Search Results (225)

Porous α-Al₂O₃ ceramics are a highly sought-after material with a multitude of applications; for example, they are used as filters, substrates, biomedicine materials, etc. Despite the availability of raw materials, a challenge associated with this technology is the high energy budget caused by sintering above 1500 °C. For the cold sintering processing (CSP) of ceramics, lowering the α-Al₂O₃ sintering temperature is one of the most urgent challenges in the background of its rapid development. This paper is the first to demonstrate a solution to this problem using the CSP of α-alumina ceramics in the presence of pure water as a transient liquid. The manufactured materials were examined using XRD analysis; the evolution of their microstructures during CSP was revealed by SEM; and the porosity was evaluated using the Archimedes method. Ceramics with an open porosity up to 36% were produced at 380–450 °C and 220 MPa in 30 min. An increase in the pressure was found to impede α-Al₂O₃ formation from γ-AlOOH. The development of the microstructure was discussed within the framework of the dissolution–precipitation model and homogenous nucleation. The results of the SEM study pointed to the coalescence of γ-AlOOH grains during CSP. Full article

In this study, a low-cost, scalable and robust process is proposed as an innovative method for coating solar mirrors with a self-cleaning, transparent in the full solar range and versatile material based on auxetic aluminum nitrides, previously obtained at the laboratory scale. This work presents the scaling-up of the fabrication process from the laboratory to prototypal scale and the preliminary results of outdoor self-cleaning solar mirror field tests in the demonstrative concentrating solar power (CSP) plant ENEASHIP located in Casaccia (Rome) ENEA Research Center. Prototypes with a size of 50 × 40 cm have shown stability in external conditions: no coating degradation occurred during the test campaign. Their washing restores the initial reflectance affected by soiling and the self-cleaning performance allows for the utilization of a reduced quantity of water for cleaning operations with respect to the uncoated glass of back surface mirrors. A similar self-cleaning AlN coating could be utilized on other solar components affected by soiling, such as the glass envelopes in heat-collecting elements, PV panels and other parts where a self-cleaning performance combined with an optical one is required. Full article

Solid particles as heat absorptances and storage mediums promise enhanced energy storage densities in concentrated solar power/thermal (CSP/T) plants. Employment of metallurgical slags as a secondary precursor material for solid particle preparation is ecologically and economically beneficial. Although these processed wastes, comprised of several oxides, exhibit generally promising high-temperature properties, chemical scattering from batch to batch may result in distinct material and functional properties, which may be an obstacle for their utilization. In this study, a steelmaking slag, LiDonit (LD), produced using a unique controlled slag treatment with high reproducibility is investigated as a candidate material. The aforementioned subsequent unique slag treatment makes LD a very promising and distinguishable secondary raw material for high-temperature applications. The as-received microstructure, phase components, and chemical composition of the LD material were analyzed to understand its material properties and to assess its reproducibility. The as-received LD chunks were transferred into pellets by subsequent milling, gel-casting, and sintering stages to reveal the potential processing routes. The CSP/T-related properties of sintered pellets, such as high temperature stability, heat capacity, and solar absorptance, were also examined to reveal their potential use in CSP/T applications and expand application areas with high added value. Full article

In the rapidly evolving field of sustainable construction, this study aims to address the critical need for advancement in the building industry, focusing on vital indicators like energy efficiency and cost-effectiveness, as well as improving occupant comfort. This research introduces a novel approach to support the choice of suitable structural systems for mass housing projects, with a case study on Iran’s national housing scheme. This methodology involves a four-phase process, beginning with compiling a database from existing studies to outline primary and secondary indicators affecting structural system selection. It utilizes the fuzzy AHP method for criteria prioritization and the fuzzy TOPSIS technique for alternatives (LSF, 3DP, ICF, TRC, and RCCF). The study identified the light steel framing (LSF) system as the optimal choice for Iran’s housing needs based on various criteria. Then, in the final phase, the study evaluates the seismic performance of cold-formed steel (CFS) frames with various sheathing panel types (OSB, DFP, CSP, and GWB) under monotonic loads, examining key seismic parameters across 38 frame setups. The findings reveal that LSF structures can effectively withstand seismic events within the elastic behavior range, suggesting that this construction approach is viable for enhancing mass housing production in Iran’s construction sector. Full article

