was introduced to provide standardized structural detailing for low-rise reinforced concrete buildings without masonry infill, particularly for use in areas where access to professional engineering services is limited. This study was motivated by the need to critically assess the structural performance of buildings designed according to such rule-of-thumb detailing, which is widely applied through owner–builder practices. Nonlinear pushover analyses were carried out using finite element modelling for typical configurations on soil types C and D, under peak ground accelerations of 0.25 g, 0.30 g, 0.35 g, and 0.40 g. The response spectrum from NBC 105:2020 was adopted to determine performance points. The analysis focused on global response, capacity curves, storey drift, and hinge formation to evaluate structural resilience. The maximum story drift for the linear static analysis is found to be 0.56% and 0.86% for peak ground acceleration of 0.40 g, for both three and four-storied buildings. Also, from non-linear static analysis, it is found that almost all hinges formed in the beams and columns are in the Immediate Occupancy (IO) level. The findings suggest that the RUD guidelines are capable of providing adequate seismic performance for low-rise reinforced concrete buildings, given that the recommended material quality and construction standards are satisfied. Full article

Rammed earth (RE) dwellings are characterized by accessible materials, low cost, and environmental sustainability. However, their poor seismic resistance limits their application. To address this issue, three conventional technical approaches have been developed: (1) adding cement to improve strength; (2) improving structural integrity using reinforced concrete ring beams and columns; and (3) embedding vertical steel bars in order to provide resistance against horizontal seismic actions. While effective, these methods rely on energy-intensive materials with high carbon emissions. In this study, we analyze the seismic damage characteristics and construction mechanisms of RE walls. The results reveal that the horizontal joints in RE walls significantly weaken their resistance to horizontal seismic actions. To mitigate this, three types of undulating joints are proposed and six specimens tested. The maximum horizontal loads of the specimens with local subsidence-type joints are 132.44 kN and 135.41 kN, respectively, which are approximately 50% higher than specimens with horizontal joints, whose maximum horizontal loads are 80.7 kN and 85.83 kN, respectively, while the maximum horizontal loads of the specimens with horizontally concatenated gentle arc-type joints are 151.17 kN and 173.58 kN, respectively, and they exhibit nearly double the shear capacity of the specimens with horizontal joints. Building on these findings and test results, we also include recommendations for integrating elegant RE wall texture design with seismic-resistant undulating joint technology. Full article

To address the conflicts between high-penetration distributed photovoltaics (PV) integration causing voltage limit violations, reverse power flow issues, and the grid connection needs of industrial and commercial users, this paper proposes an optimal capacity planning method for distributed PV considering the user’s grid connection locations. This method effectively increases the acceptance capacity of the distribution transformer network for distributed PV while ensuring the safe and stable operation of the distribution network. First, the source–load uncertainty is considered, and the k-means clustering algorithm is used to select multiple typical daily probability scenarios. Then, the PV optimal connection node range is obtained through a PV site selection and sizing model. For the planning of nodes within the optimal range, an optimal capacity planning model focusing on the economic benefits of users is established. This model aims to optimize the improvement of wheeling cost and maximize the economic benefits of grid-connected users by determining the optimal PV access capacity for each node. Finally, for PV users outside this range, after determining the maximum allowable capacity for each node, the capacity margin and static voltage stability are comprehensively considered to evaluate the network access scheme. Simulation examples are used to verify the effectiveness of the proposed method, and the simulation results show that the proposed method can effectively increase the acceptance capacity of the distribution network for photovoltaic systems. By fully considering the wheeling cost collection strategy, the distributed PV acceptance capacity is increased by 20.14%, while both user benefits and the operational safety and economic performance of the distribution network are significantly improved, ultimately resulting in a 27.77% increase in total revenue. Full article

A metal-ion-free method was developed to prepare κ-carrageenan/cellulose hydrogel beads for efficient cationic dye removal. The beads were fabricated using a mixture of 1-ethyl-3-methylimidazolium acetate and N,N-dimethylformamide as the solvent system, followed by aqueous ethanol-induced phase separation. This process eliminated the need for metal-ion crosslinkers, which typically neutralize anionic sulfate groups in κ-carrageenan, thereby preserving a high density of accessible binding sites. The resulting beads formed robust interpenetrating polymer networks. The initial swelling ratio reached up to 28.3 g/g, and even after drying, the adsorption capacity remained over 50% of the original. The maximum adsorption capacity for crystal violet was 241 mg/g, increasing proportionally with κ-carrageenan content due to the higher surface concentration of anionic sulfate groups. Kinetic and isotherm analyses revealed pseudo-second-order and Langmuir-type monolayer adsorption, respectively, while thermodynamic parameters indicated that the process was spontaneous and exothermic. The beads retained structural integrity and adsorption performance across pH 3–9 and maintained over 90% of their capacity after five reuse cycles. These findings demonstrate that κ-carrageenan/cellulose hydrogel beads prepared via a metal-ion-free strategy offer a sustainable and effective platform for cationic dye removal from wastewater, with potential for heavy metal ion adsorption. Full article

