Increasing Energy Demand Research Articles

Toward Carbon‐Negative Methanol Production from Biogas: Intensified Membrane Reactor

AbstractThe modern world's major challenges, such as global warming, air pollution, and increasing energy demands, escalate the importance of sustainable development and transition toward renewables using innovative and environmentally friendly solutions, such as intensifying chemical processes, to reduce carbon footprints effectively. Aiming to enhance the process toward negative carbon emissions, this perspective explores the intensified membrane reactors for reducing the energy intensity of converting biogas into methanol, a versatile chemical feedstock, and renewable liquid fuel. Syngas and methanol synthesis processes, catalysts, and membranes were explored, and novel reactor designs were proposed. Introduction of selective membranes into the catalytic reaction zone to combine synthesis separation steps could enhance the system efficiency and intensify the process by recycling energy and materials, besides reducing costs and required energy for the separation process: the continuous harnessing of products shifts reactions toward desired species while recycling energy and materials enhances the process efficiency, and separating water from methanol reduces the required energy and costs of extra processes for methanol separation. The successful implementation of this technology holds significant promise for sustainable developments in producing chemicals and renewable fuel from renewable biogas and reducing methane and carbon dioxide emissions toward achieving carbon‐negative technologies.

Exploring advanced microwave strategy for the synthesis of two-dimensional energy materials

The rapid pace of technology and increasing energy demands underscore the urgent need for eco-friendly materials with exceptional energy conversion and storage capabilities. Two-dimensional (2D) energy materials, characterized by unique physicochemical properties, hold great promise in renewable energy conversion, catalysis, and electronics. Nevertheless, conventional synthesis methods often falter in balancing high quality, high yield, and cost-effectiveness, presenting substantial obstacles to their large-scale application. Microwave-assisted synthesis, characterized by its rapid and efficient process, emerges as a promising approach to surmount these limitations. This review meticulously examines the pivotal role of microwave-assisted synthesis in the preparation of 2D materials, highlighting its profound impact on enhancing material quality and production efficiency. By scrutinizing the unique physical properties of microwaves and their applications in material synthesis, the review elucidates the innovative contributions of microwave technology to materials science. Furthermore, it delves into the intricate influence of microwave parameter control on the synthesis process and resultant material properties, offering insight into the potential of microwave technology for the precise modulation of material structure and functionality. This comprehensive analysis underscores microwave-assisted synthesis as a viable solution for overcoming current challenges, thereby advancing the development of high-performance 2D energy materials.

Performance Evaluation of Nano-Enhanced Phase Change Materials for Thermal Energy Storage: An Experimental Study

In rapidly developing economies, the increasing energy demand and fossil fuel consumption have made the need for renewable energy sources and efficient thermal energy storage (TES) solutions more urgent than ever. This study focuses on enhancing the thermal energy storage capabilities of paraffin-based phase change materials (PCMs) by incorporating Al2O3, MgO, and CuO nanoparticles. The evaluation of nano-enhanced PCMs focused on their melting temperatures, thermal storage capacities, thermal conductivities, and charge/discharge times. The experimental results revealed significant changes in the thermal properties of the nano-enhanced PCMs compared to pure paraffin. The melting temperature was raised by 2°C due to Al2O3 nanoparticles, whereas CuO and MgO nanoparticles decreased it by 1.7°C and 1.8°C, respectively. Compared to pure paraffin, Al2O3-PW, MgO-PW, and CuO-PW exhibited improvements of 13%, 39%, and 48% in thermal conductivities, respectively. CuO-doped paraffin showed an 11.8% decrease in discharge time, suggesting its suitability for rapid heat transfer applications like defrosting systems or thermal management in electronics. On the other hand, paraffin doped with MgO showed a minimal 2.24% reduction in discharge time, indicating its effectiveness in applications requiring heat retention, particularly for improved thermal insulation in building materials. The results highlighted the potential of nano-enhanced PCMs in energy storage and construction is underlined, offering a sustainable approach to improving energy efficiency in various sectors.

