Bi0.5Na0.5TiO3-0.06BaTiO3 (BNT-BT) thin films were prepared by both chemical solution (CSD) and pulsed laser deposition (PLD). The microstructure, dielectric, and ferroelectric properties were investigated. High stability of the dielectric permittivity (∆ɛ/ɛ(150 °C) ≤ ± 15%) over a wide temperature range from room temperature to 300 °C was obtained. Distinctly, the CSD film showed high TCC stability with variation of ± 5% up to 250°C. Furthermore, the CSD film showed an unsaturated ferroelectric hysteresis loop characteristic of the ergodic relaxor phase, however the PLD one exhibited almost saturated loop signature of the coexistence of both ergodic and non-ergodic states. The energy storage properties of the prepared films were determined using the P–E loops obtained at different temperatures. The results showed that these films exhibit stable and improved energy storage density comparable to the ceramic capacitors. Moreover, the CSD film exhibited more rigidity and better energy storage density that exceeds 1.3 J/cm3 under low applied field of 317 KV/cm as well as interesting efficiency in a large temperature range. The obtained results are very promising for energy storage capacitors operating at high temperatures.

The study of photonic crystals has emerged as an attractive area of research in nanoscience in the last years. In this work we study the properties of a two-dimensional photonic crystal composed of dielectric rods. The unit cell of the system is composed of six rods organized on the sites of a C6 triangular lattice. We induce a topological phase by introducing an angular perturbation ϕ in the pristine system. The topology of the system is then determined by using the so-called k.p perturbed model. Our results show that the system presents a topological and a trivial phases, depending on the sign of the angular perturbation ϕ. The topological character of the system is probed by evaluating the electromagnetic energy density and analyzing its distribution in the real space, in particular on the maximal Wyckoff points. We also find two edge modes at the interface between the trivial and topological photonic crystals, which present a pseudospin topological behavior. By applying the Bulk-Edge correspondence, we study the pseudospin edge modes and conclude that they are robust against defects, disorder and reflection. Moreover, the localization of the edge modes leads to the confinement of light and the interface behaves as a waveguide for the propagation of electromagnetic waves. Finally, we show that the two edge modes present energy flux propagating in opposite directions, which is the photonic analogue of the quantum spin Hall effect.

Artemisia absinthium (A. absinthium) leaf extract was successfully used to create zinc oxide nanoparticles (ZnO NPs), and their properties were investigated via several techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), Fourier transform infrared (FTIR), and UV–Vis spectroscopy. SEM analysis confirmed the spherical and elliptical shapes of the particles. Three different zinc peaks were observed via EDX at energies of 1, 8.7, and 9.8 keV, together with a single oxygen peak at 0.5 keV. XRD analysis identified ZnO NPs as having a hexagonal wurtzite structure with a particle size that decreased from 24.39 to 18.77 nm, and with an increasing surface area (BET) from 4.003 to 6.032 m2/g for the ZnO (without extract) and green ZnO NPs, respectively. FTIR analysis confirmed the groups of molecules that were accountable for stabilizing and minimizing the ZnO NPs, which was apparent at 3400 cm. Using UV–Vis spectroscopy, the band gap energies (Egs) for the green ZnO and ZnO (without extract) NPs were estimated, and the values were 2.65 and 2.79 eV, respectively.

Many buildings built before the energy performance regulations are in a situation of thermal discomfort and energy inefficiency. The creation of intelligent environments advances towards new opportunities, based on real-time monitoring and on the development of sensors and technologies. Furthermore, the standards for building automation and electronic systems enable interoperability and interconnection between control devices and systems. The application of soft computing has significantly improved the energy efficiency, however, requires prior assessment to design the automation functions. Temperature, humidity, air quality, occupancy and energy consumption are the most common measured parameters, but the relationship with other operational variables such as occupancy or some building states remains as a research challenge. This article presents a methodology to develop the automatization of an existing large public building. The methodology consists of three stages: 1. Assessment and diagnosis to set appropriate actions using EN ISO 52120-1. 2. EN 50090 for open communication networks, and EN ISO 52120-1 to assign the technical building management. 3. System control deploying of low-cost and low-consumption input and output devices. It has been proved that it is possible to effectively automate an obsolete building with a low cost, open source system that can be easily applied in other buildings.

We present a theoretical modeling of a cylindrical tunable liquid crystal lens based on the modulation of the anchoring energy. This latter can be easily obtained by means of photoaligning techniques. The liquid crystal cell we propose exhibits strong anchoring at the top substrate and an anchoring energy with parabolic profile at the bottom substrate. The model describes the dependence of the focal length on the applied voltage and presents a theoretical study of lens aberrations. The results obtained are of general relevance and can be used to optimize the performances of every kind of liquid crystal lens with parabolic profile.

Hydrogen powered vehicles use high-pressure reservoirs from which the gas is transferred to the low-pressure fuel-cell via a classical pressure reduction valve. In these systems no expansion work is recovered and the question is addressed of the potential to increase the global efficiency by using an expansion machine between the reservoir and the electrochemical reactor. This paper investigates the feasibility of such an expansion machine, evaluates the mechanical constraints in terms of forces, torques and produced power by numeric simulation. It further evaluates the energetic contribution to the whole conversion chain from the hydrogen reservoir to the common electrical network on board. A low energy contribution of the expansion system addresses the question of the real benefit of such an investment.

The free energy principle (FEP) is a mathematical and scientific principle that describes the relationship between the physical behavior of a dynamical system and the interpretation of such behavior as carrying out inference. It blurs the boundary between the ontological mode of the system of interest and the epistemological significance it acquires through its dynamic interaction with the environment. New materialism (or neo-materialism), despite lacking a single definition, refers to a range of emerging perspectives that attempt to dismantle the long-held divisions between ontology, epistemology, and even ethics, with the aim of achieving a comprehensive transformation of naturalized thinking. In this context, new materialism provides powerful tools to reframe some of the conceptual foundations of the FEP. This paper is the first in a series that aims to systematically construct a neo-materialistic perspective for the FEP, exploring its wide-ranging implications. It serves as an introduction to the series, arguing for the justification of deploying new materialism to reframe the FEP and introducing some essential concepts to be utilized in developing a neo-materialistic account of the FEP.

Sensor networks, as a special subtype of wireless networks, consist of sets of wirelessly connected sensor nodes often placed in hard-to-reach environments. Therefore, it is expected that sensor nodes will not be powered from the power grid. Instead, sensor nodes have their own power sources, the replacement of which is often impractical and requires additional costs, so it is necessary to ensure minimum energy consumption. For that reason, the energy efficiency of wireless sensor networks used for monitoring environmental parameters is essential, especially in remote networking scenarios. In this paper, an overview of the latest research progress on wireless sensor networks based on LoRa was provided. Furthermore, the analyses of the energy consumption of sensor nodes used in agriculture to observe environmental parameters were carried out. Optimization methods of energy consumption, in terms of choosing the appropriate data collection processes, as well as the settings of wireless network radio parameters were suggested. In the conducted analyses, special emphasis was placed on choosing the optimal package size. In this paper, it was proven that the adjustment of the transmission speed to the actual size of the packet is important for better energy efficiency of communication.

Solar energy is a renewable and sustainable source of energy, and it has been used in addition of specified technologies, such as solar cooling. The demand for cooling continues to increase in line with environmental changes and a greater desire for human comfort. This study primarily aimed to analyze the performance of an evaporative cooling system powered by solar energy and assess the economic and environmental impact of this system. In this system, hot, dry incoming air is used to evaporate water, thus transforming part of its sensitive heat into latent heat without any variation in enthalpy or total heat. The outputted air then has a lower temperature and a greater humidity, thus providing a more comfortable, healthier environment for its users. To achieve this study’s objectives, numerical code was developed and implemented in MATLAB. The obtained results reveal that the efficiency of the evaporative cooler exceeds 90%, with maximum efficiency being reached at a high wet-bulb depression, while minimum efficiency was observed when the dry air has a high relative humidity and a low dry-bulb temperature.

