Search Results (1,179)

Driven by the imperative for enhanced battery safety, solid electrolytes have emerged as a leading strategy in next-generation energy storage technologies. Beyond conventional polymer, oxide, and sulfide systems, chloride-based inorganic solid electrolytes have recently garnered significant attention due to their unique combination of high ionic conductivity, favorable electrochemical stability, and processability. This work presents a comprehensive review of chloride solid electrolytes, examining their crystal structures, synthesis approaches, ionic transport mechanisms, and physicochemical stability under operational conditions. Furthermore, we discuss critical considerations for integrating these materials into practical all-solid-state batteries (ASSBs), including performance across wide temperature ranges, scalable cell fabrication methods, and cost-effectiveness. By bridging fundamental material properties with device-level engineering challenges, this review aims to provide a roadmap for future research and development, highlighting the substantial promise of chloride electrolytes in enabling safe, high-performance solid-state batteries. Full article

The increasing impact of infectious, cardiovascular and neurodegenerative diseases has intensified the demand for early and decentralized diagnostics. Label-free electrochemical biosensors are promising candidates, offering high sensitivity, low reagent consumption and miniaturizable, low-cost architectures for point-of-care (PoC) testing. This review summarizes advances in immobilization strategies, recognition elements such as DNA, antibodies, aptamers, and molecularly imprinted polymers, as well as electrode platforms including glassy carbon, screen-printed, and 3D-printed systems, with an emphasis on DNA biosensors, multiplexed configurations, and applications to disease biomarkers. Beyond analytical performance, we critically examine the barriers that keep most devices at the proof-of-concept stage, including bioreceptor stability and immobilization, limited validation in real samples, reliance on conventional materials, challenges in scalable manufacturing, transport, and storage, and the absence of fully integrated PoC systems. Finally, we discuss significant advances in sensitivity, reproducibility, and application to real samples, but note that translation to real-world use and commercialization remains limited. Full article

The heavy use of digital images across network systems has become a major concern regarding data confidentiality and unauthorized access. Conventional image encryption techniques hardly achieve high security levels efficiently, especially in real-time and resource-constrained environments. These challenges motivate the development of more robust and efficient encryption mechanisms. In this paper, a dual-chaotic image encryption framework is developed where two complementary chaotic systems are combined to effectively realize confusion and diffusion. The proposed method uses a chaotic permutation mechanism to find the pixel positions and enhanced chaotic diffusion to change the pixel values for eliminating the statistical correlations. An extended family of piecewise affine chaotic maps is designed to enhance the dynamic range and complexity of the diffusion process for strengthening the resistance capability against cryptographic attacks. Intensive experimental validations confirm that the proposed scheme well obscures the visual information and strongly reduces the pixel correlations in the encrypted images. High entropy values, uniform histogram distributions, high resistance to differential attacks, and improved robustness are further evidenced by statistical and security analyses compared to some conventional image encryption techniques. The results also show extremely low computational overheads, hence allowing for efficient implementation. The proposed encryption framework provides more security for digital image transmission and storage, and the performances are still practical. Given its robustness, efficiency, and scalability, it is equally adequate for real-time multi-media applications and secure communication systems, hence promising to offer a reliable solution for modern image protection requirements. Full article

The agri-food sector is a major contributor to global greenhouse gas emissions while facing increasing demand for food production driven by population growth. Transitioning towards sustainable and low-carbon agricultural systems is therefore critical. Green hydrogen, produced from renewable energy sources, holds significant promise as a clean energy carrier and chemical feedstock to decarbonize multiple stages of the agri-food supply chain. This systematic review is based on a structured analysis of peer-reviewed literature retrieved from Web of Science, Scopus, and Google Scholar, covering over 120 academic publications published between 2010 and 2025. This review provides a comprehensive overview of hydrogen’s current and prospective applications across agriculture and the food industry, highlighting opportunities to reduce fossil fuel dependence and greenhouse gas emissions. In agriculture, hydrogen-powered machinery, hydrogen-rich water treatments for crop enhancement, and the use of green hydrogen for sustainable fertilizer production are explored. Innovative waste-to-hydrogen strategies contribute to circular resource utilization within farming systems. In the food industry, hydrogen supports fat hydrogenation and modified atmosphere packaging to extend product shelf life and serves as a sustainable energy source for processing operations. The analysis indicates that near-term opportunities for green hydrogen deployment are concentrated in fertilizer production, food processing, and controlled-environment agriculture, while broader adoption in agricultural machinery remains constrained by cost, storage, and infrastructure limitations. Challenges such as scalability, economic viability, and infrastructure development are also discussed. Future research should prioritize field-scale demonstrations, technology-specific life-cycle and techno-economic assessments, and policy frameworks adapted to decentralized and rural agri-food contexts. The integration of hydrogen technologies offers a promising pathway to achieve carbon-neutral, resilient, and efficient agri-food systems that align with global sustainability goals and climate commitments. Full article