This work proposes for the first time protecting–reflecting on both sides of plated mirrors and a solution to polycarbonate surface vulnerability to weathering and scratching using tungsten disulfide (WS₂) by mechanical polishing. The ability of the dynamic chemical plating (DCP) technique to deposit Ag films at the nanometer scale on a polycarbonate (PC) substrate and its characteristics to be metallized is also shown. These deposits hold significant promise for concentrated solar power (CSP) applications. Complementarily, the application of WS₂ as a reflective film for CSP by mechanical polishing on smooth polycarbonate surfaces is both novel and practical. This technique is innovative and scalable without needing reactants or electrical potential, making it highly applicable in real-world scenarios, including, potentially, on-site maintenance. The effects of surface morphology and adhesion, and the reflectivity parameters of the silver metallic surfaces were investigated. Wettability was investigated because it is important for polymeric surfaces in the activation and metal deposition immediately after redox reactions. The flame technique improved wettability by modifying the surface with carbonyl and carboxyl functional groups, with PC among the few industrial polymers that resisted such a part of the process. The change in the chemical composition, roughness, and wettability of the surfaces effectively improved the adhesion between the Ag film and the PC substrate. However, it did not significantly affect the adhesion between PC and WS₂ and showed its possible implementation as a first surface mirror. Overall, this work provides a scalable, innovative method for improving the durability and reflectivity of polycarbonate-based mirrors, with significant implications for CSP applications. Full article

With the surge in cloud storage popularity, more individuals are choosing to store large amounts of data on remote cloud service providers (CSPs) to save local storage resources. However, users’ primary worries revolve around maintaining data integrity and authenticity. Consequently, several cloud auditing methods have emerged to address these concerns. Many of these approaches rely on traditional public-key cryptography systems or are grounded in identity-based cryptography systems or certificateless cryptography systems. However, they are vulnerable to the increased costs linked with certificate management, key escrow, or the significant expenses of establishing a secure channel, respectively. To counter these limitations, Li et al. introduced a certificate-based cloud auditing protocol (LZ22), notable for its minimal tag generation overhead. Nonetheless, this protocol exhibits certain security vulnerabilities. In this paper, we devise a counterfeiting technique that allows the CSP to produce a counterfeit data block with an identical tag to the original one. Our counterfeiting method boasts a 100% success rate ∀ data block and operates with exceptional efficiency. The counterfeiting process for a single block of 10 kB, 50 kB, and 100 kB takes a maximum of 0.08 s, 0.51 s, and 1.04 s, respectively. By substituting the exponential component of homomorphic verifiable tags (HVTs) with non-public random elements, we formulate a secure certificate-based cloud auditing protocol. In comparison to the LZ22 protocol, the average tag generation overhead of our proposed protocol is reduced by 6.80%, 13.78%, and 8.66% for data sizes of 10 kB, 50 kB, and 100 kB, respectively. However, the auditing overhead of our proposed protocol shows an increase. The average overhead rises by 3.05%, 0.17%, and 0.45% over the LZ22 protocol’s overhead for data sizes of 10 kB, 50 kB, and 100 kB, correspondingly. Full article