The battle of currents between AC and DC reignited as a result of the development in the field of power electronics. The efficiency of DC distribution systems is highly dependent on the efficiency of distribution converter, which calls for optimized schemes for efficiency enhancement of distribution converters. Modular solid-state transformers play a vital role in DC Distribution Networks and Renewable Energy systems (RES).This paper deals with efficiency-based load distribution for Solid State Transformers (SSTs) in DC distribution networks. Aim is to achieve a set of minimum inputs that are consistent with output while considering constraints and efficiency. As the main feature of modularity is associated with a three-stage structure of SSTs. This modular structure has been optimized using Ant Lion Optimizer (ALO) and validated by applying it EIA (Energy Information Agency) DC Distribution Network which contains SSTs. In the DC distribution grid, modular SSTs provide promising conversion of DC power from medium voltage to lower DC range (400V). The proposed algorithm is simulated in MATLAB and also compared with two other metaheuristic algorithms. The obtained results prove that the proposed method can significantly reduce input requirements for producing the same output while satisfying the specified constraints.

In this work we report recent theoretical calculations of a superconducting island in a strong vortex confinement regime. The obtained results reveal the evolution of superconducting condensate as a function of electron mean-free path (l) with the evolution of an applied magnetic field H0. The results of this study provide an insight about the emergent superconducting properties under such conditions, using the Ginzburg-Landau numerical simulations where spatial variation of thickness d on island, omnipresent in these kind of structures grown on Si (111), is taken into account. These results offer a new route to tailor superconducting circuits by using the controlled bombardment, in order to explore the impact on vortex distribution, phase of order parameter, number of vortices, free energy and the first H1 and second critical field H2.

As a manifestation of technological innovation achievements, patents reflect the frontier of technological development in the field. This paper constructs a multi-entity patent collaboration network and analyzes its evolution patterns to provide a reference for innovation organizations to grasp the general direction of innovation development and select partners. Based on the data of collaboration patents of two and three organizations in China's new energy vehicles (NEV) industry from 2008 to 2021, this paper constructs higher-order interaction collaboration innovation networks in different periods to analyze the spatial evolution of networks and patent cooperation activities. The results show that the generalized degree distribution of nodes and edges conforms to the power-law distribution. The two-dimensional simplex networks gradually form triangle groups centered on the core nodes, and the importance of key edges is beginning to emerge. Key organizations and partners, including State Grid Corporation of China, Tsinghua University, and China Electric Power Research Institute, will largely determine the direction for the future development of cooperation innovation. The study also reveals that Beijing, Jiangsu, Zhejiang, Guangzhou, and Shanghai are in central positions in the cooperative innovation network, based on their cooperation breadth and depth measures. Additionally, key links formed by Beijing as hubs are not only the center of information exchange but also function as bridges that connect to other regions.

This paper provides a comprehensive overview of recent advancements in autonomous electric vehicle (AEV) within the specified region. It elaborates on the progress and comparative analysis of diverse subsystems, including energy storage, cell balancing for battery systems, vehicle charger layouts, electric vehicle motor mechanisms, and braking systems. Furthermore, this paper showcases several prototype autonomous electric vehicles as conclusive study findings.

The transportation sector is a significant source of greenhouse gas emissions. Electric vehicles (EVs) have gained popularity as a solution to reduce emissions, but the high load of charging stations poses a challenge to the power grid. Nuclear-Renewable Hybrid Energy Systems (N-RHES) present a promising alternative to support fast charging stations, reduce grid dependency, and decrease emissions. However, the intermittent problem of renewable energy sources (RESs) limits their application, and the synergies among different technologies have not been fully exploited. This paper proposes a predictive and adaptive control strategy to optimize the energy management of N-RHES for fast charging stations, considering the integration of nuclear, photovoltaics, and wind turbine energy with a hydrogen storage fuel cell system. The proposed dynamic model of a fast-charging station predicts electricity consumption behavior during charging processes, generating probabilistic forecasting of electricity consumption time-series profiling. Key performance indicators and sensitivity analyses illustrate the practicability of the suggested system, which offers a comprehensive solution to provide reliable, sustainable, and low-emission energy to fast-charging stations while reducing emissions and dependency on the power grid.

Self-healing ceramic composites are promising smart materials for high-temperature applications. To better understand their behaviors under service conditions, numerous studies have been performed both experimentally and numerically, and kinetics parameters such as activation energy and frequency factor are reported to be indispensable for investigating healing phenomena. Here, we propose a method for determining the kinetic parameters of self-healing ceramic composites based on the oxidation kinetics model of strength recovery. These parameters are determined by an optimization method using experimental strength recovery data under various healing temperatures and times and microstructural features on the fractured surfaces. Alumina and mullite matrix-based self-healing ceramic composites, such as Al2O3/SiC, Al2O3/TiC, Al2O3/Ti2AlC (MAX phase), and mullite/SiC, were selected as target materials. The theoretical strength recovery behaviors of the cracked specimens obtained from the determined kinetic parameters were compared with the experimental results. The determined parameters are within the previously reported range, and the predicted strength recovery behaviors are reasonably agreed with the experimental values. The proposed method can also be applied to other self-healing ceramics with matrices reinforced with different healing agents to evaluate oxidation rate, crack healing rate, and theoretical strength recovery behaviors for designing self-healing materials used in high temperature applications. Furthermore, the healing ability of composites can be fairly discussed regardless of the type of strength recovery test.

It is often claimed that Einstein is wrong about quantum mechanics. However, when comparisons are made with respect to theoretical foundations rather than experimental results Einstein’s theories are found to be superior. Although quantum mechanics correctly predicts what it is possible to observe (the emissions) it ignores the other half of natural phenomena, what cannot be observed (the absorptions), thereby violating the conservation laws. By describing only one-half of radiation processes conceptual difficulties such as wave function collapse, infinite paths, and inscrutable mathematics seem to be insoluble mysteries. The deficiencies are corrected by introducing Hamilton’s principle S = ∫ Ldt and applying the methods of quantum field theory to derive relativistic equations of motion. The calculus of variations is used to show that the wave function represents an incomplete equation of motion because it equals twice the allowable action minimum.

This paper presents a comprehensive review that highlights the characteristics of non-isolated step-up converters based on high boost voltage lifting techniques. The paper categorises the high boost techniques: multistage/multilevel, switched capacitor, voltage multiplier, voltage lift, switched inductor, and magnetic coupling. The paper also discusses in detail the advantages and disadvantages for each category such as cost, complexity, power density, reliability and efficiency. The number of passive and active components, voltage gain, voltage stress, switching frequency, efficiency and power rating are also compared. Although the paper considers coupling inductors in the context of the non-isolated converter, the focus of the entire article is on the non-isolated high voltage step-up techniques. The key contribution in this paper is the review of high boosting techniques rather than the DC /DC converters. This allows divergence of new ideas and new power converters that will help provide highly efficient and flexible power converters for several applications where the sending end voltage is very low as photovoltaic systems. In addition, many applications and control techniques of DC/DC converters are summarised in this paper.

