Search Results (73)

In accordance with growing environmental pressures and the demand for sustainable industrial practices, membrane technologies have emerged as key enablers for increasing efficiency, reducing emissions, and supporting circular processes across multiple sectors. This review focuses on the integration among microalgae-based systems, offering innovative and sustainable solutions for biomass production, carbon capture, and industrial wastewater treatment. In cultivation, membrane photobioreactors (MPBRs) have demonstrated biomass productivity up to nine times greater than that of conventional systems and significant reductions in water (above 75%) and energy (approximately 0.75 kWh/m³) footprints. For carbon capture, hollow fiber membranes and hybrid configurations increase CO₂ transfer rates by up to 300%, achieving utilization efficiencies above 85%. Coupling membrane systems with industrial effluents has enabled nutrient removal efficiencies of up to 97% for nitrogen and 93% for phosphorus, contributing to environmental remediation and resource recovery. This review also highlights recent innovations, such as self-forming dynamic membranes, magnetically induced vibration systems, antifouling surface modifications, and advanced control strategies that optimize process performance and energy use. These advancements position membrane-based microalgae systems as promising platforms for carbon-neutral biorefineries and sustainable industrial operations, particularly in the oil and gas, mining, and environmental technology sectors, which are aligned with global climate goals and the UN Sustainable Development Goals (SDGs). Full article

Climate change has driven global awareness of environmental issues, leading to the adoption of clean technologies aimed at reducing Greenhouse Gas (GHG) emissions. An effective method to assess environmental mitigation is the quantification of the Product Carbon Footprint (PCF) in the Life Cycle Assessment (LCA) of production processes. In the oil extraction industry, artificial lift systems use electro submersible pumps (ESPs) that can now incorporate new operating principles based on permanent magnet motors (PMMs) and CanSystem (CS) as an alternative to traditional normal induction motors (NIMs) and can help lower the carbon footprint. This study compares the PCF of ESPs equipped with PMMs and CS versus NIMs, using LCA methodologies in accordance with ISO 14067:2018 for defining the Functional Unit (FU) and ISO 14064-1:2019 to calculate the GHG inventory and the amount of CO₂ equivalent per year. The analysis spans five key stages and 14 related activities. For ESPs with NIMs, this study calculated 999.9 kg of raw materials, 1491.66 kW/h for manufacturing and storage, and 5.77 × 10⁴ kW/h for use. In contrast, ESPs with PMMs and CS required 656 kg of raw materials and consumed 4.44 × 10⁴ kW/h during use, resulting in an 23% reduction in energy consumption. This contributed to an 21.9% decrease in the PCF. The findings suggest that PMMs and CS offer a sustainable solution for reducing GHG emissions in oil extraction processes globally. Full article

In recent years, there has been a notable concern about the production of cementitious composites due to its high cement consumption and the corresponding carbon footprint. This has led to significant progress within the construction sector in integrating various waste materials as cement alternatives into cementitious composites. In this study, a sustainable high strength fiber reinforced mortar (HS-FRM) was designed with ceramic powder (CP) and metakaolin (MK) materials as partial replacements of the conventional HS-FRM by up to 80%. Magnetized water (MW) was used in the proposed HS-FRM as mixing water and replaced the normal tap water (TW) for producing a more sustainable and higher strength cementitious product. The HS-FRM was cured using four different curing methods, namely, tap water, seawater, air, and sunlight. Fresh, mechanical, durability, and microstructure characteristics were measured and analyzed for the proposed HS-FRM. The results showed that CP can enhance the slump of HS-FRM by up to 50% (achieved at 40% CP), while MK showed the same or less slump (by up to 33%) than that of the conventional HS-FRM. Using up to 80% of either CP or MK in the HS-FRM continuously decreased its 28-day compressive strength by up to 78% or 83%, respectively. The HS-FRM cured in tap water exhibited the highest compressive strength compared to the other curing conditions. The use of MW improved the workability of the HS-FRM by up to 225% and the compressive strength by up to 13%. The microstructure analyses interpreted the reported variation in the HS-FRM compressive strength and showed that using MW in the HS-FRM revealed a dense structure with an adequate bond between the fiber and the matrix with a relatively low number of micro-cracks and pores compared when using TW. The XRD analysis showed higher peaks of Q, C, and L with the presence of MW compared to mixtures made with TW. Full article

