This review paper organizes and summarizes the literature on Vertical Greenery Systems (VGS) when used as passive tool for energy savings in buildings. First, with the information obtained in the ...reviewed literature some key aspects to consider when working with VGS are clarified, such as the classification systems, the climate influence, the plant species used and the different operating mechanisms. Then, the main conclusions of this literature, sorted by construction system (Green Walls or Green Façades) and climatic situation, are summarized. In general, it can be concluded that VGS provide great potential in reducing energy consumption in buildings, especially in the cooling periods. However, a lack of data on operation during the heating period as well as during the whole year has been found. On the other hand, results show that the investigations of VGS are not equally distributed around the world, being basically concentrated in Europe and Asia. Moreover, the review concludes that some aspects must be studied in depth, such as which species are the most suitable for each climate, influence on energy savings of the façade orientation, foliage thickness, presence of air layers, and finally, substrate layer composition and thickness in the case of green walls.
Increasing global building energy demand, with the related economic and environmental impact, upsurges the need for the design of reliable energy demand forecast models. This work presents kCNN-LSTM, ...a deep learning framework that operates on the energy consumption data recorded at predefined intervals to provide accurate building energy consumption forecasts. kCNN-LSTM employs (i) k−means clustering – to perform cluster analysis to understand the energy consumption pattern/trend; (ii) Convolutional Neural Networks (CNN) – to extract complex features with non-linear interactions that affect energy consumption; and (iii) Long Short Term Memory (LSTM) neural networks – to handle long-term dependencies through modeling temporal information in the time series data. The efficiency and applicability of kCNN-LSTM were demonstrated using a real time building energy consumption data acquired from a four-storeyed building in IIT-Bombay, India. The performance of kCNN-LSTM was compared with the k-means variant of the state-of-the-art energy demand forecast models in terms of well-known quality metrics. It is also observed that the accurate energy demand forecast provided by kCNN-LSTM due to its ability to learn the spatio-temporal dependencies in the energy consumption data makes it a suitable deep learning model for energy consumption forecast problems.
•kCNN-LSTM, a deep learning based energy consumption forecast model, is presented.•Timestamp based features generated from the timestamp provides parameter-rich data.•k-means clustering analyzes the trend in energy consumption data.•CNN-LSTM captures spatio-temporal characteristics in energy consumption data.•A case study on KReSIT building energy consumption data is presented.
Wind energy as one of the renewable energies is serving as an indispensable role in generating new electric power. The worldwide installation of wind farms has considerably increased recently. To ...extract more wind resources, multi-megawatt wind turbines are usually designed and constructed with large rotors and slender tower. These flexible structures are susceptible to external dynamic excitations such as wind, wave and seismic loads. The excessive vibrations can compromise the wind energy conversion, lead to the structural fatigue damage and even result in the catastrophic failure of wind turbines in harsh environmental conditions. Various control devices have been proposed and used to mitigate the unwanted vibrations of wind turbines to enhance their safety and serviceability. This paper aims to provide a state-of-the-art review of the current vibration control techniques and their applications to wind turbines. Firstly, the widely used control strategies in engineering structures are briefly introduced. Their applications to suppress the adverse vibrations of the structural components of wind turbines, mainly the tower and blades, are then reviewed and discussed in detail. It can be concluded that the vibration mitigation of wind turbines is very challenging due to the fact that the dynamic behaviours of wind turbines are very complicated, which are associated with the aerodynamics, rotation of the blades, interaction between the tower and rotating blades, and soil-structure interaction, etc. Moreover, it is a challenge to straightforwardly use many of the conventional control devices because of the limited spaces in the tower and blades.
•The commonly used control approaches in wind turbines are briefly presented.•The applications and control effectiveness of various control devices used in wind turbines are comprehensively reviewed.•The remaining challenges of the conventional control methods in wind turbines are discussed.