This paper evaluates an architectural design using an Energy Consumption consideration of Natural Ventilation in a hot dry climate (Khartoum State), at dwellings design applied. Method was used analysis of Autodesk IEVS software natural ventilation and energy consumption simulation. It resulted that to cooling, by natural ventilation in dwelling design used to get indoor temperature at the comfortable level during the summer. The Best-Case Situation of natural ventilation with consider of energy saving Based on the CFD simulation analysis, the performance of internal air velocity is approximately 0.7m/s. The wind velocity starts to slow down towards the rear of the apartment spaces. Approximately 95% of the internal areas have average air velocity between 0.43 m/s to 0.9 m/s. Internal Air flow pattern single floor house plan at Khartoum (Alazhari City); showing the internal air velocity of 0.7m/s near the window opening positions with the wind directions in the details and pressure of the air as worst-case situation, with velocity and temperature of the air with average 22o as a best-case situation. during a year. Architectural design process in the urban area of Alazhari City for dwelling towards to saving energy was applied and determined into an urban planning neighbourhood at Khartoum.

Hydrogen-bond (H-bond) energies in 310-helices of short alanine peptides were systematically examined by precise DFT calculations with the negative fragmentation approach (NFA), a modified method based on the molecular tailoring approach. The contribution of each H-bond was evaluated in detail from the 310-helical conformation of total energies (whole helical model; WH3-10 model), and the results were compared with the property of H-bond in a-helix from our previous study. The H-bond energies of the WH3-10 model exhibited tendencies different from those exhibited by the -helix, in that they depended on the helical position of the relevant H-bond pair. H-bond pairs adjacent to the terminal H-bond pairs were observed to be strongly destabilized. The analysis of electronic structures indicated that structural characteristics cause the destabilization of the H-bond in 310-helices. We also found that the longer the helix length, the more stable the H-bond in the terminal pairs of the WH3-10 model, suggesting the action of H-bond cooperativity.

This paper presents the implementation of a control strategy based on fuzzy logic artificial intelligence (AI) for speed regulation of an electromagnetic frequency regulator (EFR) prototype, aiming to eliminate the dependence on knowledge of physical parameters in the most diverse operating conditions. Speed multiplication is one of the most important steps in power generation wind. Gearboxes are generally used for this purpose. However, they have a reduced lifespan and a high failure rate and are still noise sources. The search for new ways to match the speed (and torque) between the turbine and the generator is an important research area to increase the energy, financial and environmental efficiency of wind systems. The EFR device is an example of an alternative technology that this team of researchers has proposed. It counts the fact of taking advantage of the main advantages of an induction machine with the rotor in a squirrel cage positively. In the first studies, the EFR control strategy consisted of the conventional PID controllers, which has several limitations widely discussed in the literature. This strategy also limits the EFR's performance, considering its entire operating range. The simulation program was developed using the Matlab/Simulink platform, while the experimental results were obtained in the laboratory emulating the EFR-based system. The EFR prototype used has 2 poles, a nominal power of 2.2 kW, and a nominal frequency of 60 Hz. Experimental results were presented to validate the efficiency of the proposed control strategy.

Generalisation from the local 4-dimensional spacetime form for a proper time interval provides an alternative basis for a unified theory contrasting with the more familiar approach of appending extra dimensions of space. In both cases the main goal is to derive a structure of matter that accounts for empirical observations from the properties of the additional components. Previous work has focussed upon the direct and significant connections that this new approach makes with the Standard Model of particle physics while also providing a link with dark matter models. In this paper we elaborate on how a further sector of generalised proper time, incorporating the key component of negative pressure, can account for the apparent dark energy fuelling the accelerating large-scale expansion of the universe. Through comparison with existing dark energy models we elucidate the elementary composition of this sector, its potential relation to an effective cosmological constant term, and the nature of possible interaction with the visible and dark matter sectors.

The rapid industrial growth in solar energy is gaining increasing interest in renewable power from smart grids and plants. Anomaly detection in photovoltaic (PV) systems is a demanding task. In this sense, it is vital to utilize recent advances in machine learning to accurately and timely detect different anomalies and condition monitoring. This paper addresses this issue by evaluating different machine learning techniques and schemes and showing how to apply these approaches to solve anomaly detection and detect faults on photovoltaic components. For this, we apply distinct state-of-the-art machine learning techniques (AutoEncoder Long Short-Term Memory (AE-LSTM), Facebook-Prophet, and Isolation Forest) to detect faults/anomalies and evaluate their performance. These models shall identify the PV system's healthy and abnormal actual behaviors. Our results provide clear insights to make an informed decision, especially with experimental trade-offs for such complex solution space.

An interesting physical phenomenon was recently observed when a fresh-water basin is covered by a thin ice film that has properties similar to that of a rubber membrane. Surface waves can be generated under the action of wind on the air-water interface that contains an ice film. The modulation property of hydro-elastic waves (HEWs) in deep water covered by thin ice film blown by the wind with a uniform vertical profile is studied here in terms of the air-flow velocity versus a wavenumber. The modulation instability of HEWs is studied through the analysis of coefficients of the nonlinear Schrödinger (NLS) equation with the help of the Lighthill criterion. The NLS equation is derived using the multiple scale method in the presence of airflow. It is demonstrated that the potentially unstable hydro-elastic waves with negative energy appear for relatively small wind speeds, whereas the Kelvin–Helmholtz instability arises when the wind speed becomes fairly strong. Estimates of parameters of modulated waves for the typical conditions are given.

(1) Background: Due to the high proportion of disadvantaged students in a rural school in Taiwan and the gap between students’ concepts and practices of environmental protection and sustainable energy, four science and mathematics teachers in this school planned an engineering-centered PjBL of sustainable energy curriculum in a Makers Club to enhance students’ creativity, engineering skills, practices of environmental protection and sustainable energy, and learning attitudes; (2) Methods: This study is four-year action research. Teachers and students initiated the idea from rebuilding an old fan in a classroom; (3) Results: The students in the Makers Club improved their engineering skills and created various green-power generation devices (evolved from ventilation ball generator, hydropower, ocean current power generators to tiny, 3D-printing wind power generators). They turned environmental protection and sustainable energy concepts into actions during practices and won awards from science and engineering fairs every year. This creative and supportive atmosphere spread from the club to the whole school and improved the students’ practices of environmental protection and learning attitudes after long-term implementation; (4) Conclusions: The design principles of the engineering-centered PjBL of sustainable energy curriculum played a critical role and were outlined at the end of the study.

The classical uncertainty principle inequalities were imposed as a mathematical constraint over the general relativity geodesic equation. In this way, the uncertainty principle was reformulated in terms of the proper space-time length element, Planck length and a geodesic-derived scalar, leading to a geometric expression for the uncertainty principle (GeUP). This re-formulation confirmed the necessity for a minimum length for the space-time line element in the geodesic, dependent on a geodesic-derived scalar which made the expression Lorentz-covariant. In agreement with quantum gravity theories, GeUP required the imposition of a perturbation over the background Minkowski metric unrelated to classical gravity. When applied to the Schwarzschild metric, a geodesic exclusion zone was found around the singularity where uncertainty in space-time diverged to infinity.

The Unmanned Aerial Vehicles (UAVs), used in civilian applications such as emergency medical deliveries, precision agriculture, wireless communication provisioning, etc., face the challenge of limited flight time due to their reliance on the on-board battery. Therefore, developing efficient mechanisms for in-situ power transfer to recharge UAV batteries hold potential in extending their mission time. In this paper, we study the use of far-field wireless power transfer (WPT) technique from specialized, transmitter UAVs (tUAVs) carrying Multiple Input Multiple Output (MIMO) antennas for transferring wireless power to receiver UAVs (rUAVs) in a mission. The tUAVs can fly and adjust their distance to the rUAVs to maximize energy transfer. The use of MIMO antennas further boost the energy reception by narrowing the energy beam toward the rUAVs. The complexity of their dynamic operating environment increases with the growing number of tUAVs, and rUAVs with varying levels of energy consumption and residual power. We propose an intelligent trajectory selection algorithm for the tUAVs based on a deep reinforcement learning model called Proximal Policy Optimization (PPO) to optimize the energy transfer gain. Simulation results demonstrate that with the use of PPO, the system achieves a tenfold flight time extension compared to no wireless recharging. Further, PPO outperforms the benchmark movement strategies of ’Traveling Salesman Problem’ and ’Low Battery First’ when used by the tUAVs.