Accurate current sensing in rectangular conductors is challenged by mechanical deformations, including eccentricity (X/Y-axis shifts) and inclination (Z-axis tilt), which distort magnetic field distributions and induce measurement errors. To address this, we propose a bio-inspired error compensation strategy integrating an elliptically configured Hall sensor array with a hybrid Grey Wolf Optimizer (GWO)-enhanced backpropagation neural network. The eccentric displacement and tilt angle of the conductor are quantified via a three-dimensional magnetic field reconstruction and current inversion modeling. A dual-stage optimization framework is implemented: first, establishing a BP neural network for real-time conductor state estimations, and second, leveraging the GWO’s swarm intelligence to refine network weights and thresholds, thereby avoiding local optima and enhancing the robustness against asymmetric field patterns. The experimental validation under extreme mechanical deformations (X/Y-eccentricity: ±8 mm; Z-tilt: ±15°) demonstrates the strategy’s efficacy, achieving a 65.07%, 45.74%, and 76.15% error suppression for X-, Y-, and Z-axis deviations. The elliptical configuration reduces the installation footprint by 72.4% compared with conventional circular sensor arrays while maintaining a robust suppression of eccentricity- and tilt-induced errors, proving critical for space-constrained applications, such as electric vehicle powertrains and miniaturized industrial inverters. This work bridges bio-inspired algorithms and adaptive sensing hardware, offering a systematic solution to mechanical deformation-induced errors in high-density power systems. Full article

Accurately detecting and classifying brain tumors in magnetic resonance imaging (MRI) scans poses formidable challenges, stemming from the heterogeneous presentation of tumors and the need for reliable, real-time diagnostic outputs. In this paper, we propose a novel multi-path convolutional architecture enhanced with channel-wise attention mechanisms, evaluated on a comprehensive four-class brain tumor dataset. Specifically: (i) we design a parallel feature extraction strategy that captures nuanced tumor morphologies, while channel-wise attention refines salient characteristics; (ii) we employ systematic data augmentation, yielding a balanced dataset of 6380 MRI scans to bolster model generalization; (iii) we compare the proposed architecture against state-of-the-art models, demonstrating superior diagnostic performance with 97.52% accuracy, 97.63% precision, 97.18% recall, 98.32% specificity, and an F1-score of 97.36%; and (iv) we report an inference speed of 5.13 ms per scan, alongside a higher memory footprint of approximately 26 GB, underscoring both the feasibility for real-time clinical application and the importance of resource considerations. These findings collectively highlight the proposed framework’s potential for improving automated brain tumor detection workflows and prompt further optimization for broader clinical deployment. Full article

With the growth of renewable energy, electrified highways can efficiently utilize green energy such as solar and wind for EVs, promoting sustainable transportation and carbon reduction, and accelerating the transition to a greener future. For high-power DC/DC converters in electrified roadways, a lightweight and compact design is crucial, but inductors limit progress. Therefore, this study focuses on the magnetic integration of DC/DC chopping inductors. It first selected and optimized the decoupled magnetic integration form, initial electromagnetic parameters, and core sizes based on circuit topology and device specifications, using core loss and thermal rise models. Then, it determined the optimal winding turns ratio according to the air gap and magnetic resistance ratio, obtaining the final design with insulation considered. The design was verified through finite-element simulation, prototype manufacturing, and testing, and an improved optimization with interleaved parallel control was proposed. Results indicate that magnetic integration reduces the inductor’s volume by 7.93% and footprint by 38.62%, facilitating the lightweight and compact design of relevant magnetic components. With interleaved parallel control, the integrated inductor’s volume can be reduced by 19.74%, significantly decreasing the volume and mass of the chopping inductor. Full article

The demand for computing power has been growing exponentially with the rise of artificial intelligence (AI), machine learning, and the Internet of Things (IoT). This growth requires unconventional computing primitives that prioritize energy efficiency, while also addressing the critical need for scalability. Neuromorphic computing, inspired by the biological brain, offers a transformative paradigm for addressing these challenges. This review paper provides an overview of advancements in 2D spintronics and device architectures designed for neuromorphic applications, with a focus on techniques such as spin-orbit torque, magnetic tunnel junctions, and skyrmions. Emerging van der Waals materials like CrI₃, Fe₃GaTe₂, and graphene-based heterostructures have demonstrated unparalleled potential for integrating memory and logic at the atomic scale. This work highlights technologies with ultra-low energy consumption (0.14 fJ/operation), high switching speeds (sub-nanosecond), and scalability to sub-20 nm footprints. It covers key material innovations and the role of spintronic effects in enabling compact, energy-efficient neuromorphic systems, providing a foundation for advancing scalable, next-generation computing architectures. Full article