Transition metal-assisted layer-by-layer binder free deposition for high-performance energy storage devices

The increasing energy demands of the world necessitate the development of advanced energy storage systems. Hybrid supercapacitors (HSCs) have emerged as promising candidates, combining the high specific power density (PS) of supercapacitors (SCs) with the high specific energy density (ES) of batteries (BATs). However, its performance is dependent on the properties of electrode materials, which need enhancements in conductivity, surface area, and electrochemical stability. In this study, we utilized magnetron sputtering technique for exploring the potential of interface engineering to improve the electrochemical performance of tungsten disulfide (WS2) as a battery grade electrode material by incorporating chromium (Cr) and titanium (Ti) as an interfacial layer. This strategic modification significantly increased the conductivity, charge transfer efficiency, and structural stability of the WS2 electrode. Electrochemical experimentation in both half-cell and full-cell configurations revealed that the WS2/Cr and WS2/Ti electrode exhibits superior CS [2400 and 3800] F/g, respectively compared to pristine WS2. Fabricated WS2/Cr//AC and WS2/Ti//AC attained ES [95 and 117] Wh/kg and PS [6800 and 8500] W/kg, respectively. The outcomes from the electrochemical testing further demonstrated the superior cyclic stability of WS2/Cr//AC and WS2/Ti//AC with [96.5 and 98.3] % which shows that Cr and Ti as an interfacial layer not only mitigates the limitations of WS2 but also enables the devices to achieve higher performance metrics, underscoring the critical role of interface engineering in advancing HSCs technologies.

Effect of Architecture and Inference Parameters of Artificial Neural Network Models in the Detection Task on Energy Demand

Artificial neural network models for the task of detection are used in many fields and find various applications. Models of this kind require adequate computational resources and thus require adequate energy expenditure. The increase in the number of parameters, the complexity of architectures, and the need to process large data sets significantly increase energy consumption, which is becoming a key sustainability challenge. Optimization of computing and the development of energy-efficient hardware technologies are essential to reduce the energy footprint of these models. This article examines the effect of the type of model, as well as its parameters, on energy consumption during inference. For this purpose, sensors built into the graphics card were used, and software was developed to measure the energy demand of the graphics card for different architectures of YOLO models (v8, v9, v10), as well as for different batch and model sizes. This study showed that the increase in energy demand is not linearly dependent on batch size. After a certain level of batch size, the energy demand begins to decrease. This dependence does not occur only for n/t size models. Optimum utilization of computing power due to the number of processed images for the studied models occurs at the maximum studied batch size. In addition, tests were conducted on an embedded device.

GAPS OF INDIAN ELECTRICAL ENERGY SECTOR AND ITS OPTIMAL MITIGATION BY USING OPTIMAL UTILIZATION OF INDIAN RENEWABLE ENERGY POLICY WITH THE HELP OF THE P&O MPPT TECHNIQUE

Developing countries, especially, India, depend importantly on energy sources to perform their country’s industrial and economic activities. Mainly the two factors continuous population growth of the country and the rapid growth rate of industrialization of the country, the gap between electrical energy supply and demand for electrical energy is slowly and consistently increasing. To resolve this unevenness, there is a jointly planned attempt is required to enhance the contribution of renewable energy in the all over mix of energy. Despite these attempts, unexpected surges caused by the sector of domestic energy consumption could lead to important shortfalls between energy requirements at peak demand and available supply in India. As a solution to this challenge, the Union government of India has launched a new policy, named PM SURYA GHAR: MUFT BIJLI YOJANA, targeted to handle this crucial problem head-on. This initiative requires addressing the increasing energy demand by promoting the utilization of solar power in households throughout the length and breadth of the country. With the implementation techniques of Photo voltaic optimization, this analysis explores how such types of strategies can play a significant role in filling the gap between the energy supply-demand in the Indian context. Employing the solar energy potential and optimizing and utilization of solar energy, creates a path to not only meet the enhancing energy requirements but also creates the path for a more environmentally friendly and sustainable energy in India. By integration of innovative technologies and solutions of renewable energy holds the key to ensuring a balanced, sustainable, stable energy supply for the future of India and country’s growth and development.