We have an unprecedented ability to map the Earth’s surface as deep learning technologies are applied to an abundance of high-frequency Earth observation data. Simple, free, and effective methods are needed to enable a variety of stakeholders to use these tools to improve scientific knowledge and decision making. Here we present a trained U-Net model that can map and delineate ground mounted solar arrays using publicly available Sentinel-2 imagery, and that requires minimal data pre-processing and no feature engineering. By using label overloading and image augmentation during training, the model is robust to temporal and spatial variation in imagery. The trained model achieved a precision and recall of 91.5% each and an intersection over union of 84.3% on independent validation data from two distinct geographies. This generalizability in space and time makes the model useful for repeatedly mapping solar arrays. We use this model to delineate all ground mounted solar arrays in North Carolina and the Chesapeake Bay watershed to illustrate how these methods can be used to quickly and easily produce accurate maps of solar infrastructure.

The objective of this article: analysis of research trends on the topic "Materials Science for Energy Engineering" for the period 2012-2021. Materials and methods: bibliometric analysis of data from the Scopus abstract database.Results. It is shown that this topic is developing faster than the general energy topics.The key feature of the research trends is a significant increase in work on the development of materials for renewable energy and a decrease in the number of publications related to nuclear power.The primary goal of many studies is to increase the efficiency of renewable energy production through the use of new materials.The importance of the topic is evidenced by the emergence of new journals that quickly entered the first quartile of the abstract databases Scopus and Web of Science, for example: ACS Applied Energy Materials.There has been a significant increase of interest in perovskite solar cells, layered semiconductors, triboelectric nanogenerators, cobalt compounds, sulfur compounds, and oxygen and hydrogen evolution reaction during Electrolysis.Publications on electric batteries are well represented in all time intervals. The focus is on electrode materials and battery efficiency.

Renewable methanol, obtained from CO₂ and hydrogen provided from renewable energy, has been proposed as a way to close the CO₂ loop. In industry, methanol synthesis using the catalyst CuO/ZnO/Al₂O₃ occurs at a high pressure. We intend to make certain modification on the traditional catalyst in order to work at lower pressure, maintaining high selectivity. Therefore, three heterogeneous catalysts have been synthesized by co-precipitation in order to improve the activity and the selectivity to methanol under mild conditions of temperature and pressure. Certain modifications on the traditional catalyst Cu/Zn/Al₂O₃ were employed such as the modification of the synthesis time and the addition of Pd as a dopant agent. The most efficient catalyst among those tested was a palladium-doped catalyst, 5% Pd/Cu/Zn/Al₂O₃. This had a selectivity of 64% at 210C and 5 bar.

The change in the value of the breaking energy is discussed here for selected steel grades used in building structures after subjecting the samples made of them to episodes of heating in the steady-state heating regime and then cooling in a simulated fire conditions. These changes were recorded based on the instrumented Charpy impact tests, in relation to the material initial state. The S355J2+N, 1H18N9T steels and also X2CrNiMoN22-5-3 duplex steel were selected for detailed analysis. The fire conditions were modelled experimentally by heating the samples and then keeping them for a specified time at a constant temperature of: 600°C (first series) and 800°C (second series), respectively. Two alternative cooling variants were investigated in the experiment: slow cooling of the samples in the furnace, simulating the natural fire progress, without any external extinguishing action, and cooling them in water mist simulating an extinguishing action by a fire brigade. The temperature of the tested samples was set at the level -20oC and alternatively at the level + 20oC. The conducted analysis is aimed at assessing the risk of sudden, catastrophic fracture of load-bearing structure made of steel degraded as a result of a fire previously occurred with different development scenarios.

The need for quick and easy deflection calculations of various prefabricated slabs causes that simplified procedures and numerical tools are used more and more often. Modelling of full 3D finite element (FE) geometry of such plates is not only uneconomical but often requires the use of complex software and advanced numerical knowledge. Therefore, numerical homogenization is an excellent tool, which can be easily employed to simplify a model, especially when accurate modelling is not necessary. Homogenization allows for simplifying a computational model and replacing a complicated composite structure with a homogeneous plate. Here, a numerical homogenization method based on strain energy equivalence is derived. Using the method proposed, the structure of the prefabricated concrete slabs reinforced with steel spatial trusses is homogenized to a single plate element with an effective stiffness. There is a complete equivalence between the full 3D FE model built with solid elements combined with truss structural elements and the simplified homogenized plate FE model. The method allows for the correct homogenization of any complex composite structures made of both solid and structural elements, without the need to perform advanced numerical analyses. The only requirement is a correctly formulated stiffness matrix of a representative volume element (RVE) and appropriate formulation of the transformation between kinematic constrains on RVE boundary and generalized strains.

The use of different primary energy sources in human society has led to two major polluting emissions in the environment: energy (mostly heat), and chemical substances (mostly carbon dioxide). In this paper, the total global anthropogenic emissions of heat to the atmosphere during the industrial era (years 1850-2018) were determined and their effect on the change of global atmospheric temperature was calculated. The concept of a theoretical three-phase Earth reactor was introduced to estimate global atmospheric temperature increase caused by anthro-pogenic heat emissions. The resulting calculations closely approximated the actual atmospheric temperature change recorded during the last 170-year period. These results suggest that the temperature change of the atmosphere (global warming) is entirely due to anthropogenic heat emissions.

This paper proposes a mathematical model to simulate Day-ahead markets of large-scale multi-energy systems with high share of renewable energy. Furthermore, it analyses the importance of including unit commitment when performing such analysis. The results of the case study, which is performed for the North Sea region, show the influence of massive renewable penetration in the energy sector and increasing electrification of the district heating sector towards 2050, and how this impacts the role of other energy sources such as thermal and hydro. The penetration of wind and solar is likely to challenge the need for balancing in the system as well as the profitability of thermal units. The degree of influence of the unit commitment approach is found to be dependent on the configuration of the energy system. Overall, including unit commitment constraints with integer variables leads to more realistic behaviour of the units, at the cost of increasing considerably the computational time. Relaxing integer variables reduces significantly the computational time, without highly compromising the accuracy of the results. The proposed model, together with the insights from the study case, can be specially useful for system operators for optimal operational planning.

In the development of power systems it is indicated very often, that transformation of power systems should be carried out in accordance with the idea of energy democracy. This will develop energy communities, that are trying to meet energy needs by using local renewable generation sources. This may result with a temporary low load on the MV lines connecting the community grid and the power system. Such state may cause incorrect operation of power protection systems. This can cause an extended protection operation time, due to decision algorithms inactivity at low values of measurement currents. Therefore, the detailed MV lines overcurrent digital protection model and a dynamic model of the power network were developed. The simulation results are showing that the settings of the parameters activating the protection decision algorithms affect their operation time in dynamic conditions. The conclusion is that the development of the power protection automatics must be carried out in the same time (preferably in advance) with the change of the power system operation model. This is very important for future power systems with high penetration energy communities and renewable generation sources.

The current need to develop sustainable power sources has led to the development of ocean-based conversion systems. Wells turbine is a widely used converter in such systems which suffers from a lack of operational range and power production capacity under operational conditions. The profile named IFS which is concave in the post-mid-chord region, can produce significantly larger lift forces and show better separation behavior than the NACA profiles. In the present study, we tested this profile for the first time in a Wells turbine. The performance of six different blade designs with IFS and NACA profiles were evaluated and compared using a validated computational fluid dynamic model. Although the substitution of the NACA profile with the IFS profile in all cases increased the torque generated, the most efficient power generation and the largest efficient range were achieved in the design with varying thickness from the hub with a 0.15 thickness ratio reaching to the ratio of 0.2 at the tip. The operational span of this design with the IFS profile was 24.1% greater and the maximum torque generation was 71% higher than the case with the NACA profile. Therefore, the use of the IFS profile is suggested for further study and practical trials.