Industries are working to minimize their reliance on petrochemicals and petroleum-based industrial components and replace them with biobased, sustainable, and environmentally friendly alternatives ...due to the global warming emergency caused by the uncontrolled production of greenhouse gases. The agricultural waste provides large volumes of lignocellulosic biomass, a sustainable resource material to develop a wide portfolio of bioproducts. Recent developments in integrated biorefineries have enhanced the utilization of waste lignocellulose components to generate biofuels, platform chemicals, resins, bioplastics, additives, and other biobased materials for a variety of applications. Here in this review, we have summarized recent advancements in the processing of lignocellulosic biomass from agricultural waste. Additionally, this review thoroughly discussed the recent technological advancements in the utilization of various lignocellulose biomass constituents for biofuels, biocomposites, and bioplastics. Finally, an assessment of the currently existing literature gaps and prospective future perspectives for the development of lignocellulosic biomass from agricultural waste has been conducted.
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•Circular economy principles can help in reducing the impact on natural resources.•Researchers and businesses are showing interest in lignocellulose biorefineries.•LCB offers renewable feedstock for many application areas i.e. bioplastics and fuel.•This review gives readers a clearer grasp of how LCB is used in circular economies.
Lithium metal is one of the most attractive anode materials for electrochemical energy storage. However, the growth of Li dendrites during electrochemical deposition, which leads to a low Coulombic ...efficiency and safety concerns, has long hindered the application of rechargeable Li-metal batteries. Here we show that a 3D current collector with a submicron skeleton and high electroactive surface area can significantly improve the electrochemical deposition behaviour of Li. Li anode is accommodated in the 3D structure without uncontrollable Li dendrites. With the growth of Li dendrites being effectively suppressed, the Li anode in the 3D current collector can run for 600 h without short circuit and exhibits low voltage hysteresis. The exceptional electrochemical performance of the Li-metal anode in the 3D current collector highlights the importance of rational design of current collectors and reveals a new avenue for developing Li anodes with a long lifespan.
Ion migration has been proposed as a possible cause of photovoltaic current-voltage hysteresis in hybrid perovskite solar cells. A major objection to this hypothesis is that hysteresis can be reduced ...by changing the interfacial contact materials; however, this is unlikely to significantly influence the behaviour of mobile ionic charge within the perovskite phase. Here, we show that the primary effects of ion migration can be observed regardless of whether the contacts were changed to give devices with or without significant hysteresis. Transient optoelectronic measurements combined with device simulations indicate that electric-field screening, consistent with ion migration, is similar in both high and low hysteresis CH
NH
PbI
cells. Simulation of the photovoltage and photocurrent transients shows that hysteresis requires the combination of both mobile ionic charge and recombination near the perovskite-contact interfaces. Passivating contact recombination results in higher photogenerated charge concentrations at forward bias which screen the ionic charge, reducing hysteresis.
Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Better or even optimal building energy control and operation strategies provide great opportunities to reduce ...building energy consumption. Moreover, it is estimated by the National Energy Technology Laboratory that more than one-fourth of the 713GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. Energy forecasting models for building energy systems are essential to building energy control and operation. Three general categories of building energy forecasting models have been reported in the literature which include white-box (physics-based), black-box (data-driven), and gray-box (combination of physics based and data-driven) modeling approaches. This paper summarizes the existing efforts in this area as well as other critical areas related to building energy modeling, such as short-term weather forecasting. An up-to-date overview of research on application of building energy modeling methods in optimal control for single building and multiple buildings is also summarized in this paper. Different model-based and model-free optimization methods for building energy system operation are reviewed and compared in this paper. Agent based modeling, as a new modeling strategy, has made a remarkable progress in distributed energy systems control and optimization in the past years. The research literature on application of agent based model in building energy system control and operation is also identified and discussed in this paper.
