بحوث سكوبس — فريال ابراهيم جبار

Addresses off-grid potable-water gaps in arid regions with a bio-inspired hybrid aerogel that couples nocturnal atmospheric moisture adsorption with solar-driven interfacial desalination. Rice-husk biochar scaffolds loaded with CaCl₂ and plasmonic nanoparticles are folded into origami panels; characterized physicochemical properties, dynamic vapor sorption across humidity and temperature ranges, photothermal evaporation, and autonomous day night cycling; conducted 0.25 m2 field deployments including arid region, Abha, Saudi Arabia sites producing 2.7 ± 0.3 L day−1 at about 35 % ambient humidity; energy analysis indicated 1.7 MJ kg H2O−1 (0.47 kWh L−1) regeneration; produced water met potable quality metrics; cradle to gate life cycle model reported global warming potential 17.4 kg CO2eq and cumulative energy demand 312 MJ per functional m2 with intensity 0.48 kg CO2eq m3 across assessed service life; cost model with sorbent fabrication $42 m−2 and identified freeze drying throughput as key lever; concept reduces reliance on grid energy and external infrastructure for dispersed communities; limits include processing energy, material cost, and climatic dependence; integration pathways with modular 4 to 6 m2 units discussed, targeting off grid clinics and relief camps. © 2025 Elsevier B.V.

This study investigates residential electricity and gas demand in Iraq using smart meter data from 15,000 households between 2019 and 2023. The primary objective is to analyze temporal energy consumption patterns, focusing on the impact of environmental, behavioral, and household-specific factors. The results show that electricity consumption peaks during the afternoon, particularly between 12:00 and 14:00, with average usage reaching 2.3 to 2.6 kWh, while gas consumption increases in the winter months, especially in the early morning hours, driven by heating and cooking activities. The analysis of weekend versus weekday consumption reveals a 6.4 % increase in electricity and a 3.1 % rise in gas usage on weekends, indicating shifts in behavioral energy usage patterns. The study finds that predicted values closely match observed data, with a deviation of only 5 % for electricity and 7 % for gas, showcasing high model accuracy. The concept of "variability" is clarified as fluctuations in demand across different times of the day, which were reduced in households with efficient appliances, as identified from household energy audits linked to smart meters. The dataset also provides insights into the use of energy-efficient appliances, collected from utility-linked surveys and integrated household registration data. The findings offer valuable insights into demand-side energy management and are particularly relevant to urban Iraqi households but may also inform demand forecasting in similar regions with comparable climates and energy use behaviors. © 2025

This study introduces a novel approach to sustainable fuel production through the integrated application of plasma gasification, Fischer–Tropsch (FT) synthesis, and solar-powered electrolysis, focusing on the co-valorization of medical waste (MW) and biomass waste (BMW). Addressing critical challenges related to waste accumulation and energy security, the system transforms complex waste streams into synthetic e-fuels by optimizing syngas composition and hydrogen integration. In the case study of Iraq where over 4.12 million tonnes of solid waste were landfilled in 2023, including substantial medical and municipal waste this approach offers a viable solution for resource recovery. Plasma gasification converts MW and BMW into syngas, which is refined and processed for CO2 capture using an MDEA-based absorption system. Solar-derived hydrogen, produced through a PEM electrolyzer, is integrated to achieve the optimal H2/CO ratio for FT synthesis. System modeling was conducted in Aspen Plus and MATLAB, with a Genetic Algorithm (GA) employed to optimize parameters for hydrogen yield enhancement. Four biomass-to-medical waste blending ratios (0.2 to 0.8) were tested. The highest-performing scenario (0.8 ratio) achieved a hydrogen mole fraction of 45.78 %, a syngas flowrate of 8,670 Nm3/h, hydrogen production of 1,300 kg/h, and a peak FT conversion efficiency of 55.8 %. Liquid fuel yield reached 1,360 kg/h, with diesel comprising the dominant product at 519 kg/h and 22,317 MJ/h of energy output. Hydrogen utilization efficiency increased to 87.5 %, and energy cost for hydrogen electrolysis decreased to 54.2 MJ/kg. Economic evaluation revealed strong financial viability at scale, with the highest scenario yielding a net present value (NPV) of $43.71 million, return on investment (ROI) of 16.48 %, and a payback period reduced to 14.93 years. Environmental analysis showed significant reductions in CO2 emissions (down to 19.3 %) and improvements in carbon-to-fuel efficiency (up to 71.2 %), with stable solid residue losses. High-temperature plasma gasification was chosen because it can safely process infectious medical waste and delivers a tar-lean syngas ideally suited for downstream Fischer-Tropsch conversion. © 2025 Elsevier Ltd.