A characteristic feature of lightweight constructions is their low thermal mass which causes high internal temperature fluctuations that require high heating and cooling demand throughout the year. Phase Change Materials (PCMs) is effective in providing thermal inertia to low thermal mass buildings. The aim of this paper is to analyse the thermal behaviour of two proposed lightweight buildings designed for homeless people and to investigate the potential benefit achievable through the use of different types of PCM in the temperate climatic conditions of Christchurch, New Zealand. For this purpose, over 300 numerical simulations have been conducted using the simulation software DesignBuilder®. The bulk of the simulations were carried out under the assumption that the whole opaque building envelope is equipped with PCM. The results showed significant energy saving and comfort enhancement through the application of PCMs. Thereby, annual energy saving of over 50 % was reached for some of the PCMs considered. Additionally, the effectiveness of single, PCM-equipped structure components was investigated and substantial benefits between 19 and 27 % annual energy saving were achieved. However, occupant behaviour in terms of ventilation habits, occupancy of zones etc. remains one of the biggest challenges in any simulation work due to insufficient data.

Though inland ships share a small portion of the total global CO₂ emission from shipping, from the individual country’s economic and environmental perspective, this is very important. In order to reduce CO₂ emission from the sea going ships by increasing energy efficiency, International Maritime Organization (IMO) adopted a generalized Energy Efficiency Design Index (EEDI) in 2011. However, due to the variation in the environmental, geographic and economic conditions, a generalized EEDI cannot be established in a similar fashion as established by IMO. Shallow and restricted water effects, different fuel qualities (to reduce operational cost), increase in engine power requirement, reduction in carrying capacity, cargo availability, etc. forbid the use of existing EEDI formulation for inland waterways. So, an EEDI formulation based on revised parameters has been proposed for the inland ships of Bangladesh. This paper focuses on the implementation of the revised EEDI formulation by performing a sensitivity analysis of different ship design parameters. Based on the analysis, suggestions were made on how to design inland oil tankers of Bangladesh using the revised EEDI formulation for reducing CO₂ from the current level. Keeping the same speed and capacity, those vessels were redesigned based on those suggestions. The CFD analysis of those redesigned vessels using ‘Shipflow’ has shown a total resistance reduction of 10-13%.

While there is overwhelming evidence for dark matter (DM) in galaxies and galaxy clusters, all searches for DM particles have so far proved negative. It is not even clear whether only one particle is involved or a combination or particles, their masses not precisely predicted. This non-detectability raises the possible relevance of modified gravity theories – MOND, MONG, etc. Here we consider a specific modification of Newtonian gravity (MONG) which involves gravitational self-energy, leading to modified equations whose solutions imply flat rotation curves and limitations of sizes of clusters. The results are consistent with current observations including that involving large spirals. This modification could also explain the current Hubble tension. We also consider effects of dark energy (DE) in terms of a cosmological constant.

As the first initiative of its kind in Algeria, here is presented a solar-powered mobile “Ultraviolet Germicidal Irradiation” disinfection unit (UVGI) based on a special germicidal ultraviolet-C (UVC) radiator. The system was designed to disinfect several objects such as: medical tools, reusable masks, face-shields, gloves, phones, laptops, keys, money and many other portable devices that need to be disinfected/sterilized. It offers the advantage of complete autonomy through the built-in photovoltaic (PV) system that includes a solar panel, a gel battery, a charge controller and a power inverter. The system provides an extra 220V-50Hz outlet with 375VA maximum power to be used when energy is needed. The system is easily scalable to generate higher ultraviolet dosages by adding more UVC lamps. The chemical-free germicidal UVC sanitizing method employed by this device effectively disactivates a very wide range of microorganisms (microbes, bacteria and fungi and viruses including the actual SARS-CoV-2 that causes COVID-19 respiratory disease) and it has several advantages in comparison to chemical-based sanitizing methods. The total cost to make this open source device is below 1000 € and is easily customizable and scalable. This device is an open source, secure and fast equipment for objects and surface disinfection. The device will be fully automated by adding PIR sensors or remote control after further funding will be received.

This article presents a method of segmenting images with gray levels that uses Onicescu's information energy calculated in the context of the neutrosophic theory. Starting from the information energy calculation for complete neutrosophic information, it is shown how to extend its calculation for incomplete and inconsistent neutrosophic information. The segmentation method is based on calculation of thresholds for separating the gray levels using the local maximum points of the Onicescu information energy.

The gravitational charge should be the energy instead of mass. This modification will lead to some different results and the experiments to test are also presented. Especially, we propose a scheme to achieve the negative energy and gravitational repulsive force in the lab.

This paper presents a comparison between a kite model with a constant-length tether and a model based on a system identification algorithm. The concept of system identification is applied to predict the uncertainties related to the variation of the wind speed and the shape deformation of the tethered membrane wing during flight. A pole-placement controller is used to ensure that the kite follows the planned flight path. Thus, we can determine the required locations of the closed loop poles, and then enforce them by changing the controller's gains in real-time. The capability of the system identification algorithm to recognize sudden changes in the dynamic model, and the ability of the controller to stabilize the system in the presence of such changes are confirmed. Furthermore, the system identification algorithm is applied to determine the parameters of a kite with variable-length tether used in a flight test of the 20 kW kite power system of TU Delft. Experimental data of this test were compared with the system identification results in real-time and significant changes were observed in the parameters of the dynamic model which heavily affect the resulting response.

A new frontier in solar thermal panel technology can be a high vacuum collector, thick enough to be equipped with solar concentrators based on non-imaging optics, such as the Compound Parabolic Concentrators (CPC). The high vacuum technology guarantees higher operating temperatures thanks to the enhanced thermal insulation, which leads to pay particular attention to the absorber radiative emission. In this paper by means of numerical simulations we compare the efficiency of a flat selective solar absorber under high vacuum to the efficiency of a CPC under high-vacuum collector.

Plants Microbial Fuel Cells (PMFC) is a new technology that generates electricity in a renewable, clean and sustainable way. In spite of these advantages, it still faces limitations in power generation and current density, reaching lower production values than other renewable technologies. Different studies maintain that the high resistivity of the cathode is the main limitation in the generation of energy; therefore, non-metallic materials to obtain a better performance are replacing the metallic electrodes. The implementation of these materials applied to PMFC requires a complex interdisciplinary work. Through three experimental tests using metallic electrodes for the extraction of electrons, this research study shows that the treatment of the substrate with natural materials, the volume plant roots, and substrate temperature and humidity control have a significant influence in the increase of the electric potential and the generated current.

When considering implementation of shallow geothermal energy as a renewable source for heating and cooling of the building, special care should be taken in hydraulic design of borehole heat exchanger system. Laminar flow can occur in pipes due to usage of glycol mixture at low temperature or inadequate flow rate. This can lead to lower heat extraction and rejection rates of the exchanger because of higher thermal resistances. Furthermore, by increasing flow rate to achieve turbulent flow and satisfactory heat transfer rate can lead to increase the pressure drop of the system and oversizing of circulation pump which leads to impairment of seasonal coefficient of performance at the heat pump. Most frequently used borehole heat exchanger system in Europe is double-loop pipe system with smooth inner wall. Lately, development is focused on implementation of different configuration as well as with ribbed inner wall which ensures turbulent flow in the system, even at lower flow rates. At a location in Zagreb, classical and extended thermal response test was conducted on three different heat exchanger configurations in the same geological environment. With classic TRT test, thermogeological properties of the ground and thermal resistance of the borehole were determined for each smooth or turbulator pipe configuration. Extended Steady-State Thermal Response Step Test (TRST) was implemented, which incorporate series of power steps to determine borehole extraction rate at the define steady-state heat transfer conditions of 0/-3°C. Results show that heat exchangers with ribbed inner pipe wall have advantages over classic double-loop smooth pipe design, in terms of greater steady state heat extraction rate and more favorable hydraulic conditions.