This work focuses on the effectiveness of removing ammonium from real municipal wastewater using synthetic faujasite (FAU-type) and β (BEA-type) zeolites and a commercial β (BEA-type) sample. The results demonstrated that synthetic samples presented enhanced performance on ammonium removal in comparison with commercial zeolite due to higher Al content and larger specific surface area, promoting better accessibility to active adsorption sites of the adsorbents. Synthetic FAU-type and BEA-type zeolites achieved a maximum adsorption capacity of 28.87 and 12.62 mg·g⁻¹, respectively, outperforming commercial BEA-type zeolite (6.50 mg·g⁻¹). Adsorption assays, associated with kinetic studies and adsorption isotherms, were better fitted using the pseudo-second order model and the Langmuir model, respectively, suggesting that chemisorption, involving ion exchange, and monolayer formation at the zeolite surface, was the main mechanism involved in the NH₄⁺ adsorption process. After ammonium adsorption, the NH₄⁺-loaded zeolite samples were used to stimulate the growth of tomato seedlings; the results revealed a change in the biomass production for seedlings grown in vitro, especially when the BEA_C_NH₄ sample was employed, leading to a 15% increase in the fresh mass in comparison with the control sample. In contrast, the excess of ammonium adsorbed over the BEA_S_NH₄ and FAU_NH₄ samples probably caused a toxic effect on seedling growth. The elemental analysis results supported the hypothesis that the presence of NH₄⁺-loaded zeolite into the culture medium was important for the release of nitrogen. The obtained results show then that the investigated zeolites are promising both as efficient adsorbents to mitigate the environmental impact of ammonium-contaminated water bodies and as nitrogen-rich fertilizers. Full article

Biochar serves as an effective adsorbent for the heavy metal cadmium, with its performance significantly influenced by its physicochemical properties and various environmental features. Traditional machine learning models, though adept at managing complex multi-feature relationships, rely heavily on expertise in feature engineering and hyperparameter optimization. To address these issues, this study employs an automated machine learning (AutoML) approach, automating feature selection and model optimization, coupled with an intuitive online graphical user interface, enhancing accessibility and generalizability. Comparative analysis of four AutoML frameworks (TPOT, FLAML, AutoGluon, H₂O AutoML) demonstrated that H₂O AutoML achieved the highest prediction accuracy (R² = 0.918). Key features influencing adsorption performance were identified as initial cadmium concentration (23%), stirring rate (14.7%), and the biochar H/C ratio (9.7%). Additionally, the maximum adsorption capacity of the biochar was determined to be 105 mg/g. Optimal production conditions for biochar were determined to be a pyrolysis temperature of 570–800 °C, a residence time of ≥2 h, and a heating rate of 3–10 °C/min to achieve an H/C ratio of <0.2. An online graphical user interface was developed to facilitate user interaction with the model. This study not only provides practical guidelines for optimizing biochar but also introduces a novel approach to modeling using AutoML. Full article

Standalone photovoltaic (PV) systems offer a viable path to decentralized energy access but face limitations during periods of low solar irradiance. While batteries provide short-term storage, their capacity constraints often restrict the use of surplus energy, highlighting the need for long-duration solutions. Green hydrogen, generated via proton exchange membrane (PEM) electrolyzers, offers a scalable alternative. This study proposes a stochastic energy management framework that leverages a Markov decision process (MDP) to coordinate PV generation, battery storage, and hydrogen production under variable irradiance and uncertain load demand. The strategy dynamically allocates power flows, ensuring system stability and efficient energy utilization. Real-time weather data from Goiás, Brazil, is used to simulate system behavior under realistic conditions. Compared to the conventional perturb and observe (P&O) technique, the proposed method significantly improves system performance, achieving a $99.9\%$ average efficiency (vs. 98.64%) and a drastically lower average tracking error of 0.3125 (vs. 9.8836). This enhanced tracking accuracy ensures faster convergence to the maximum power point, even during abrupt load changes, thereby increasing the effective use of solar energy. As a direct consequence, green hydrogen production is maximized while energy curtailment is minimized. The results confirm the robustness of the MDP-based control, demonstrating improved responsiveness, reduced downtime, and enhanced hydrogen yield, thus supporting sustainable energy conversion in off-grid environments. Full article