In this study, a tyre defect detection model is improved and optimized under the YOLOv5 framework, aiming at radial tyre defects with characteristics such as an elongated shape and various target sizes and defect types. The DySneakConv module is introduced to replace the first BotteneckCSP in the Backbone network. The deformation offset of the DySneakConv module is used to make the convolutional energy freely adapt to the structure to improve the recognition rate of tyre defects with elongated features; the AIFI module is introduced to replace the fourth BotteneckCSP, and the self-attention mechanism and the processing of large-scale features are used to improve the recognition rate of tyre defects with elongated features using the AIFI module. This latter module has a self-attention mechanism and the ability to handle large-scale features to solve the problems of diverse tyre defects and different sizes. Secondly, the CARAFE up-sampling operator is introduced to replace the up-sampling operator in the Neck network. The up-sampling kernel prediction module in the CARAFE operator is used to increase the receptive field and allow the feature reorganization module to capture more semantic information to overcome the information loss problem of the up-sampling operator. Finally, based on the improved YOLOv5 detection algorithm, the Channel-wise Knowledge Distillation algorithm lightens the model, reducing its computational requirements and size while ensuring detection accuracy. Experimental studies were conducted on a dataset containing four types of tyre defects. Experimental results for the training set show that the improved algorithm improves the mAP0.5 by 4.6 pp, reduces the model size by 25.6 MB, reduces the computational complexity of the model by 31.3 GFLOPs, and reduces the number of parameters by 12.7 × 10⁶ compared to the original YOLOv5m algorithm. Experimental results for the test set show that the improved algorithm improves the mAP0.5 by 2.6 pp compared to the original YOLOv5m algorithm. This suggests that the improved algorithm is more suitable for tyre defect detection than the original YOLOv5. Full article

In the last two decades, Peru has experienced a process of transformation in the sources of its energy matrix, increasing the participation of clean energy such as solar photovoltaic (PV), on-shore wind, biomass, and small hydro. However, hydropower and natural gas remain the main sources of electricity, whereas off-shore wind, biogas, waves, tidal, and geothermal sources are currently underdeveloped. This article presents the enormous potential of Peru for the generation of electrical energy from a solar source equivalent to 25 GW, as it has in one of the areas of the world with the highest solar radiation throughout the year. In addition, this article presents the main advantages, benefits, and considerations of the implementation of solar photovoltaic technology, with emphasis on (i) the potential of solar energy, showing the available potential and an installed capacity by the year 2024 equivalent to 398 MW, (ii) current solar energy sources, characterizing existing industrial solar photovoltaic (PV) energy plants, and (iii) future solar energy facilities projections, stating the portfolio of solar renewable energy plant projects to be implemented in the future considering an installed capacity of 7.2 GW by 2028. Additionally, lessons learned, challenges, and directions for the future development of solar energy in the country are presented. Finally, the article concludes that if Peru takes advantage of solar potential by considering a sustainable future perspective and implementing strategic land-use planning, the southern region will be transformed into a world-class territory for renewable energy development considering the hybridization of concentrated solar power (CSP) systems with solar photovoltaic (PV) systems and solar energy storage systems. Full article

Electroencephalography (EEG) is effectively employed to describe cognitive patterns corresponding to different tasks of motor functions for brain–computer interface (BCI) implementation. Explicit information processing is necessary to reduce the computational complexity of practical BCI systems. This paper presents an entropy-based approach to select effective EEG channels for motor imagery (MI) classification in brain–computer interface (BCI) systems. The method identifies channels with higher entropy scores, which is an indication of greater information content. It discards redundant or noisy channels leading to reduced computational complexity and improved classification accuracy. High entropy means a more disordered pattern, whereas low entropy means a less disordered pattern with less information. The entropy of each channel for individual trials is calculated. The weight of each channel is represented by the mean entropy of the channel over all the trials. A set of channels with higher mean entropy are selected as effective channels for MI classification. A limited number of sub-band signals are created by decomposing the selected channels. To extract the spatial features, the common spatial pattern (CSP) is applied to each sub-band space of EEG signals. The CSP-based features are used to classify the right-hand and right-foot MI tasks using a support vector machine (SVM). The effectiveness of the proposed approach is validated using two publicly available EEG datasets, known as BCI competition III–IV(A) and BCI competition IV–I. The experimental results demonstrate that the proposed approach surpasses cutting-edge techniques. Full article