Green hydrogen, derived from renewable energy sources, is emerging as a key player in the global transition to sustainable energy. This study provides a comprehensive review of recent advancements in green hydrogen production technologies, including electrolysis (proton exchange membrane, alkaline, and solid-oxide), biological methods, and thermochemical processes. Despite its potential, the green hydrogen sector faces challenges such as high production costs, energy-intensive processes, and infrastructure limitations for storage and transportation. However, global investments and policy initiatives are driving cost reductions, with projections indicating a decline in production costs to below $2/kg by 2030. Countries such as Germany, Japan, and Australia are leading large-scale hydrogen initiatives, with targets to expand electrolyzer capacity and integrate green hydrogen into industrial, transportation, and power generation sectors. Additionally, advancements in electrolyzer efficiency, material innovations, and renewable energy integration are expected to enhance hydrogen's commercial viability. This review highlights key strategies, policy frameworks, and technological improvements needed to accelerate green hydrogen adoption, positioning it as a crucial component in achieving carbon neutrality and enhancing energy security. © 2025 The Authors

Green hydrogen has the potential to significantly contribute to the global energy transition toward sustainable and decarbonized energy systems. Produced through renewable-powered electrolysis, green hydrogen provides a viable pathway for decarbonizing challenging sectors, such as heavy industry and transportation, while simultaneously addressing renewable intermittency by enabling large-scale energy storage and grid flexibility. This study evaluates the geopolitical and economic implications of developing robust green hydrogen supply chains, particularly in renewable resource-rich regions. Despite its promise, significant barriers persist, including high production costs, infrastructural inadequacies, and policy uncertainty. Emerging technological innovations, coupled with supportive financial strategies and comprehensive policy frameworks, can help overcome these barriers. The given outcomes recommended a strengthening international cooperation and implementing harmonized regulatory standards to accelerate green hydrogen adoption globally, positioning it as a core component of achieving net-zero emissions, driving economic growth, and advancing equitable energy transitions. © 2025 The Authors

Artificial Intelligence (AI) has emerged as a critical solution to address persistent challenges hindering renewable energy adoption, including resource intermittency, grid integration complexities, and economic barriers. This review synthesizes recent advancements, highlighting AI's capability to significantly enhance renewable energy systems through improved forecasting accuracy, optimized resource allocation, and heightened operational efficiency. The findings demonstrate AI-driven predictive models' effectiveness in aligning energy generation with demand, reducing operational downtime via predictive maintenance, and stabilizing energy distribution in AI-powered smart grids. Further, AI facilitates efficient management of decentralized energy networks, including microgrids, and enhances energy storage solutions to maintain reliability during low-generation periods. AI's contribution to refining electrolysis processes significantly boosts green hydrogen viability, offering promising decarbonization pathways for energy-intensive industries. Evidence from various international case studies underscores AI's transformative impact, notably in wind and solar forecasting and hybrid system optimization, driving cost reductions and broadening renewable energy access, especially in developing regions. The paper suggests prioritizing research on fully autonomous smart grids and advanced storage solutions to further enhance scalability, reliability, and support global Net-Zero ambitions. Additionally, addressing the societal and environmental implications of AI deployment remains essential for maximizing its sustainable impact in transforming the global energy landscape. © 2025 The Authors

This research introduces a comprehensive multi-criteria geographic information system-based approach designed to determine optimal locations for solar and wind energy development by integrating geographic information system, multi-criteria decision analysis, and the analytical hierarchy process. The methodology enables spatial analysis that considers a wide range of environmental, economic, and technical factors, producing suitability maps that prioritize locations for renewable energy infrastructure. Applied to the geographic and climatic context of Iraq, the approach addresses the countries’ growing energy demands and infrastructure constraints by identifying regions with high renewable energy potential. the analysis resulted in 38.33 % of the total study area being suitable for utility-scale solar photovoltaic installations, 12.44 % for large-scale wind farms, and 34.47 % for small-scale solar photovoltaic projects. site selection criteria included solar irradiance, wind speed, terrain slope, ambient temperature, land use, elevation, and proximity to infrastructure such as roads and power lines. the study demonstrates the critical role of spatial decision-making tools in promoting sustainable energy strategies, especially within developing countries experiencing energy deficits and environmental pressures. © 2025 The Authors