The rapid development of sixth-generation mobile communication systems has brought about significant advancements in both Quality of Service (QoS) and Quality of Experience (QoE) for users, largely due to the extremely high data rates and a diverse range of service offerings. However, these advancements have also introduced challenges, especially concerning the growing demand for a wireless spectrum and the limited availability of resources. Various efforts have been made and research has attempted to tackle this issue such as the use of Cognitive Radio Networks (CRNs), which allows opportunistic spectrum access and intelligent resource management. This work demonstrate a new method in the optimization of allocation resource in CRNs based on the Snake Optimizer (SO) along with reinforcement learning (RL), which is an effective meta-heuristic algorithm that simulates snake cloning behavior. SO is tested over three different scenarios with varying numbers of secondary users (SUs), primary users (PUs), and frequency bands available. The obtained results reveal that the proposed approach is able to largely satisfy the aforementioned requirements and ensures high spectrum utilization efficiency and low collision rates, which eventually lead to the maximum possible spectral capacity. The study also demonstrates that SO is versatile and resilient and thus indicates its capability of serving as an effective method for augmenting resource management in next-generation wireless communication systems. Full article

Due to the dynamic increase in the number of prosumer electrical installations in Poland, one may observe many negative effects of their development, including the deterioration of energy quality parameters and the reliability of the existing distribution network. The installation of solar panels in Polish homes was mainly motivated by economic reasons. One of the most important problems of the distribution network is the increase in voltage. The aim of this work was to develop a practical method for determining the maximum voltage changes caused by the connection of photovoltaic installations. To accomplish this, a representative low-voltage overhead line, typical of those found in Poland, was modeled using the NEPLAN software. More than 100 distinct simulations were conducted, exploring various locations and power capacities of photovoltaic installations and utilizing authentic annual profiles for both electrical loads and photovoltaic generation. From the analysis of the data obtained, relationships that enable the determination of voltage changes induced by photovoltaic connections at any node within the low-voltage circuit were established. The computational results derived from this simplified model demonstrate sufficient accuracy for practical applications, and the required input data is accessible to distribution system operators. Full article

This paper presents a new high-speed RGB image transmission system over Free-Space Optics (FSO) channel employing Optical Code Division Multiple Access (OCDMA) with Permutation Vector (PV) codes. Four RGB images are transmitted simultaneously at 10 Gbps per image, achieving a total capacity of 40 Gbps. The system’s performance is evaluated under various atmospheric conditions, including three fog levels and real-world visibility data from Alexandria city, Egypt. Image Quality Assessment (IQA) metrics, including Signal-to-Noise Ratio (SNR), Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), correlation coefficients, and Structural Similarity Index Measure (SSIM), are evaluated for both unfiltered and median-filtered images. The results show significant degradation in image quality due to transmission distance and atmospheric attenuation. In Alexandria’s clear atmospheric conditions, the system achieves a maximum transmission range of 15 km with acceptable visual quality, while the range is reduced to 2.6 km, 1.6 km, and 1 km for Low Fog (LF), Medium Fog (MF), and Heavy Fog (HF), respectively. At these distances, the RGB images achieve minimum SNR, RMSE, and SSIM values of 7.27 dB, 47.66, and 0.20, respectively, with further improvements when applying median filtering. Full article

The structural and functional characteristics of oil body proteins (OBPs) isolated from hemp, plum, and jujube seeds were systematically investigated, along with their potential application in constructing curcumin-loaded artificial oleosomes (AOs). OBPs were extracted through alkaline extraction coupled with ultrasonic disruption, followed by comprehensive physicochemical characterization using SDS-PAGE, FTIR spectroscopy, fluorescence spectroscopy, and evaluation of particle size, zeta potential, surface hydrophobicity, solubility, thermal stability, and emulsification properties. Plum seed-derived OBPs were found to demonstrate superior emulsifying capacity and solubility, which were attributed to distinctive structural features, including the following: an elevated random coil content (13%), enhanced surface hydrophobicity (21,781 A.U.), reduced particle size (103 nm), and higher zeta potential (−46 mV). These structural advantages were correlated with improved interfacial adsorption capacity and colloidal stability. When employed in AO fabrication, plum seed OBPs produced curcumin-loaded systems exhibiting maximum encapsulation efficiency (92%), minimal droplet size (5.99 μm), and optimal bio-accessibility (50%) compared to their hemp- and jujube-based counterparts. Furthermore, AOs utilizing plum seed OBPs displayed enhanced antioxidant activity and significantly improved stability. The collective findings establish plum seed OBPs as exceptional natural emulsifiers with strong potential for bioactive compound delivery applications. Full article