Target detection technology based on unmanned aerial vehicle (UAV)-derived aerial imagery has been widely applied in the field of forest fire patrol and rescue. However, due to the specificity of UAV platforms, there are still significant issues to be resolved such as severe omission, low detection accuracy, and poor early warning effectiveness. In light of these issues, this paper proposes an improved YOLOX network for the rapid detection of forest fires in images captured by UAVs. Firstly, to enhance the network’s feature-extraction capability in complex fire environments, a multi-level-feature-extraction structure, CSP-ML, is designed to improve the algorithm’s detection accuracy for small-target fire areas. Additionally, a CBAM attention mechanism is embedded in the neck network to reduce interference caused by background noise and irrelevant information. Secondly, an adaptive-feature-extraction module is introduced in the YOLOX network’s feature fusion part to prevent the loss of important feature information during the fusion process, thus enhancing the network’s feature-learning capability. Lastly, the CIoU loss function is used to replace the original loss function, to address issues such as excessive optimization of negative samples and poor gradient-descent direction, thereby strengthening the network’s effective recognition of positive samples. Experimental results show that the improved YOLOX network has better detection performance, with mAP@50 and mAP@50_95 increasing by 6.4% and 2.17%, respectively, compared to the traditional YOLOX network. In multi-target flame and small-target flame scenarios, the improved YOLO model achieved a mAP of 96.3%, outperforming deep learning algorithms such as FasterRCNN, SSD, and YOLOv5 by 33.5%, 7.7%, and 7%, respectively. It has a lower omission rate and higher detection accuracy, and it is capable of handling small-target detection tasks in complex fire environments. This can provide support for UAV patrol and rescue applications from a high-altitude perspective. Full article

Many countries around the world are rapidly advancing sustainable development (SD) through the exploitation of clean energy sources such as solar and wind energy, which are becoming the core of the sustainable energy transition. In recent years, the continuous advancement of Earth system models (ESMs) has facilitated numerous studies utilizing them to predict long-term and large-scale meteorological elements, consequently enabling forecasts of wind and solar energy. These forecasts provide critical guidance for formulating national renewable energy policies. Nevertheless, the current literature on ESMs predicting wind and solar energy lacks sufficient integration. Hence, to comprehend the focal points and future research prospects, we conducted this systematic review, employing four academic search tools to comprehensively analyze the relevant literature from the past five years. We summarized the general analytical process and compared the content and conclusions of the literature. The study reveals that future photovoltaic (PV) potential for electricity generation may increase in certain regions but decrease in others, while the global potential for concentrated solar power (CSP) may diminish, influenced by diverse factors and displaying significant regional disparities. In addition, wind resource trends vary in different regions, and forecasts exhibit considerable uncertainty. Therefore, many studies have corrected wind speeds prior to predicting wind energy. Subsequent research endeavors should concentrate on optimizing ESMs, investigating the impacts of technological innovation, and enhancing the prediction and analysis of extreme weather events. Full article

The C(sp²)-aryl sulfonate functional group is found in bioactive molecules, but their synthesis can involve extreme temperatures (>190 °C or flash vacuum pyrolysis) and strongly acidic reaction conditions. Inspired by the 1917 Tyrer industrial process for a sulfa dye that involved an aniline N(sp²)-SO₃ intermediate en route to a C(sp²)-SO₃ rearranged product, we investigated tributylsulfoammonium betaine (TBSAB) as a milder N-sulfamation to C-sulfonate relay reagent. Initial investigations of a stepwise route involving TBSAB on selected anilines at room temperature enabled the isolation of N(sp²)-sulfamate. Subsequent thermal rearrangement demonstrated the intermediary of a sulfamate en route to the sulfonate; however, it was low-yielding. Investigation of the N-sulfamate to C--sulfonate mechanism through control experiments with variation at the heteroatom positions and kinetic isotope experiments (KIE^H/D) confirmed the formation of a key N(sp²)-SO₃ intermediate and further confirmed an intermolecular mechanism. Furthermore, compounds without an accessible nitrogen (or oxygen) lone pair did not undergo sulfamation- (or sulfation) -to-sulfonation under these conditions. A one-pot sulfamation and thermal sulfonation reaction was ultimately developed and explored on a range of aniline and heterocyclic scaffolds with high conversions, including N(sp²)-sulfamates (O(sp²)-sulfates) and C(sp²)-sulfonates, in up to 99 and 80% (and 88% for a phenolic example) isolated yield, respectively. Encouragingly, the ability to modulate the ortho-para selectivity of the products obtained was observed under thermal control. A sulfonated analog of the intravenous anesthetic propofol was isolated (88% yield), demonstrating a proof-of-concept modification of a licensed drug alongside a range of nitrogen- and sulfur-containing heterocyclic fragments used in drug discovery. Full article