The widespread use of petroleum derivatives in industrial settings poses a challenge due to their toxicity and the difficulty of removing them from tanks, pipes, and equipment. Conventional degreasers are generally expensive, toxic, and harmful to workers’ health and the environment. In this study, an environmentally friendly biodetergent formulated from natural ingredients was produced in a pilot plant with 480 L h⁻¹ capacity, in 250 L homogenizers, at 3500 rpm and 80 °C, and its performance evaluated under different operating conditions. Furthermore, the biodetergent efficiency was compared with that of commercial degreasers commonly used in industrial settings. Stability tests indicated 100% stable emulsion with 2.0% fatty alcohol and 1.0% stabilizing gum after one week of storage. In application tests, the biodetergent promoted up to 100% removal of heavy fuel oil (OCB1) and diesel from metal surfaces, both in concentrated and (1:1 v/v) diluted forms. In direct comparisons, the product performed equally or better than commercial degreasers, notably removing >95% of OCB1 in 10 min and maintaining efficiency after multiple reuse cycles. Unlike acidic or solvent-based formulations, the biodetergent did not induce corrosion on pieces or release toxic vapors when applied to heated surfaces. In summary, the developed bioproduct demonstrated industrial scalability and high efficiency, constituting a sustainable alternative for petrochemical cleaning operations in onshore and offshore environments. Full article

Achieving Egypt’s 2035 renewable electricity targets presents substantial operational and institutional challenges, compounded by limited electricity trade across the Middle East and North Africa (MENA) region. This study applies a PLEXOS-based simulation framework that integrates short-term economic dispatch with the Projected Assessment of System Adequacy (PASA) to evaluate the system-level impacts of economically dispatched cross-border interconnections with Saudi Arabia, Libya, Jordan, and Sudan. The analysis also incorporates domestic flexibility measures, including five-minute dispatch, dynamic reserve requirements, and battery energy storage systems (BESS). Scenarios with renewable energy penetration levels of up to 50% are assessed using Egypt’s 2023 power system as the baseline. The results demonstrate that transitioning from a static, hourly, standalone operating framework to an integrated flexibility configuration—combining five-minute dispatch, 8 GW of economically dispatched cross-border interconnection capacity, and 8 GWh of BESS—yields substantial system-wide benefits at 50% renewable penetration. Loss-of-Load Probability declines from 96.48% to zero, ensuring full system adequacy, while total operational costs decrease by more than 45%, corresponding to annual savings of approximately USD 1.04 billion. Renewable energy curtailment is reduced by over 98%, enabling nearly 15 TWh of additional clean electricity generation, and CO₂ emissions fall by 11.6 million tons (≈40%). In addition, the operating-reserve shadow price—an indicator of reserve scarcity—declines to near zero, underscoring the effectiveness of coordinated regional dispatch and domestic flexibility in mitigating scarcity conditions. These findings provide robust evidence that integrated operational, temporal, and spatial flexibility can significantly accelerate renewable energy integration while strengthening system adequacy. The proposed framework offers an actionable and scalable blueprint for policy coordination and market reform in Egypt, with broader relevance for emerging power systems across the MENA region. Full article