The central focus of this work is to implement an effective and cost-friendly wheelchair motion control system for individuals with impaired upper body movements by utilizing the mandibular movement of an individual. The initial part of the system is the signal-gathering system that is built of two functional blocks, the magnet and sensing block. A magnet is affixed to the inferior region of the user’s mandible, and the sensing block, which incorporates two static HMCL 5883L sensors, quantifies the magnetic field intensity modulated by the magnet’s displacement. The processing unit deciphers these sensor signals to ascertain the wheelchair’s trajectory, while the mechanical unit affects the movement directives. The methodology is embedding the HMCL 5883L sensor into the microcontroller to detect the required motion for the wheelchair. The HMCL 5883L sensors are incorporated to identify each change in the orientation of the magnet. HMCL 5883L is a sophisticated and budget technology. The sensor partitions the magnet’s strength path into three hypothetical axes to trace the magnet in the user’s jaw region. The magnet’s configuration in the mandibular region will not create unease, and a user jaw action that requires a certain level is not new. This development empowers the mobility of patients with Quadriplegia, and because of the device’s smaller footprint and feasible modules, it infuses sustainable development and availability. Full article

The biomechanical mechanism of postoperative patellofemoral joint (PFJ) complications after open-wedge high tibial osteotomy (OWHTO) has not been investigated. This study was to determine the length changes in the patellar tendon (PT), medial patellotibial ligament (MPTL), medial patellofemoral ligament (MPFL), and quadriceps moment arm (QMA) during staircase motion before and after OWHTO. Computed tomography (CT) scans of 15 patients’ lower extremities were used to reconstruct three-dimensional models, and magnetic resonance imaging (MRI) of the knee and hip joints was used to mark the soft tissue footprints. Then, such soft tissue lengths were quantified by a dual fluoroscopic imaging system (DFIS). Additionally, function scores were used to assess patient outcome changes. The results showed that there was a contraction of the PT after OWHTO due to its adhesion to the osteotomy site, causing PT length to be negatively correlated to the open-wedge angle. In addition, the shortening of the MPTL and QMA caused patellar instability and an imbalance in the strength of the lower extremities. Additionally, most knee function scores improved after OWHTO, except the Feller scores. Multiple methods should be considered to optimize surgical procedures, postoperative rehabilitation, and physical therapy. Full article

With their cost-effective manufacturing process, hybrid stepper motors (HSMs) are a popular choice for position control in low-power industrial applications. These versatile motors offer a compelling solution for reducing system costs and size since at standstill/low speeds, HSMs typically have higher torque density with respect to low-power permanent magnet (PM) motors. This higher torque density determines a reduced use of rare-earth PMs and, therefore, a lower environmental footprint. In practical applications, the commonly used microstepping control faces low efficiency, low dynamic performance, vibrations, and a variable maximum continuous torque depending on the working point. In this paper, the operating region of an HSM is extended in the field-weakening (FW) region, showing how field-oriented control (FOC) with FW allows one to strongly increase the drive performance with a slight cost increase thanks to the availability of low-cost magnetic encoders. Due to the fact that FOC provides only the requested current, the HSM faces lower temperatures, lower insulation degradation, and lower permanent magnet demagnetization issues. An experimental evaluation comparing the commonly used microstepping and the proposed FOC with FW is performed on four commercial HSMs with different DC voltage power supplies using an industrial test bench. In particular, the experimental campaign has a focus on steady-state conditions in the case of the maximum continuous torque, showing the advantages of FOC with FW because the advantages in transient conditions are well known. Full article

This study addresses the environmental challenges associated with high-performance rare-earth magnets, particularly NdFeB, which are essential in green and digital technologies. By employing Life Cycle Assessment (LCA) with openLCA software, we evaluate the environmental impacts across the life cycles of ferrite, NdFeB, and MnAlC magnets, focusing on extraction, processing, and recycling. Various studies have explored different aspects of the LCA of NdFeB magnets, focusing on production methods, recycling processes, and the environmental impacts of different rare-earth sources. A comparative LCA highlights the significant environmental footprint of rare-earth magnets, underscoring the role of functional unit selection: when assessed per unit of energy density, the environmental impact of NdFeB magnets aligns more closely with alternatives. Methodological issues such as data quality, choice of functional units, and system complexity affect LCA accuracy, as inconsistencies in data or scope led to potential distortions in environmental assessments. This research also explores manganese-based magnets as viable alternatives to reduce reliance on rare-earth materials. Legislative initiatives, including the EU’s Ecodesign Directive and Critical Raw Materials Act, support sustainable management practices to ensure reliable material supply while promoting environmental protection. This paper highlights the importance of sustainable magnetic materials, emphasizing the need for interdisciplinary research to balance technological efficiency and environmental impact, especially as rare-earth magnet demand rises with the transition to renewable energy sources. Full article