The energy sector is the main source of greenhouse gases, so it has the highest potential for improvement. The improvements can be achieved by generating energy from renewable sources. It is necessary to combine production from renewable sources with storage systems. Thermal energy storage using concentrated solar power systems is a promising technology for dispatchable renewable energy that can guarantee a stable energy supply even in remote areas without contributing to greenhouse gas emissions during operation. However, it must be emphasised that greenhouse gases and other impacts can occur during the production process of concentrating solar system components. This paper analyses the receiver design to produce thermal energy for the existing CSP dish plant at the Energy Center of the Politecnico di Torino. The plant is designed to produce electrical energy in the spring and summer periods. In addition to this energy production, the CSP can be adopted to produce thermal energy, through hot water, during the less favourable periods of the year in terms of global solar radiation. The surface heat flux is calculated in the first part of the analysis to obtain the maximum internal temperature in the receiver, which is 873.7 °C. This value is a constraint for the choice of material for the solar receiver. A life cycle assessment is performed to compare the emissions generated during the production of the main components of the CSP system with the emissions generated by the methane-fuelled water heater to produce the same amount of thermal energy. It can be concluded that the production of the main components of the CSP system results in lower greenhouse gas emissions than the operational phase of a conventional system. Given the assumptions made, the utilization of methane leads to the emission of approximately 12,240 kg of CO₂, whereas the production of the CSP system results in emissions totalling 5332.8 kg of CO₂ equivalent Full article

Concentrating solar power (CSP) technology with thermal energy storage (TES) could contribute to achieving a net zero emissions scenario by 2050. Calcium looping (CaL) is one of the potential TES processes for the future generation of CSP plants coupled with highly efficient power cycles. Research on CaL as a system for thermochemical energy storage (TCES) has focused on efficiency enhancement based on hybridization with other renewable technologies. This work proposes a novel solid management system to improve the efficiency of a CaL TCES system. The inclusion of a solid–solid separation unit after the carbonation step could lead to energy and size savings. The role of segregation between carbonated and calcined material on plant requirements is assessed, given the experimental evidence on the potential classification between more and less carbonated particles. The results show lower energy (up to 12%) and size (up to 76%) demands when the circulation of less carbonated material through the CaL TCES system diminishes. Moreover, under a classification effectiveness of 100%, the retrieval energy could increase by 32%, and the stored energy is enhanced by five times. The present work can be a proper tool to set the design and size of a CaL TCES system with a partial separation of the carbonated material. Full article

Hot stamping (or press hardening) is a new technology that is widely used in the production of advanced high-strength steel parts for automotive applications. Electrochemical measurements, including potentiodynamic polarization and electrochemical impedance spectroscopy (EIS), and accelerated corrosion tests (the neutral salt spray test and periodic immersion test) were conducted on press-hardened samples produced from uncoated (cold-rolled and cold strip production (CSP) hot-rolled) and Al–Si-coated press-hardened steels to elucidate their distinct anti-corrosion mechanisms. The cross-sectional micromorphology and element distribution of three types of press-hardened steels after a neutral salt spray test were observed using scanning electron microscopy (SEM) and energy-dispersive X-ray analysis (EDAX). The corrosion resistance of Al–Si-coated press-hardened steel was found to be significantly diminished following the hot stamping process due to the presence of microcracks and elevated iron content in the coating subsequent to austenitizing heat treatment. On the other hand, the corrosion resistance of uncoated press-hardened sheets produced from cold-rolled and CSP hot-rolled press-hardened steel was found to be proximal due to their nearly identical composition and microstructure (fully martensite) after the hot stamping process. Considering the high efficiency and energy-saving properties of hot-rolled press-hardened steel, it holds the potential to replace cold-rolled and even aluminum–silicon-coated press-hardened steel in automobile manufacturing. Full article