Urban grids face the challenge of expanding renewable deployment while curbing emissions and minimizing the capital burden of network reinforcements, all of which depend on effective flexibility integration. A hybrid optimization framework is introduced, combining Mixed-Integer Nonlinear Programming with a reformulated MILP structure to jointly size photovoltaic systems, battery storage, staged network upgrades, and the dynamic participation of electric vehicles as both load and distributed storage. Thousands of EV constraints are consolidated through a polytope-based approach, and reinforcement costs are captured using a piece-wise linear model tailored to feeder capacity increments. Application to the Tuwaiq Smart City network, covering 3780 households, employs one-minute resolution data for 2024 to benchmark five operational schemes: No Flexibility, Demand Response, Smart Charging, Vehicle-to-Grid, and Integrated Decentralised Energy Management (IDEM). Compared with the baseline, IDEM achieves a 43.8 % reduction in annualised system cost, 46 % decrease in peak imports, and capacity cuts of 75 % and 82 % for PV and storage respectively, alongside a 65 % drop in grid integration expenses. A Monte Carlo test of 150 runs confirms cost stability within ±6 %, validating the robustness of layered flexibility under stochastic solar and mobility profiles. Solving across a full-year span is achieved within minutes on standard hardware, confirming the framework's practical value for strategic energy planning © 2025 The Authors

A comprehensive review of physical, chemical, and geological hydrogen storage and delivery methods to support sustainable energy systems is presented a survey of compressed gas, liquid hydrogen, adsorption on porous carbon and metal organic frameworks, metal and complex hydrides, liquid organic hydrogen carriers, and subsurface options such as salt caverns and depleted reservoirs is provided. Pathways are compared using energy density, reversibility, efficiency, safety, scalability, and cost, and synthesize design trade-offs across mobile and stationary applications. Compressed gas demonstrates technological maturity yet faces compression energy penalties and lower volumetric density. Liquid hydrogen offers compact storage and long-distance transport but contends with liquefaction energy demand and boil-off losses. Metal and complex hydrides enable dense, inherently contained storage, with challenges in heat management and reaction kinetics. Adsorption materials show promise yet often require low temperature for high uptake. Liquid organic hydrogen carriers leverage familiar logistics at the expense of catalytic dehydrogenation steps and efficiency. Geological storage provides seasonal and strategic capacity, with salt caverns emerging as strong candidates while contamination and integrity risks require monitoring and robust standards. Highlight hybrid architectures that pair high-pressure tanks with hydride beds and advanced cryo-compressed approaches that increase practical capacity for mobility. Priorities include faster kinetics at moderate temperature, durable sorbents and hydrides, loss mitigation, standardized safety protocols, techno-economic benchmarks, and integration with renewable grids and transport. © 2025 The Authors

This study introduces an integrated predictive modeling framework for assessing building energy consumption and indoor thermal comfort, with a focus on supporting decarbonization efforts in both new construction and retrofit scenarios. A total of 21 critical design and operational parameters were evaluated using Monte Carlo simulations combined with EnergyPlus, enabling high-resolution analysis of cooling loads, thermal comfort performance, and retrofit outcomes. The proposed multi-variable regression model demonstrated strong predictive accuracy, achieving an R² of 0.98, a mean absolute percentage error of 1.59 %, and a Coefficient of Variation of the Root Mean Square Error (CVRMSE) of 1.47 % in forecasting annual cooling demands. Optimization of variables such as indoor temperature set-point, solar heat gain coefficient, and glazing U-values yielded energy savings of up to 70 kWh/m² annually, corresponding to a potential carbon emission reduction of 31.5 kg CO₂/m²/year, based on a regional electricity emission factor of 0.45 kg CO₂/kWh. The environmental quality thermal comfort index developed within this framework effectively quantified comfort conditions across varying scenarios, with values improving from 50 to 100 under optimized configurations. The model also revealed pronounced spatial variability, with perimeter zones reaching peak cooling loads of up to 198 W/m², emphasizing the need for zone-specific design strategies. © 2025 The Author(s)

The study explores the critical need for adapting research structures to bolster sustainable action and addresses the incorporation of intergovernmental agencies on sustainability findings within a mission-driven approach. Sustainable change is an urgent global challenge requiring swift and comprehensive action. Traditional research structures often struggle to effectively address the complex and interconnected nature of sustainably issues hindering progress. This study proposes a mission-driven framework that aligns research efforts with an overarching goal of combating sustainable change. Integrating Intergovernmental Panel on Climate Change (IPCC) findings, known for scientific rigor and consensus-based assessments, this approach ensures the incorporation of the latest and most reliable sustainability data. The study highlights the potential benefits of this approach, including enhanced policy development, informed decision-making, and greater public engagement. Emphasizing the significance of collaborative efforts among scientists, policymakers, and stakeholders, the mission-driven approach encourages a holistic understanding of sustainability challenges and fosters effective solutions for a more sustainable future. © 2025 The Authors