Tool–Branch Interaction Mechanism of Impact-Pruning Process Based on Finite Element Method

This study addresses the necessity for a more profound comprehension of the mechanical behavior and fracture mechanisms of tree branches during impact pruning. The methodologies of the research are to develop a failure model of impact-cutting mechanics and a tool–branch interaction model using the finite element method (FEM). The validation of the model was conducted through the measurement of cutting forces and cross-sectional morphology in the field. A comparative analysis between experimental and simulation data revealed an average relative error below 15% for cutting force and below 10% for the cross-sectional ratio, thereby confirming the accuracy of the model. The findings indicate the presence of plastic deformation within the cutting zone, with elastic deformation prevailing in the surrounding region. As the branch approaches the yield point, the phenomenon of plastic deformation intensifies, resulting in a notable increase in internal energy demands, particularly in larger branches. The optimal pruning diameter was identified as 15 mm. An increase in cutting velocity raises the peak cutting force by 460.9 N per m/s, while a 1° increase in the blade wedge angle adds 34.9 N. A reduction in normal stress by increasing the tool back angle improves energy efficiency. This study provides insights to optimize pruning practices, enhancing efficiency and precision.

Sustainability Prediction by Evaluating the Emergy of a Co-Treatment System for Municipal Wastewater and Acidic Water Using Intermittent Electrocoagulation

The objective of this research was to evaluate the sustainability of a co-treatment system that combines Municipal Wastewater (MW) and Acid Mine Drainage (AMD) through the technique of intermittent electrocoagulation, applied as an advanced solution to improve contaminant removal efficiency and optimize energy balance. Four scenarios were analyzed: Treatment I (with a 1/7 ratio of urban wastewater to AMD), Treatment II (which includes an artificial wetland), Treatment IIIa (which introduces electrocoagulation to enhance sulfate removal and pH regulation), and Treatment IIIb (which employs a 1/15 ratio of AMD to eutrophic water). The methodology focused on calculating key sustainability indicators such as the Net Yield Ratio (EYR), Emergy Inversion Ratio (EIR), Environmental Loading Ratio (ELR), and Sustainability Index (SI), in order to assess the impact of each technology on the energy efficiency and environmental load of the system. The results showed that, although Treatment IIIa was effective in contaminant removal, the EIR increased to 0.18 and the ELR rose to 0.62, indicating a higher reliance on non-renewable inputs due to increased energy demand. However, Treatment IIIb, which combines electrocoagulation with eutrophic water, significantly improved the sustainability of the system, achieving an SI of 2.31 and an ELR of 1.22, reflecting a reduction in energy efficiency due to intensive use of external resources, but overall greater sustainability compared to the other scenarios. This research concludes that intermittent electrocoagulation, when integrated with synergistic resources like eutrophic water, can enhance contaminant removal efficiency and improve the use of renewable resources, minimizing environmental load and increasing the sustainability of wastewater treatment systems.

Enhancing energy control for a hybrid system comprising a wind turbine, diesel generator, and storage systems

The increase in demand for electrical energy has made renewable energy sources, such as wind power, increasingly attractive. However, intermittency and variability represent the major problems of these types of energies. The hybridization of several energy sources allows to have a reliable and efficient supply system. This paper was interested in the control of a hybrid energy system, which includes a wind turbine, storage systems (batteries and super-capacitors) and a conventional diesel generator, with the aim of generating constant power. A control strategy is developed taking into account the various constraints of the hybrid system. Both of storage systems as well as the diesel generator operate according to the modes presented in the supervision algorithm to absorb and compensate the fluctuation of the wind energy and reach to a constant energy flow. The super-capacitor operates before the battery to absorb the power peaks in both charge and discharge modes. The hybrid system is simulated using MATLAB/Simulink software, and the results are provided in order to show the effectiveness of this control strategy.