Unmanned Aerial Vehicles (UAVs) are increasingly integrated into Internet of Things (IoT) ecosystems for applications such as surveillance, disaster response, environmental monitoring, and logistics. These missions demand reliable and secure communication between UAVs and cloud platforms for command, control, and data storage. However, UAV communication channels are highly vulnerable to eavesdropping, spoofing, and man-in-the-middle attacks due to their wireless and often long-range nature. Traditional cryptographic schemes either impose excessive computational overhead on resource-constrained UAVs or lack sufficient robustness for cloud-level security. To address this challenge, we propose a dual-layer encryption architecture that balances lightweight efficiency with strong cryptographic guarantees. Unlike prior dual-layer approaches, the proposed framework introduces a context-aware adaptive lightweight layer for UAV-to-gateway communication and a hybrid post-quantum layer for gateway-to-cloud security, enabling dynamic cipher selection, energy-aware key scheduling, and quantum-resilient key establishment. In the first layer, UAV-to-gateway communication employs a lightweight symmetric encryption scheme optimized for low latency and minimal energy consumption. In the second layer, gateway-to-cloud communication uses post-quantum asymmetric encryption to ensure resilience against emerging quantum threats. The architecture is further reinforced with optional multi-path hardening and blockchain-assisted key lifecycle management to enhance scalability and tamper-proof auditability. Experimental evaluation using a UAV testbed and cloud integration shows that the proposed framework achieves 99.85% confidentiality preservation, reduces computational overhead on UAVs by 42%, and improves end-to-end latency by 35% compared to conventional single-layer encryption schemes. These results confirm that the proposed adaptive and hybridized dual-layer design provides a scalable, secure, and resource-aware solution for UAV-to-cloud communication, offering both present-day practicality and future-proof cryptographic resilience. Full article

The exponential growth of digital data and the escalating sophistication of cyber threats have intensified the demand for secure yet computationally efficient encryption methods. Conventional algorithms (e.g., AES-based schemes) are cryptographically strong and widely deployed; however, some implementations can face performance bottlenecks in large-scale or real-time workloads. While many modern systems seed from hardware entropy sources and employ standardized cryptographic PRNGs/DRBGs, security can still be degraded in practice by weak entropy initialization, misconfiguration, or the use of non-cryptographic deterministic generators in certain environments. To address these gaps, this study introduces FileCipher. This novel file-encryption framework integrates a chaos-enhanced Cryptographically Secure Pseudorandom Number Generator (CPRNG) based on the State-Based Tent Map (SBTM). The proposed design achieves a balanced trade-off between security and efficiency through dynamic key generation, adaptive block reshaping, and structured confusion–diffusion processes. The SBTM-driven CPRNG introduces adaptive seeding and multi-key feedback, ensuring high entropy and sensitivity to initial conditions. A multi-threaded Java implementation demonstrates approximately 60% reduction in encryption time compared with AES-CBC, validating FileCipher’s scalability in parallel execution environments. Statistical evaluations using NIST SP 800-22, SP 800-90B, Dieharder, and TestU01 confirm superior randomness with over 99% pass rates, while Avalanche Effect analysis indicates bit-change ratios near 50%, proving strong diffusion characteristics. The results highlight FileCipher’s novelty in combining nonlinear chaotic dynamics with lightweight parallel architecture, offering a robust, platform-independent solution for secure data storage and transmission. Ultimately, this paper contributes a reproducible, entropy-stable, and high-performance cryptographic mechanism that redefines the efficiency–security balance in modern encryption systems. Full article

This paper presents Nexus, a proof-of-concept low-cost, modular, and reprogrammable multichannel data logger aimed at validating the architectural feasibility of an open and scalable acquisition platform for scientific instrumentation. The system was conceived to address common limitations of commercial data loggers, such as high cost, restricted configurability, and limited autonomy, by relying exclusively on widely available components and open hardware/software resources, thereby facilitating reproducibility and adoption in resource-constrained academic and industrial environments. The proposed architecture supports up to six interchangeable acquisition modules, enabling the integration of up to 20 analog channels with heterogeneous resolutions (24-bit, 12-bit, and 10-bit ADCs), as well as digital acquisition through multiple communication interfaces, including I²C (two independent buses), SPI (two buses), and UART (three interfaces). Quantitative validation was performed using representative acquisition configurations, including a 24-bit ADS1256 stage operating at sampling rates of up to 30 kSPS, 12-bit microcontroller-based stages operating at approximately 1 kSPS, and 10-bit operating at 100 SPS, consistent with stable real-time acquisition and visualization under proof-of-concept constraints. SPI communication was configured with an effective clock frequency of 2 MHz, ensuring deterministic data transfer across the tested acquisition modules. A hybrid data management strategy is implemented, combining high-capacity local storage via USB 3.0 solid-state drives, optional cloud synchronization, and a 7-inch touchscreen human–machine interface based on Raspberry Pi OS for system control and visualization. Power continuity is addressed through an integrated smart uninterruptible power supply, which provides telemetry, automatic source switching, and limited backup operation during power interruptions. As a proof of concept, the system was functionally validated through architectural and interface-level tests, demonstrating stable communication across all supported protocols and reliable acquisition of synthetic and biosignal-like waveforms. The results confirm the feasibility of the proposed modular architecture and its ability to integrate heterogeneous acquisition, storage, and interface subsystems within a unified open-source platform. While not intended as a finalized commercial product, Nexus establishes a validated foundation for future developments in modular data logging, embedded intelligence, and application-specific instrumentation. Full article