The energy efficiency of grinding depends on the appropriate selection of cutting conditions, grinding wheel and workpiece material. Additionally, the estimation of specific energy consumption is a good indicator to control the energy consumed during the grinding process. Consequently, this study develops a model of material removal rate to estimate the specific energy consumption based on the measurement of active power consumed in a plane surface grinding of C45K with different thermal treatments and AISI 304. This model identifies and evaluates the power dissipated by sliding, ploughing and chip formation in a industrial-scale grinding process. Furthermore, the instantaneous positions of the abrasive grains during cutting are described to study the material removal rate. The estimation of specific chip formation energy is similar to that described by other authors in laboratory scale, which allows to validate the model and experiments. Finally, the results show that the energy consumed by sliding is the main phenomenon of energy dissipation in industrial-scale grinding process, where it is denoted that sliding energy by volume unity decreases as the depth of cut and speed of workpiece increase.

Smart cities and smart technologies have been incorporated into several axes to increase the comfort of life. The connected building's concept was introduced for this reason. However, it was utilized in power management for better organizing, greater buildings management, and monetary savings. Cars technologies and the number of vehicles are also involved; Nowadays, each house has at least one car. Technological evolution helped to make those cars intelligent and connected. In the latest versions, the majority of those cars were equipped with several sensors, several communication protocols and a principal electrical control unit (ECU), especially for the electric vehicle model. This type of architecture was an essential element in a smart city, thus, it helps to manage power and decide when a vehicle needs to be charged. Based on the smart city concept and using possible network communication between buildings and vehicles, EVs can share their own information related to the powerful experience on a specific path. This information can be gathered in a gigantic database and used for managing the power inside these vehicles. In this field, we propose in this paper a new approach for power management inside an electric vehicle based on bi-communication between vehicles and buildings. The proposed approach is founded on two essential parts; the first is related to vehicles’ classification and buildings’ recommendation according to different car positions. Two algorithms, related to the SVC and neural network was employed in this work for implementing the final process. Different possibilities and situations were discussed for this approach. The proposed method was tested and validated using Simulink/Matlab application. The state of charge of the used battery was compared at the end of this work, for two specified cases, for showing the contribution of this approach.

In a recent Foundations of Physics paper [5] by the current author it was shown that, when the self-force problem of classical electrodynamics is properly solved, it becomes a plausible ontology underlying the statistical description of quantum mechanics. In the current paper we extend this result, showing that ordinary matter, thus represented, possibly suffices in explaining the outstanding observations currently requiring for this task the contrived notions of dark-matter, dark-energy and inflation. The single mandatory 'fix' to classical electrodynamics, demystifying both very small and very large scale physics, should be contrasted with other adhoc solutions to either problems. Instrumental to our cosmological model is scale covariance (and 'spontaneous breaking' thereof), a formal symmetry of classical electrodynamics treated on equal footing with its Poincare covariance, which is incompatible with the (absolute) metrical attributes of the GR metric tensor.

Global financial investments in energy production and consumption are significant since all aspects of a country's economic activity, and development require energy resources. In this paper, we assess the investment trends in the global energy sector during, before and after financial crises of 2008 using two data sources: (1) Dealogic database providing cross‐border mergers and acquisitions (M&As), and (2) fDi Intelligence fDi Markets database providing greenfield (GF) foreign direct investments (FDIs). We highlight the changing role of China and compare its M&A and GF FDI activities to those of the United States, Germany, UK, Japan and others during this period. We analyze the investments along each segment of the energy supply chain of these countries to highlight the geographical origin and destination, sectoral distribution, and cross‐border M&As and GF FDI activities. Our paper shows that while energy accounts for nearly 25% of all GF FDI, it only accounts for 4.82% of total M&A FDI activity in the period 1996-2016. China's outbound FDI in the energy sector started its ascent around the time of the global recession and had accelerated in the post-recession phase. In the energy sector, the development of China's outbound cross‐border M&As is similar to USA or UK, located mostly in the developed countries in the west, while their outbound GF investments are spread across many countries around the world. Also, China's outbound energy M&As are concentrated in certain segments (extraction, and electricity generation) while their GF covers all segments of the energy supply chain.

Underwater wireless sensor networks (UWSN) have recently been proposed as a way to monitor and explore the water depths' environments. Efficiently delivering the data is still a challenging problem in these networks because of the weaknesses in the acoustic transmission. To tackle such a problem, we propose a novel algorithm provides controlling mechanisms for critical long-term data forwarding underwater sensor networks, called Hop by Hop Power-Efficient Routing Protocol (Hⁿ-PERP). The proposed Hⁿ-PERP is a centralized full-control model that enhances the network's throughput and energy efficiency by a set of solutions depend on power monitoring in UWSN nodes. In particular, the model provides a guaranteed mechanism for scheduling and processing data transmission based on number of nodes, hops between the nodes, energy level and congestion within each node to minimize energy levels or power consumption by avoiding disconnected probability for any node, which in turn maximizing the network lifetime. Simulation results show that our proposed model is consistent with energy level and congestion, and is more accurate for enabling routing and data transmission. Therefore, the data packet delivery ratio and overall throughput also achieves robust scenarios of very sparse or/and weak networks, to keep on Performance stability in UWSN via adjusting hop-by-hop delay and energy consumption during packages delivery.

The physical and economic sustainability of using Built Environment Wind Turbine (BEWT) systems depends on the wind resource potential of the candidate site. Therefore, it is crucial to carry out a wind resource assessment prior to deployment of the BEWT. The assessment results can be used as a referral tool for predicting the performance and lifespan of the BEWT in the given built environment. To date, there is limited research output on BEWTs in South Africa with available literature showing a bias towards utility-scale or conventional ground based wind energy systems. This study aimed to assess wind power generation potential of BEWT systems in Fort Beaufort using the Weibull distribution function. The results show that Fort Beaufort wind patterns can be classified as fairly good and that BEWTs can best be deployed at 15m for a fairer power output as roof height wind speeds require BEWT of very low cut-in speed of at most1.2ms⁻¹.

The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management and development related challenges leading to inequity, inadequacy and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on long term basis to identify the existing bottlenecks. Although there are several indicators used for the performance evaluation of the irrigation schemes, but we used the coefficient of variation (CV) of actual evapotranspiration (ETa) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET) and temporal CV of RET to assess the equity, adequacy and reliability of water distribution respectively, from 2003 to 2013. The ETa was estimated through surface energy balance system (SEBS) algorithm and the ETa estimates were validated using advection aridity (AA) method with R2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that mean seasonal sub-based RET values during summer (May – September) (0.37 ± 0.06) and winter (October – April) (0.40 ± 0.08) are below the target values (RET ≥0.75) during 2003-2013. The CV of mean ETa within sub-basins and provinces for the entire study period has equitable distribution of water from October-January (0.09±0.04) whereas the highest inequity (0.24±0.08) in water distribution is during early summer. The range of the CV of mean ETa (0.04-0.06) on monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of temporal CV of mean RET highlights unreliable water supplies across the entire basin. The maximum ETa during the study period was estimated for Shamal sub-basin (552±43mm) while among provinces Kunar experienced the highest ETa (544±39mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing the water distribution plans in future.