Developmental nicotine exposure alters cardiovascular structure and function in neonatal and juvenile rats.

Here we test the hypothesis that continuous nicotine exposure throughout pre- and postnatal development (developmental nicotine exposure, DNE) alters cardiovascular structure and function in neonatal and juvenile rats. Echocardiography showed that DNE reduced left ventricular mass, left ventricular outflow tract (LVOT) diameter, and posterior wall thickness, but only in females. Both male and female DNE rats had a lower end-systolic volume, higher ejection fraction, and increased fractional shortening, with unchanged stroke volume and cardiac output. Left ventricular single cardiac myocytes from male and female DNE animals exhibited increased calcium-evoked maximal tension with no effect on EC50. Tail-cuff plethysmography in awake rats showed that DNE males had lower systolic blood pressure and higher heart rate than control males. No significant changes in preload, afterload, or the in vitro renal artery response to vasodilators was observed. The results suggest that DNE enhances myocyte tension-generating capacity, possibly compensating for an unknown developmental insult, which may differ in males and females. While this adaptation maintains normal resting cardiac function, it may lead to reduced cardiac reserve, increased energy demand, and elevated oxidative stress, potentially compromising both short-and-long-term cardiovascular health in developing neonates.

Assessing Photo-Voltaic Potential in Urban Environments: A Comparative Study between Aerial Photogrammetry and LiDAR Technologies

Abstract. Urban development and population growth have significantly increased energy demands, predominantly met by non-renewable resources, negatively impacting nature and climate. Consequently, there has been a global shift towards renewable energy sources, with solar energy being widely adopted. Photovoltaic (PV) potential measures the usable electricity from solar energy using PV technology. With conventional methods, estimating PV potential involves converting 3D point cloud data to 2.5D elevation models, which can affect the accuracy of the estimation. A research gap exists in using adequate 3D point cloud datasets for PV potential estimation considering roof surface area and the surface normal vectors. This study compares aerial photogrammetry and aerial LiDAR point clouds for PV potential estimation against the DSM-based approach. Accurate PV potential estimation must consider solar incidence, roof area, azimuth, tilt angles, and PV efficiency. Traditional 2.5D methods often overlook crucial azimuth and tilt data, limiting the accuracy of the PV estimation. Converting 3D data to 2.5D may result in information loss, while 3D analyses offer higher accuracy. To investigate the mentioned gaps, this research aims to evaluate the capabilities of photogrammetry and LiDAR for urban PV potential estimation, highlighting their feasibility and accuracy over 2.5D methods.

Data-independent acquisition proteomic analysis of the brain microvasculature in Alzheimer’s disease identifies major pathways of dysfunction and upregulation of cytoprotective responses

Brain microvascular dysfunction is an important feature of Alzheimer’s disease (AD). To better understand the brain microvascular molecular signatures of AD, we processed and analyzed isolated human brain microvessels by data-independent acquisition liquid chromatography with tandem mass spectrometry (DIA LC–MS/MS) to generate a quantitative dataset at the peptide and protein level. Brain microvessels were isolated from parietal cortex grey matter using protocols that preserve viability for downstream functional studies. Our cohort included 23 subjects with clinical and neuropathologic concordance for Alzheimer’s disease, and 21 age-matched controls. In our analysis, we identified 168 proteins whose abundance was significantly increased, and no proteins that were significantly decreased in AD. The most highly increased proteins included amyloid beta, tau, midkine, SPARC related modular calcium binding 1 (SMOC1), and fatty acid binding protein 7 (FABP7). Additionally, Gene Ontology (GO) enrichment analysis identified the enrichment of increased proteins involved in cellular detoxification and antioxidative responses. A systematic evaluation of protein functions using the UniProt database identified groupings into common functional themes including the regulation of cellular proliferation, cellular differentiation and survival, inflammation, extracellular matrix, cell stress responses, metabolism, coagulation and heme breakdown, protein degradation, cytoskeleton, subcellular trafficking, cell motility, and cell signaling. This suggests that AD brain microvessels exist in a stressed state of increased energy demand, and mount a compensatory response to ongoing oxidative and cellular damage that is associated with AD. We also used public RNAseq databases to identify cell-type enriched genes that were detected at the protein level and found no changes in abundance of these proteins between control and AD groups, indicating that changes in cellular composition of the isolated microvessels were minimal between AD and no-AD groups. Using public data, we additionally found that under half of the proteins that were significantly increased in AD microvessels had concordant changes in brain microvascular mRNA, implying substantial discordance between gene and protein levels. Together, our results offer novel insights into the molecular underpinnings of brain microvascular dysfunction in AD.