This study provides a comprehensive assessment of building energy optimization through a systematic methodology utilizing Bayesian Adaptive Spline Surfaces (BASS) across multiple time scales. The complexity of sensitivity analysis increases when addressing issues embedded in multiple time scales. To address this, the proposed approach extends global variance-based sensitivity analysis to annual, monthly, and daily scales. Case studies demonstrate how the methodology leverages BASS models to achieve rapid and precise sensitivity outcomes essential for multi-time-scale energy evaluations. BASS models offer significant advantages, including high predictive accuracy and efficient computation of sensitivity metrics without relying on Monte Carlo integrals. Additionally, the integration of principal component analysis helps manage the high correlation among multiple energy outputs at finer scales, leading to substantial computational cost savings. The findings reveal that this sensitivity analysis approach provides new insights into the energy characteristics influenced by varying weather conditions across different time scales. The results establish a scalable framework applicable to diverse energy systems and time scales, showcasing the adaptability and effectiveness of this method in advancing the field of building energy analysis. © 2025

A data-driven optimization framework was developed to enhance energy performance in building clusters through multi-energy storage systems, combining electrical and thermal solutions. The approach used surrogate modeling, symbolic regression, and genetic programming to simulate energy consumption, integrate weather and tariff data, and refine storage strategies across varied building types. Applied to a cluster in Bismayah city, Iraq, the methodology evaluated HVAC configurations, façade designs, and thermal mass levels to tailor storage capacity recommendations. Results revealed a 38 % reduction in peak grid import and a 24.6 % drop in overall energy consumption when hybrid energy storage was implemented. A thermal energy storage tank capacity of 4651 kWh, coupled with a battery storage unit of 342 kWh, demonstrated a 35 % decrease in energy costs. Demand response participation increased by 45 % through strategic use of pre-cooling routines and temperature reset controls. TES-only configurations achieved energy usage of 16.3 kWh/m², while hybrid configurations further reduced to 8.7 kWh/m². Budget analyses showed that investments ranging from $2.6 million to $10.4 million proportionally enhanced system performance without over-sizing. The integration of Battery and Thermal Energy Storage with Phase Change Materials further supported passive thermal control, reducing HVAC reliance during peak hours. © 2025 The Author(s)

Global plastic waste streams motivate routes that convert polyethylene terephthalate into durable, repairable parts through additive manufacturing. The central question addressed is whether a continuous reactive-extrusion process can transform polyethylene terephthalate flakes into vitrimer filaments that deliver high strength, heat resistance, and repairability with practical energy and cost. Developed a twin-screw reactive-extrusion route that couples grafting and vacuum devolatilization with in-line drawing to 1.75 mm filament, and verified transesterification and imine exchange using infrared spectroscopy, solid-state carbon nuclear magnetic resonance, gel fraction, and Flory–Rehner analysis. Rheology and stress-relaxation defined a topology-freezing window of 120–145 °C and activation energies of 148–190 kJ mol−1, guiding print settings and post-print repair schedules. Printing at 252–255 °C nozzle, 85 °C bed, and 0.20 mm layers produced consistent deposition; mechanical testing reached tensile strength up to 63 MPa, interlayer shear 28–30 MPa, and heat-deflection temperature of 120–125 °C. Weld repair at 150–180 °C restored about 80 % tensile strength, and five melt reprocessings retained about 95 % heat-deflection temperature with modest viscosity drift. Microscopy showed wider inter-bead necks and about 1.6 % porosity with nano-silica, consistent with tougher interfaces. Process energy use totaled 1.70 kWh kg−1 and modeled cost was $1.69 kg−1 with major contributions from feed at $0.752 and electricity at $0.345. The study demonstrates a scalable pathway to high-strength, heat-resistant, and repairable vitrimer parts from waste polyethylene terephthalate with quantified performance, energy, and cost. © 2025 The Authors.

Post quantum is a general name to all the techniques which are safe against the quantum computer attack. The wireless network is one of the most important means of communication. Wireless network security is a top priority. Wireless networks use conventional cryptography, which has various flaws, whereas quantum cryptography claims to be completely secure. It wasn't long after quantum computers became operational that people began to think about new ways to secure electronic communications. After considering all of the weaknesses in conventional cryptosystems, individuals began to look for new ways to secure electronic communications. Traditional cryptography has many problems, but quantum cryptography addresses nearly all of them. ©Copyright Fakhruldeen.