Polarization-insensitive waveguide crossings are indispensable components of photonic integrated circuits (PICs), enabling the concurrent computing of optical signals from diverse waveguides inside the limits of a restricted spatial footprint. Leveraging mirror symmetry direct binary search, we successfully demonstrate an ultra-compact and ultra-low loss polarization-insensitive waveguide crossing that achieves insertion losses below −0.11 dB and crosstalk levels beneath −22.6 dB for transverse electric (TE) mode, as well as insertion losses below 0.05 dB and crosstalk levels beneath −24.5 dB for transverse magnetic (TM) mode across the C-band with a footprint of 3 × 4 μm². The results confirm that this mirror symmetry optimization method yields high-efficiency devices while reducing computational time. We believe this high-efficiency polarization-insensitive waveguide crossing can have potential applications in dense PIC systems. Full article

The article presents a sensitivity analysis of the carbon footprint for different modes of transporting neodymium magnets over a selected route, in the context of their environmental impact and sustainable development. Neodymium magnets, widely used in modern technologies such as wind turbines, are essential for renewable energy sources, making the selection of environmentally optimal transportation crucial. The calculations included road, rail, inland waterway, and air transport, using available emission calculators, which allowed for an analysis using averaged emission indicators for each mode of transport. Additionally, a comparative analysis was conducted with the SimaPro program to verify the consistency and accuracy of the results. The findings indicated that rail transport, with access to low-emission infrastructure and a reduced carbon footprint per unit of mass, is the most efficient option for CO₂ emissions reduction, whereas air transport, despite its speed, generates the highest emissions per ton of cargo, making it the least environmentally friendly alternative. A t-test analysis was also conducted to statistically validate the results for each transportation option. Full article

Tungsten (W) and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. Despite these relevant features, there is a lack of understanding of how the structural and mechanical properties of W-based alloys are affected by the temperature in fusion power plants. In this work, we present a study on the thermo-mechanical properties of five W-based plasma-facing materials. First-principles density functional theory (DFT) calculations are combined with the quasi-harmonic approximation (QHA) theory to investigate the electronic, structural, mechanical, and thermal properties of these W-based alloys as a function of temperature. The coefficient of thermal expansion, temperature-dependent elastic constants, and several elastic parameters, including bulk and Young’s modulus, are calculated. Our work advances the understanding of the structural and thermo-mechanical behavior of W-based materials, thus providing insights into the design and selection of candidate plasma-facing materials in fusion energy devices. Full article

Both experimental and clinical liver fibrosis leave a metabolic footprint that can be uncovered and defined using metabolomic approaches. Metabolomics combines pattern recognition algorithms with analytical chemistry, in particular, ¹H and ¹³C nuclear magnetic resonance spectroscopy (NMR), gas chromatography–mass spectrometry (GC–MS) and various liquid chromatography–mass spectrometry (LC–MS) platforms. The analysis of liver fibrosis by each of these methodologies is reviewed separately. Surprisingly, there was little general agreement between studies within each of these three groups and also between groups. The metabolomic footprint determined by NMR (two or more hits between studies) comprised elevated lactate, acetate, choline, 3-hydroxybutyrate, glucose, histidine, methionine, glutamine, phenylalanine, tyrosine and citrate. For GC–MS, succinate, fumarate, malate, ascorbate, glutamate, glycine, serine and, in agreement with NMR, glutamine, phenylalanine, tyrosine and citrate were delineated. For LC–MS, only β-muricholic acid, tryptophan, acylcarnitine, p-cresol, valine and, in agreement with NMR, phosphocholine were identified. The metabolomic footprint of liver fibrosis was upregulated as regards glutamine, phenylalanine, tyrosine, citrate and phosphocholine. Several investigators employed traditional Chinese medicine (TCM) treatments to reverse experimental liver fibrosis, and a commentary is given on the chemical constituents that may possess fibrolytic activity. It is proposed that molecular docking procedures using these TCM constituents may lead to novel therapies for liver fibrosis affecting at least one-in-twenty persons globally, for which there is currently no pharmaceutical cure. This in-depth review summarizes the relevant literature on metabolomics and its implications in addressing the clinical problem of liver fibrosis, cirrhosis and its sequelae. Full article