Hybrid modeling approach for precise estimation of energy production and consumption based on temperature variations

This study introduces an advanced mathematical methodology for predicting energy generation and consumption based on temperature variations in regions with diverse climatic conditions and increasing energy demands. Using a comprehensive dataset of monthly energy production, consumption, and temperature readings spanning ten years (2010–2020), we applied polynomial, sinusoidal, and hybrid modeling techniques to capture the non-linear and cyclical relationships between temperature and energy metrics. The hybrid model, which combines sinusoidal and polynomial functions, achieved an accuracy of 79.15% in estimating energy consumption using temperature as a predictor variable. This model effectively captures the seasonal and non-linear consumption patterns, demonstrating a significant improvement over conventional models. In contrast, the polynomial model for energy production, while yielding partial accuracy (R² = 0.65), highlights the need for more advanced techniques to fully capture the temperature-dependent nature of energy production. The results indicate that temperature variations significantly affect energy consumption, with higher temperatures driving increased energy demand for cooling, while lower temperatures affect production efficiency, particularly in systems like hydropower. These findings underscore the necessity for integrating sophisticated models into energy planning to ensure resilience in energy systems amidst climate variability. The study offers critical insights for policymakers to optimize energy generation and distribution in response to changing climatic conditions.

Celebrating Ten Years of Covalent Organic Frameworks for Solar Energy Conversion: Past, Present and Future

AbstractAccelerated anthropogenic emission of greenhouse gases due to increasing energy demands has created a negative impact on our planet. Therefore, the replacement of fossil by renewable energy resources has become of paramount interest, both societally and scientifically. It is within this setting that organic photocatalysts have emerged as a new generation of earth‐abundant catalysts for the conversion of solar radiation into chemical energy. In 2014, the first example of a covalent organic framework (COF) photocatalyst for the hydrogen evolution reaction was reported by our group, which has not only marked the beginning of COF photocatalysis for solar fuel production but also helped to accelerate research into “soft photocatalysis” based on porous polymers in general. In the last decade, significant progress has been made toward developing COFs as robust, molecularly precise platforms emulating artificial photosynthesis. This mini‐review commemorates the 10th anniversary of COF photocatalysis and gives a brief historical overview of the milestones in the field since its inception in 2014. We review milestones in the development of COFs for solar fuel production and related photocatalytic transformations, including hydrogen evolution, oxygen evolution, overall water splitting, CO2 reduction, N2 fixation, oxygen reduction, and alcohol oxidation. We discuss lessons learned for the design of structure‐property‐function relationships in COF photocatalysts, and future perspectives and challenges for the field of “soft photocatalysis” are given.

Celebrating Ten Years of Covalent Organic Frameworks for Solar Energy Conversion: Past, Present and Future.