Abstract
The exploration of two-dimensional solids is an active area of materials discovery. Research in this area has given us structures spanning graphene to dichalcogenides, and more recently 2D ...transition metal carbides (MXenes). One of the challenges now is to master ordering within the atomic sheets. Herein, we present a top-down, high-yield, facile route for the controlled introduction of ordered divacancies in MXenes. By designing a parent 3D atomic laminate, (Mo
2/3
Sc
1/3
)
2
AlC, with in-plane chemical ordering, and by selectively etching the Al and Sc atoms, we show evidence for 2D Mo
1.33
C sheets with ordered metal divacancies and high electrical conductivities. At ∼1,100 F cm
−3
, this 2D material exhibits a 65% higher volumetric capacitance than its counterpart, Mo
2
C, with no vacancies, and one of the highest volumetric capacitance values ever reported, to the best of our knowledge. This structural design on the atomic scale may alter and expand the concept of property-tailoring of 2D materials.
As the main component of lignocelluloses, cellulose is a biopolymer consisting of many glucose units connected through β-1,4-glycosidic bonds. Breakage of the β-1,4-glycosidic bonds by acids leads to ...the hydrolysis of cellulose polymers, resulting in the sugar molecule glucose or oligosaccharides. Mineral acids, such as HCl and H
2
SO
4
, have been used in the hydrolysis of cellulose. However, they suffer from problems of product separation, reactor corrosion, poor catalyst recyclability and the need for treatment of waste effluent. The use of heterogeneous solid acids can solve some of these problems through the ease of product separation and good catalyst recyclability. This review summarizes recent advances in the hydrolysis of cellulose by different types of solid acids, such as sulfonated carbonaceous based acids, polymer based acids and magnetic solid acids. The acid strength, acid site density, adsorption of the substance and micropores of the solid material are all key factors for effective hydrolysis processes. Methods used to promote reaction efficiency such as the pretreatment of cellulose to reduce its crystallinity and the use of ionic liquids or microwave irradiation to improve the reaction rate are also discussed.
This paper reviews the recent advances in cellulose hydrolysis into glucose over solid acids, which plays an important role in the conversion of biomass derived carbohydrates into useful platform molecules.
Studies of the optical properties and catalytic capabilities of noble metal nanoparticles (NPs), such as gold (Au) and silver (Ag), have formed the basis for the very recent fast expansion of the ...field of green photocatalysis: photocatalysis utilizing visible and ultraviolet light, a major part of the solar spectrum. The reason for this growth is the recognition that the localised surface plasmon resonance (LSPR) effect of Au NPs and Ag NPs can couple the light flux to the conduction electrons of metal NPs, and the excited electrons and enhanced electric fields in close proximity to the NPs can contribute to converting the solar energy to chemical energy by photon-driven photocatalytic reactions. Previously the LSPR effect of noble metal NPs was utilized almost exclusively to improve the performance of semiconductor photocatalysts (for example, TiO
2
and Ag halides), but recently, a conceptual breakthrough was made: studies on light driven reactions catalysed by NPs of Au or Ag on photocatalytically inactive supports (insulating solids with a very wide band gap) have demonstrated that these materials are a class of efficient photocatalysts working by mechanisms distinct from those of semiconducting photocatalysts. There are several reasons for the significant photocatalytic activity of Au and Ag NPs. (1) The conduction electrons of the particles gain the irradiation energy, resulting in high energy electrons at the NP surface which is desirable for activating molecules on the particles for chemical reactions. (2) In such a photocatalysis system, both light harvesting and the catalysing reaction take place on the nanoparticle, and so charge transfer between the NPs and support is not a prerequisite. (3) The density of the conduction electrons at the NP surface is much higher than that at the surface of any semiconductor, and these electrons can drive the reactions on the catalysts. (4) The metal NPs have much better affinity than semiconductors to many reactants, especially organic molecules. Recent progress in photocatalysis using Au and Ag NPs on insulator supports is reviewed. We focus on the mechanism differences between insulator and semiconductor-supported Au and Ag NPs when applied in photocatalytic processes, and the influence of important factors, light intensity and wavelength, in particular estimations of light irradiation contribution, by calculating the apparent activation energies of photo reactions and thermal reactions.
The development and mechanism of new photocatalysts of gold and nanoparticles on insulator supports are reviewed.
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