To help reduce the impact of geohazards, an innovative landslide early-warning technology based on an energy demodulation-based fiber optic sensing (FOS-LW for short) technology, is introduced in this paper. FOS-LW measures the energy change in a sensing fiber at the segment of micro-bending, which can be caused by landslide movements, and automatically raises an alarm as soon as the measured signal intensity in the fiber reaches a pre-set threshold. Based on the sensing of micro-bending losses in the fiber optics, a two-event sensing algorithm has been developed for the landslide early-warning. The feasibility of the FOS-LW technology is verified through laboratory simulation and field tests. The result shows that FOS-LW has some unique features such as the graded alarm, real-time responses, remote monitoring, low cost and passive optical network, and can be applied in the early-warning of landslides.

In small-scale hydropower scheme, the most important component is electro-mechanical equipment. Since cost contribution of this component is high because hydrokinetic projects require negligible civil works. Turbine and alternator contribute major fraction of the hydrokinetic projects. Thus, there is a requirement to estimates the electromechanical equipment cost for the hydrokinetic hydropower scheme. The present paper investigates design parameters of the hydrokinetic turbines and intends to develop cost correlation which depends on most critical parameters of hydropower sites such as velocity and power capacity. In this present work, three zero head turbines are considered including straight blade Darrieus, two Stage Savonius, and Gorlov Helical. The size and cost of major components have been calculated based on material, manufacturing, research and design, and assembly costs. Based on cost and site parameters, cost correlation has been developed. The obtained cost has been validated with available zero head turbines in the market and installed projects. A techno-economic analysis has been carried out to select economical hydrokinetic turbine for river and canal application.

The concept of ecosystem services (ESs) provides a valuable approach to communicate societies' dependence on natural ecosystems, assisting in the evaluation of measures to protect vegetation in watersheds that promote water-related ESs. Vegetation cover and land use are important factors related to the capacity of ecosystems to provide soil loss regulation and sediment retention services, which are highly relevant for sediment management in watersheds draining into reservoirs with multiple water uses. This study aims to assess the relationship between potential changes in land use and land cover and the sediment retention service provided by riparian vegetation in a watershed draining into a hydroelectric reservoir in the Brazilian Cerrado. Sediment load was selected as a physical variable that affects different water uses in reservoirs, with these uses being dependent on the quality or quantity of stored water. Scenarios were analyzed to represent landscape reconfigurations from a baseline condition in order to account for the recovery of riparian vegetation by the agricultural sector, as foreseen in the Brazilian Forest Code. To map and quantify variations in annual sediment retention, the InVEST model was used, which allows estimating an integrated response of the drainage basin to large-scale land use changes over time and space. The results show that for the drainage basin of the Corumbá IV Hydroelectric Power Plant (HPP), the recovery of riparian areas occupied by annual crops has the potential to generate greater benefits to water use in the reservoir. In the studied catchment area, 14% of the total vegetation deficit in riparian areas is occupied by crops, while 86% is occupied by pastures. This highlights the buffering role of riparian vegetation as an effective practice for managing sediment flows originating from sheet erosion in agricultural landscapes. The methodology employed in this study allows for the quantification and mapping of the effects of soil and water conservation measures in river basins. This enables the prioritization of sectoral efforts for the restoration of native vegetation, considering the highest returns in benefits perceived by water users affected by sediment input in reservoirs. The study's results reinforce the importance of conserving vegetation in riparian areas and their surroundings for sediment retention, highlighting the role of these areas as assets in providing water-related ecosystem services.

We suggest that momentum should be redened in order to help make physics more consistent and more logical. In this paper, we propose that there is a rest-mass momentum, a kinetic momentum, and a total momentum. This leads directly to a simpler relativistic energy momentum relation. As we point out, it is the Compton wavelength that is the true wavelength for matter; the de Broglie wavelength is mostly a mathematical artifact. This observation also leads us to a new relativistic wave equation and a new and likely better QM. Better in terms of being much more consistent and simpler to understand from a logical perspective.

We previously reported new superconductivity produced by an electrostatic field and a diffusion current in a semiconductor without refrigeration. In particular, the superconductivity was investigated theoretically and confirmed experimentally. Here, we determine that the derived superconducting quantum state can be reproduced in a capacitor. When circuits are formed with this new-type capacitor and diodes, a magnetic field is applied to the diodes’ depletion layer. The depletion layer is biased because of the conversion from the magnetic-field energy to electric-field energy, resulting in the diodes’ spontaneously emitting a current. Thus, the new-type capacitor is charged using no other energy source. This new phenomenon is described theoretically with assistance of initial experiments.

The aim of this work is to introduce a mathematical model representing the evolution of the temperature in a vegetation cover and the ground underneath it. Vegetation, and its interaction with soil, plays a very important role in the protection of soil surface from the action of sun and precipitations. A reduction in the vegetated mass increase the risk of desertification, soil erosion or surface runoffs which which can give rise to soil loss and sediment retention. These processes can favour climate change and global warming, which are major concerns nowadays. The mathematical model presented takes into account the main processes involved in vegetation cover and the interaction with the soil, among which, we can mention the Leaf Area Index, which is a dimensionless quantity defined as the one-sided green leaf area per unit ground surface area, or albedo and co-albedo which are clearly influenced by the vegetation. It is also considered a nonlinear heat capacity in the soil which incorporates the latent heat of fusion, when the phase change takes place. The numerical technique used to solve the mathematical model is based on a finite volume scheme with Weighted Essentially Non Oscillatory technique for spatial reconstruction and the third order Runge-Kutta Total Variation Diminishing numerical scheme is used for time integration. Some numerical examples are solved to obtain the distribution of temperature both in the vegetation cover and the soil.

We propose that, at equilibrium, statistically equal temperatures as mechanical torques are exerted on each kind of gas phase molecules as rates of translational action [@t=ʃmvds/dt=ʃmr2ωdϕ/dt=mv2, J]. These torques result from the impulsive density of resonant quantum fields with molecules, configuring the trajectories of gas molecules while balancing molecular pressure (p=NkT) against the density of field energy (J/m3). Gibbs energy fields contain no resonant quanta at zero Kelvin, with this measure of chemical potential diminishing in magnitude as translational action of the vapor molecules and quantum field energy increases with temperature. In illustration, we show how impulsive torques from quantum fields drive the reversible thermodynamics of Carnot’s heat-work engine cycle, sustain the decreasing atmospheric temperature gradient of increasing molecular entropy with altitude, support the translational action and field energy of vortical wind flow in anticyclones, frictionally warming the Earth’s surface while recycling greenhouse infrared absorption of surface radiation, generating electrical power from air flow in wind farms and destructive power in tropical cyclones. These cases all distinguish symmetrically between a causal field of impulsive quanta (Σhν) that energizes the action of matter and the resultant vis viva of molecular mechanics (mv2). The quanta of these different fields display mean wavelengths from 10-4 m to 1012 m, with mechanical advantages many orders of magnitude greater than the corresponding translational actions, though with mean quantum frequencies (v) similar to those of radial Brownian movement for independent particles (ω). These energy fields are also thermodynamically reversible reservoirs for heat, optimizing work processes on Earth and delaying the achievement of maximum entropy production from short wave solar radiation in conversion to outgoing long wave radiation to space.

Mereology stands for the philosophical concept of parthood and is based on a sound set of fundamental axioms and relations. One of these axioms relates to the existence of a universe as a thing having part all other things. The present article formulates this logical expression first as an algebraic inequality and eventually as an algebraic equation reading in words: The universe equals the sum of all things. “All things” here are quantified by a “number of things”. Eventually this algebraic equation is normalized leading to an expression The whole equals the sum of all fractions. This introduces “1” or “100%” as a quantitative – numerical - value describing the “whole”. The resulting “basic equation” can then be subjected to a number of algebraic operations. Especially squaring this equation leads to correlation terms between the things implying that the whole is more than just the sum of its parts. Multiplying the basic equation (or its square) by a scalar allows for the derivation of physics equations like the entropy equation, the ideal gas equation, an equation for the Lorentz-Factor, conservation laws for mass and energy, the energy-mass equivalence, the Boltzmann statistics, and the energy levels in a Hydrogen atom. It further allows deriving a “contrast equation” which may form the basis for the definition of a length and a time scale. Multiplying the basic equation with vectors, pseudovectors, pseudoscalars and eventually hypercomplex numbers opens up the realm of possibilities to generate many further equations.