Accelerated anthropogenic emission of greenhouse gases due to increasing energy demands has created a negative impact on our planet. Therefore, the replacement of fossil by renewable energy resources has become of paramount interest, both societally and scientifically. It is within this setting that organic photocatalysts have emerged as a new generation of earth-abundant catalysts for the conversion of solar radiation into chemical energy. In 2014, the first example of a covalent organic framework (COF) photocatalyst for the hydrogen evolution reaction was reported by our group, which has not only marked the beginning of COF photocatalysis for solar fuel production but also helped to accelerate research into "soft photocatalysis" based on porous polymers in general. In the last decade, significant progress has been made toward developing COFs as robust, molecularly precise platforms emulating artificial photosynthesis. This mini-review commemorates the 10th anniversary of COF photocatalysis and gives a brief historical overview of the milestones in the field since its inception in 2014. We review milestones in the development of COFs for solar fuel production and related photocatalytic transformations, including hydrogen evolution, oxygen evolution, overall water splitting, CO2 reduction, N2 fixation, oxygen reduction, and alcohol oxidation. We discuss lessons learned for the design of structure-property-function relationships in COF photocatalysts, and future perspectives and challenges for the field of "soft photocatalysis" are given.

Reduced neurovascular coupling of the visual network in migraine patients with aura as revealed with arterial spin labeling MRI: is there a demand-supply mismatch behind the scenes?

BackgroundAlthough neuroimaging investigations have consistently demonstrated that “hyperresponsive” and “hyperconnected” visual cortices may represent the functional substrate of cortical spreading depolarization in patients with migraine with aura, the mechanisms which underpin the brain “tendency” to ignite the cortical spreading depolarization and, consequently, aura phenomenon are still matter of debate. Considering that triggers able to induce aura phenomenon constrain brain to increase global (such as physical activity, stressors and sleep abnormalities) or local (such as bright light visual stimulations) energy demand, a vascular supply unable to satisfy the increased energy requirement could be hypothesized in these patients.MethodsTwenty-three patients with migraine with aura, 25 patients with migraine without aura and 20 healthy controls underwent a 3-Tesla MRI study. Cerebral blood flow and local functional connectivity (regional homogeneity) maps were obtained and registered to the MNI space where 100 cortical regions were derived using a functional local-global normative parcellation. A surrogate estimate of the regional neurovascular coupling for each subject was obtained at each parcel from the correlation coefficient between the z-scored ReHo map and the z-scored cerebral blood flow maps.ResultsA significantly higher regional cerebral blood flow across the visual cortex of both hemispheres (i.e. fusiform and lingual gyri) was detected in migraine with aura patients when compared to patients with migraine without aura (p < 0.05, corrected for multiple comparisons). Concomitantly, a significantly reduced neurovascular coupling (p < 0.05, false discovery rate corrected) in the primary visual cortex parcel (VIS-4) of the large-scale visual network was observed in the left hemisphere of patients with migraine with aura (0.23±0.03), compared to both patients with migraine without aura (0.32±0.05) and healthy controls (0.29±0.05).ConclusionsVisual cortex neurovascular “decoupling” might represent the “link” between the exposure to trigger factors and aura phenomenon ignition. While physiological vascular oversupply may compensate neurovascular demand-supply at rest, it becomes inadequate in case of increased energy demand (e.g. when patients face with trigger factors) paving the way to the aura phenomenon ignition in patients with migraine with aura. Whether preventive treatments may exert their therapeutic activity on migraine with aura restoring the energy demands and cerebral blood flow trade-off within the visual network should be further investigated.

Advancements in Solid Oxide Fuel Cell Technology: Bridging Performance Gaps for Enhanced Environmental Sustainability

In light of the anticipated 50% increase in global energy demand by 2050, the demand for innovative, environmentally conscious, efficient, and dependable energy technologies is paramount. Solid oxide fuel cells (SOFCs) offer a promising solution for sustainable energy production. This comprehensive review provides a detailed analysis of SOFCs, covering their fundamentals, materials, performance, and diverse applications, while also addressing technological challenges and future prospects. The review emphasizes the key advantages of SOFCs, including their high efficiency of up to 60% and minimal environmental impact. It explores the significance of impurity resistance and durability in materials and manufacturing processes for SOFC components. Comparative evaluations demonstrate the superior energy efficiency and ecological effects of SOFCs compared to other fuel cell technologies. SOFCs’ versatility and potential are showcased through their applications in transportation, power generation and storage, portable devices, and residential usage. However, challenges such as cost, longevity, reliability, and integration with other energy systems are identified, emphasizing the need for supportive policies and regulations.