Electrochemical carbon dioxide reduction reaction (CO₂RR) offers a promising route to mitigate climate change while simultaneously enabling renewable energy storage and the sustainable production of value-added chemicals. A wide variety of CO₂RR reactor designs have been developed, including both liquid-phase cells and gas-phase configurations. Among these, gas-phase systems, particularly flow-cell and membrane electrode assembly (MEA) designs, have become the primary focus of recent research due to their ability to overcome mass transport limitations and operate at high currents. While catalyst development has received considerable attention in advancing CO₂RR performance, the role of membranes in these gas-phase electrolyzers has been less systematically reviewed. This article addresses that gap by critically examining the functions, advantages, and limitations of the major membrane classes used in CO₂ electrolysis: anion exchange membranes, cation exchange membranes, bipolar membranes, and non-ion-exchange porous membranes within flow-cell and MEA configurations. We highlight how membrane properties influence local pH regulation, water management, crossover behavior, and overall reactor performance, while emphasizing that product identity is primarily catalyst-determined. By analyzing recent progress and remaining challenges, this review provides design insights for membrane selection and development toward efficient, stable, and scalable CO₂ electrolysis systems. Full article

Concrete 3D printing (3DCP) combines materials science with material processing technologies to enable automated, additive construction. This review summarizes findings from the literature and industrial practice on 3DCP mortar formulation with emphasis on the material processing chain. The workflow is examined from raw material storage through handling, mixing, and deposition. The roles of binders, aggregates, dispersed reinforcement, and chemical admixtures are discussed in relation to rheological behavior, buildability, and early-age mechanical performance. The analysis covers storage, dosing, and mixing strategies with respect to mix consistency and overall process reliability, while mortar pumping and extrusion are addressed alongside nozzle-injected additives and automation. Finally, limitations and scalability challenges are outlined with research directions such as continuous mixing, in-line monitoring, and adaptive mix formulation for on-site applications. Full article

This perspective provides a multidisciplinary assessment of the use of lithium-ion batteries from electric vehicles (EVs) for second-life applications, motivated by the need to improve resource efficiency, reduce environmental impacts, and support a circular battery economy. Second-life deployment requires the integrated consideration of technical performance, legal compliance, and economic viability. The analysis combines a technical evaluation of battery aging mechanisms, operational load effects, and qualification strategies with a legal assessment of the EU Batteries Regulation (EU) 2023/1542 and an economic analysis of market potential and business models (BM). From a technical perspective, the limitations of State of Health (SOH) as a standalone indicator are demonstrated, highlighting the need for multiple health indicators and degradation-aware qualification. A scalable two-step qualification approach, combining qualitative inspection with a standardized quantitative measurement protocol, is discussed. From a legal perspective, regulatory requirements and barriers related to repurposing, waste classification, and conformity assessment are analyzed. From an economic perspective, business model patterns and market dynamics are evaluated, identifying Automated Guided Vehicles (AGVs) and industrial Energy Storage Systems (ESSs) for renewable firming as particularly promising applications. The paper concludes with recommendations for action and key research needs to enable safe, economically viable, and legally compliant second-life deployment. Full article