The most common power system (PS) distribution network fault, single line-to-ground fault (SLGF), causes residual current (I res) to start an electrical arc and high voltage (HV) three times the rated voltage in other healthy phases. HV from capacitive currents (IC) damages cable insulation and PS appliances. Peterson The neutral point coil (PC) reduces (I res) and extinguishes the electric arc, but the fault current (I fault) remains below the protection devices' threshold. Operations and equipment are riskier. PC adaptive eliminates electrical arcs, making the network safer. This paper detects I faults online using Texas instrument validation in MATLAB and adaptive by artificial bee colony (ABC). This paper discusses Texas instrument fault current detection and MATLAB validation. It improves system reliability, device protection, and copper savings by thousands of tons. ABC intelligently optimizes many mathematical problems. ABC with network neural artificial intelligence (AI) improves algorithm performance (artificial bee colony network neural (ABCNN)). This new method may improve distribution network SLGF detection. This first work can work online in electrical power stations by building the (eZdsp F28335-RS232) into the program to send fault signals to the control when SLGF occurs without damaging devices, equipment, cables, or power outages. © 2023 Institute of Advanced Engineering and Science. All rights reserved.

This paper tackled the method for determining the number of Peterson coil which is can compensate with the capacitance because it is important in determining the state of parallel resonance, which in turn control the ground fault current and make the approximate value of the current equal to the current in the sound phases. In this way, we can protect the electrical devices and equipment from being damaged by residual current resulting from the arc due to ground fault, which increases the temperature of conductors which are to a breakdown of insulators and damaging them. Ground fault current equals three times the actual current, and its effect depends on two types of variables which are the first: the number of Peterson coils (which specify the inductance value and compensated) and second: the period time of extinguishing electric are in the ground fault. we obtain, by experimental in the lab where it using the servo motor to control the number of Peterson coils which in turn specify the variable and invariable inductance. We have obtained optimal results for the value of ground-fault current, detect the ground fault and treat it without effect of network load and without power cut off for consumer. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

In this paper, we report new nanoscale plasmonic multiple inputs logic gates based on insulator-metal-insulator (IMI) nanoring waveguides. The proposed all-optical gates are numerically analyzed by the finite element method. NOT, AND, NAND, NOR, and EX-NOR all-optical logic gates were suitably designed and investigated based on the linear interface between the propagated waves through the waveguides. The operation wavelength was 1550 nm. The simulation results show that the optical transmission threshold of (0.26) which performs the operation of planned logic gates is accomplished. Moreover, simulation results show that our compact structure of all-optical logic gates may have potential applications in all-optical integrated networks. © 2022 Institute of Advanced Engineering and Science. All rights reserved.

In this paper a laser-based visible light communication system for PC to PC data transmission has been designed, simulated, and implemented. This type of communication uses light waves in the visible spectrum (380 nm to 750 nm) to deliver data. Visible light communication is any way of transmitting data using visible light. In order to avoid being detected by human eyes, this kind of communication sends information at a slower rate than human vision. Visible light communication is significantly more reliable and capable of high information transmission rates than existing wireless technologies such as Wi-Fi, Bluetooth, and others that use radio frequency spectrum. Laser-based visible light communication systems are low-cost, low-power, and do not require radio interference studies. A diode laser is frequently used to create the signal carrier. Due to its high efficiency, it can transmit data as well as illuminate. Light waves can't be intercepted because they can't penetrate opaque objects, signifying a very secure connection. © 2022 Institute of Advanced Engineering and Science. All rights reserved.

The amount of data that must be processed, stored, and modified rises as time passes. An enormous volume of data from a wide range of sources must be stored on a safe platform. Maintaining such a large volume of data on a single computer or hard drive is impracticable. As a result, the cloud is the ideal platform for storing any quantity of data. An advantage of storing data in the cloud is that it may be accessed at any time and from any device. However, the security of data stored in the cloud is a big concern. Because of this, despite the benefits, most users are reluctant to move their papers to the cloud. The data should be encrypted before sending it off to the cloud service provider to avoid this issue. It's a great way to increase the security of your papers. According to a new technique presented in the system, data may be searched across encrypted files without compromising the privacy and security of various data owners. Implementing the pallier homomorphic encryption method makes it possible to perform computations on encrypted data without decryption. © 2022, Institute of Advanced Engineering and Science. All rights reserved.