Effects of wind farms on raptors: A systematic review of the current knowledge and the potential solutions to mitigate negative impacts

AbstractWind farms are a clean and efficient source of renewable energy. However, they cause negative impacts on raptors. Here, we present a review of the existing scientific literature on the effects of wind farms on raptors' ecology with a particular interest in the potential solutions. After collecting 216 studies, we found a consensus in the literature that raptors exhibit avoidance behaviors, and that the abundance of raptors decreases after wind farm installation, although it might recover over time. The position of wind farms on mountaintop ridges poses a particular danger to large soaring raptors, as they rely on orographic uplift to gain altitude. Adult mortality significantly affects population dynamics, particularly in endangered species, but young inexperienced individuals show a higher collision risk. The combination of different methods including field monitoring, GPS telemetry and systematic search for carcasses is an adequate approach to further investigate the problem and solutions. Shutdowns on demand, the installation of deterrents, turbine micro‐sitting and the repowering of wind farms have been suggested as potential solutions, although results are contradictory and case‐specific. Furthermore, it is essential to report the potential occurrence of conflicts of interest in scientific papers, as they can influence the interpretation of the results. Finally, from a future perspective, it is crucial to assess the effectiveness of solutions to mitigate the negative effects of wind farms to promote raptor conservation. This becomes increasingly relevant in the context of renewable energy development and increasing energy demand worldwide.

Preparation of molybdenum disulfide/bentonite nanohybrid and its tribological properties as lubricant for water-based drilling fluids

In recent years, with the increase in energy demand and gradual scarcity of medium and shallow oil and gas resources, oil and gas exploration has shifted to special wells such as deep wells, ultra-deep wells, and extended reach wells. These complex wellbore structures inevitably increase the torque and friction between the casing and the drill pipe during drilling, which aggravates friction and wear, and leads to accidents such as drill sticking and drill breakage in severe cases. In this study, molybdenum disulfide/bentonite (MoS2/Bent) nanohybrids as drilling fluid lubricant were synthesized by hydrothermal method using sodium molybdate (Na2MoO4) and thiourea (CH4N2S) as raw materials and bentonite as carrier. The as-synthesized MoS2/Bent nanohybrid was characterized by X-ray powder diffractometer, transmission electron microscopy, Fourier transform infrared spectroscopy, and the high temperature resistance and tribological properties of MoS2/Bent nanohybrid were evaluated in base slurry. The results show that the friction coefficient of MoS2/Bent nanohybrid drilling fluid before aging is reduced by 74 % and the wear rate is reduced by 97 % compared with the base slurry. After high-temperature aging at 240 °C, the friction coefficient is reduced by 77 % and the wear rate is reduced by 90 %. The excellent friction reducing and antiwear performance is attributed to the formation of low shear strength MoS2 deposition film and oxide tribofilm on the surface of the friction pair during the rubbing process.

Can Europe recover its photovoltaic manufacturing capacity?

Can Europe recover its photovoltaic manufacturing capacity? Antonio Urbina, from the Department of Sciences and Institute for Advanced Materials and Mathematics (INAMAT2), Universidad Pública de Navarra (UPNA), based at Pamplona in Spain, investigates whether Europe can recover its capacity for photovoltaic manufacturing. The energy transition is contributing worldwide to reducing greenhouse gas emissions, the leading cause of climate change. This has been achieved, despite a continually increasing energy demand in all economic sectors, by an impressive growth of installed renewable capacity, the rapid electrification of some sectors (home heating, transport) and more efficient energy use.