In the present work, the adsorption of vitamin B12 (VB12) on sugarcane-derived activated carbon (AC) was investigated with the purpose of developing a hybrid material able to degrade highly toxic and recalcitrant chlordecone (CLD) for remediating the severe environmental issue of pesticide pollution of water and soil. The AC used is made from locally accessible sugarcane bagasse. The experimental kinetic and isothermic data of VB12 adsorption on AC were modeled using multiple models, including Pseudo-Order 1 (Lagergren), Pseudo-Order 2, Elovich, and Brouers–Sotolongo models for the kinetics. The isotherms models used were Langmuir, Freundlich, Hill–Sips, Brouers–Sotolongo (BS), Brouers-Gaspard (BG), General Brouers–Sotolongo (GBS), and Redlich–Peterson (RP) models. The results showed that the BG model is the most suitable to satisfactorily describe the adsorption of VB12 on the studied AC, involving a heterogeneous adsorption mechanism onto a heterogeneous surface and providing the maximum adsorption capacity, a convenient tool to estimate the saturation level of adsorbate (i.e., chlordecone (CLD)) onto the adsorbent (AC). Voltammetric studies confirm the interaction between VB12 and the AC. Finally, molecular modeling is used to provide atomic insights showing the entrapment of VB12 inside the porous system to form a new hybrid material. The calculations provide the conformations with the best binding energy in the GaudiMM environment. Full article

With the spread of electric vehicles (EVs), the EV load will have a significant impact on the planning and operation of the grid and the operation of the electricity market. Due to the charging and discharging characteristics of EVs, as well as their randomness and dispersion, it is feasible and challenging to introduce EV loads into the grid as a means of frequency regulation and peak shaving of the power system. In this paper, considering multi-subject distribution networks and the interaction of source–grid–load–storage with Intelligent Transportation Systems (ITS), a density peak clustering (DPC) algorithm based on principal component analysis is employed to analyze the spatial and temporal characteristics of EV loads and identify the access status of EV charging stations and EV load status in each region in real time, as well as analyze the adjustable capacity and adjustable range of EV loads. Based on the adjustable capacity of the EV load, the optimization objectives include the maximum regulation of the EV load and the most economical operation cost. An accurate load regulation strategy based on automatic active control (APC) is proposed to reduce the maximum frequency deviation by 25% by integrating the load regulation of electric vehicles into the original AGC frequency regulation. At the same time, the feasibility of electric vehicles in peaking and standby scenarios is studied and verified through simulation cases, which can reduce the peak value of thermal power generation by 15% and 10% in the morning and evening. Full article

It is well understood that climate change is a major cause of the environmental shifts that are significantly impacting human lives. The floods caused by climate change are not only occurring more frequently each year, but they also bring up the problem of access to clean water for drinking and other daily usage for the affected communities. The Swat district of the Khyber Pakhtunkhwa province in Pakistan is one of the impacted regions and the growing concern for clean water access is yet to be resolved. This study aims to propose a sustainable solution to water access during the emergencies, particularly in flood and drought situations. While the roof water harvesting system (RWHS) is well established and functional in many developed regions, its potential remains underexplored in Pakistan. This research study analyzed the climate change projection data for the Saidu Sharif region of Swat. The regional climate data are gathered from the Shared Socio-economic Pathways (SSPs) for the period from 2015 to 2045. Five general circulation models (GCMs) were selected based on their performance in South Asian climate simulations. Analysis of the regional forecasted climate data indicates that almost all of the five climate models have predicted the periods of excessive rainfall to occur in the months of July, August, and September, while prolonged dry seasons may last between 271 and 325 days annually. Hydrological modeling was used to estimate RWHS performance, which incorporated the key parameters such as catchment area, runoff coefficient, and rainfall intensity. The findings suggest that the proposed RWHS could meet basic drinking water needs during the floods and even during the drought periods near around 100% satisfaction of water demand under certain conditions. For example, for an average drought period of 273 days, a household of seven people with a per capita daily water demand of 17 L requires a storage capacity of 33 m³. On the other hand, for a maximum drought duration of 325 days, the required storage volume increases to 39 m³. Demand satisfaction calculations are also used to evaluate the effectiveness of the proposed model. This research contributes to addressing the growing water scarcity challenge posed by climate change in the Swat region and offers a sustainable and practical solution. Full article