Cement production exerts a significant negative impact on the environment through the emission of greenhouse gases, particulate matter (PM), heavy metals, and other toxic substances into the atmosphere, soil, and bodies of water, degrading the environment and affecting the population’s health. This study reviews different solutions to reduce pollution and mitigate its effects. Particular attention is given to Carbon Capture, Utilization, and Storage (CCUS) technologies and their ability to significantly reduce CO₂. Biomass and waste-derived fuels were identified as viable substitutes for fossil fuels, although challenges related to supply chain reliability and secondary environmental impacts remain. The study further examined mitigation strategies for non-gaseous pollutants, including noise pollution control measures such as sound barriers and vibration isolation systems, soil remediation techniques such as phytoremediation and the recycling of cement kiln dust (CKD), and water pollution control technologies, including filtration, chemical precipitation, biological treatment, and Zero Liquid Discharge (ZLD) systems. Key research gaps were identified, particularly concerning the long-term durability, scalability, and cost-effectiveness of these mitigation approaches. Overall, the review emphasizes the need for integrated pollution control strategies to support the transition toward a more sustainable cement industry and recommends future research focused on developing mitigation technologies that are efficient, economically viable, and adaptable to large-scale industrial applications. Full article

The rapid integration of photovoltaic (PV) generation into modern power networks introduces significant operational challenges, including intermittent power production, uneven charge distribution, and reduced system reliability in multi-battery energy storage systems. Addressing these challenges requires intelligent, adaptive, and physically consistent control strategies capable of operating under uncertain environmental and load conditions. This study proposes a Physics-Informed Neural Network (PINN)-based charge allocation framework that explicitly embeds physical constraints—namely charge conservation and State-of-Charge (SoC) equalization—directly into the learning process, enabling real-time adaptive control under varying irradiance and load conditions. The proposed controller exploits real-time measurements of PV voltage, current, and irradiance to achieve optimal charge distribution while ensuring converter stability and balanced battery operation. The framework is implemented and validated in MATLAB/Simulink under Standard Test Conditions of 1000 W·m⁻² irradiance and 25 °C ambient temperature. Simulation results demonstrate stable PV voltage regulation within the 230–250 V range, an average PV power output of approximately 95 kW, and effective duty-cycle control within the range of 0.35–0.45. The system maintains balanced three-phase grid voltages and currents with stable sinusoidal waveforms, indicating high power quality during steady-state operation. Compared with conventional Proportional–Integral–Derivative (PID) and Model Predictive Control (MPC) methods, the PINN-based approach achieves faster SoC equalization, reduced transient fluctuations, and more than 6% improvement in overall system efficiency. These results confirm the strong potential of physics-informed intelligent control as a scalable and reliable solution for smart PV–battery energy systems, with direct relevance to renewable microgrids and electric vehicle charging infrastructures. Full article

High-energy Ni-rich layered cathodes are critical for next-generation lithium-ion batteries yet remain limited by severe interfacial degradation and thermal vulnerability under high-voltage operation. In this work, a robust spinel-layered heterostructure is constructed by encapsulating LiNi_0.8Co_0.1Mn_0.1O₂ (NCM811) with a LiNi_0.5Mn_1.5O₄ (LNMO) spinel shell via a scalable sol–gel route. Structural characterizations confirm that the coating maintains the secondary-particle architecture, while X-ray photoelectron spectroscopy reveals a chemically reconditioned interface, achieved by the scavenging residual lithium species and suppressing of rock-salt-like surface reconstruction. Consequently, the optimized 4 wt% LNMO@NCM811 electrode demonstrates significantly enhanced high-voltage (2.8–4.4 V) stability, maintaining 41.84% of its initial capacity after 200 cycles compared to only 15.75% for the pristine sample. Crucially, thermogravimetric-differential scanning calorimetry (TG-DSC) uncovers the kinetic origin of this safety improvement: the spinel shell alters the thermal decomposition pathway, delaying the 10% mass loss temperature (T_10%) from 515.2 °C to 716.6 °C and suppressing the total exothermic heat release from 208.3 J g⁻¹ to 81.5 J g⁻¹. Collectively, these results demonstrate that the co-free spinel encapsulation is a dual-functional strategy to simultaneously stabilize surficial chemistry and intrinsically enhance the thermal safety of Ni-rich cathodes for carbon-neutral energy storage applications. Full article