This paper explores a novel approach to modeling the positional dynamics of stars using discrete dynamical systems. We define star evolution through discrete-time update rules based on right ascension, declination, and distance, incorporating chaotic behavior via nonlinear functions and external perturbations. By applying Ricci flow and Riemannian metrics, we provide new insights into the positional dynamics of stars. Theoretical computations of Perelman entropy are used to assess system complexity, with high-precision Runge-Kutta methods ensuring accurate solutions for our chaotic model. We quantify chaos using Lyapunov exponents and perform bifurcation analysis to study how parameter variations affect the dynamics. Comparing our model to the Lorenz attractor reveals both similarities and unique characteristics in stellar dynamics. Our results show that entropy increases exponentially, indicating that predicting star positions with precision becomes increasingly challenging over time. This study advances the understanding of chaos in celestial systems and contributes to dynamical systems theory by integrating chaos theory with astronomical modeling.

L-17 is a thiadiazine derivative with putative anti-inflammatory, neuroprotective, and antidepressant-like properties. In this study, we applied combined in silico, ex vivo, and in vivo electrophysiology techniques to reveal the potential mechanism of action of L-17. PASS 10.4 Professional Extended software suggested that L-17 might have pro-cognitive, antidepressant, and antipsychotic effects. Docking energy assessment with AutoDockVina predicted that the binding affinities of L-17 to the serotonin transporter (SERT) and serotonin receptors 3 and 1A (5-HT3 and 5-HT1A) receptors are compatible to the selective serotonin reuptake inhibitor (SSRI) fluoxetine and selective antagonists of 5-HT3 and 5-HT1A receptors, granisetron and WAY100135, respectively. Acute pre-treatment with L-17 robustly increased c-Fos immunoreactivity in the amygdala (central nucleus), suggesting increased neuronal excitability in this brain area after L-17 administration. Acute L-17 also dose-dependently inhibited of 5-HT neurons of the dorsal raphe nucleus (DRN). This inhibition was partially reversed by subsequent administration of WAY100135, suggesting the involvement of extracellular 5-HT. Based on in silico predictions, c-Fos immunohistochemistry, and in vivo electrophysiology, we suggest that L-17 is a potent 5-HT reuptake inhibitor and/or partial 5-HT1A receptor antagonist. Thus, L-17 might be a representative of a new class of antidepressant drugs. Since L-17 also possesses neuro- and cardio-protective properties, it can be useful in post-stroke and post-myocardial infarction (MI) depression. In general, combined in silico predictions and ex vivo neurochemical and in vivo electrophysiological assessment might be a useful strategy for early preclinical assessment of the affectivity and neural mechanism in action of the novel CNS drugs.

The main foundations of the standard $\Lambda $CDM model of cosmology are that: 1) The redshifts of the galaxies are due to the expansion of the Universe plus peculiar motions; 2) The cosmic microwave background radiation and its anisotropies derive from the high energy primordial Universe when matter and radiation became decoupled; 3) The abundance pattern of the light elements is explained in terms of primordial nucleosynthesis; and 4) The formation and evolution of galaxies can be explained only in terms of gravitation within a inflation+dark matter+dark energy scenario. Numerous tests have been carried out on these ideas and, although the standard model works pretty well in fitting many observations, there are also many data that present apparent caveats to be understood with it. In this paper, I offer a review of these tests and problems, as well as some examples of alternative models.

One of the challenges of deploying Wireless Sensor Networks (WSN) at large scale is to operate for prolonged periods of time relying on the limited amounts of energy stored in its nodes. Generally, data communication is the main factor of draining energy. Consequently, reducing the amount of transmitted data by the nodes is of great interest. At the same time, reducing data to be transmitted should not decrease the quality of the deduced information. Solving this problematic is what we call in this article "Ensuring the Quality of Information Service (QoIS)". This document provides a state-of-the-art for the QoIS regarding WSNs. At first, we give a quick overview of the Internet of Things (IoT) paradigm and the WSN technologies in order to understand how data is gathered and used in these networks. Also, we introduce a novel concept: QoIS, in contrast with classic QoS. Then, it is expected a summary of criteria that asses the QoIS in WSNs plus some techniques to improve it. In this article, we will focus on data management techniques. These techniques can improve raw data, information and/or knowledge quality in energy-constrained WSNs. Finally, we give some conclusions and a glimpse about our future work.

Ambient vibration energy is widely being harnessed as a source of electrical energy to drive low-power devices. The vibration energy harvester (VEH) of interest employs an electromagnetic transduction mechanism, whereby ambient mechanical vibration is converted to electrical energy. The limitations affecting the performance of VEHs, with an electromagnetic transduction structure, include its operational bandwidth as well as the enclosure-size constraint. In this study, an analysis and design of a nonlinear VEH system is conducted, using the Output Frequency Response Function (OFRF) representations of the actual system model. However, the OFRF representations are determined from the Generalised Associated Linear Equation (GALE) decompositions of the system of interest. The effect of both nonlinear damping and stiffness characteristics, to respectively extend the average power and operational bandwidth of the VEH device, is demonstrated.

With a low rate of new building construction and insufficient rate of existing building renovation, there is the need for stepping up the pace of building renovation with ambitious performance targets to achieve EU climate change policies. However, effective technologies alone cannot solve the low renovation rate of existing buildings in Europe that is hindering the reaching of EU-wide targets. A workshop was held at the Sustainable Place Conference 2018 to present successful experiences with an integrative approach from H2020 innovation actions (4RinEU, P2ENDURE, Pro-GET-OnE, MORE-CONNECT) aiming at improving building energy performance through deep renovation. This article presents the outcomes of the joint workshop and interactive discussion, by focusing on the different technical, financial and social added values, barriers and challenges in building renovation as well as on the identification of open questions to address future innovation opportunities.

The process of building microgrids on top of existing passive distribution networks warrants a multi-criteria analysis. Besides the calculation of investment outlays needed for the modernization of distribution networks, such an analysis covers an assessment of the technological and economic effects of building microgrids. The resulting effects depend on the topology and configuration of distribution networks, specific microgrid features, the choice of current type for the entire microgrid or its individual parts, the ways of connecting distributed energy resources (DER), the availability and condition of information and communications technology (ICT) infrastructure, and other factors. Complete input data allow one to design an optimal microgrid configuration, but the main technological and economic effects are determined by the algorithms of operation and the parameters setting of the automatic control system (ACS) and the protection system. Known approaches to designing microgrids focus on addressing basic tasks while minimizing investment required for their implementation. The above is fully justified when constructing new microgrids, but building microgrids on top of existing distribution networks, given the uniqueness of their topology and configuration, does not allow the use of standardized solutions. The development of approaches to the design of microgrids under such constraints, with minimized investment for the modernization of existing distribution networks, is an urgent task. The use of different types of current for microgrid segments determines the choice of particular ACS and protection system, which depends on the availability of information and communications technology infrastructure. This article contributes a review of approaches to designing AC and AC-DC microgrids to maximize their technological and economic effects. We review techniques for analyzing existing distribution networks aimed at choosing the type of current for the entire microgrid or its individual parts, the optimal connection points of microgrids to distribution networks, the mix and capacity of DERs, with such choices informed by the condition of switching devices and information and communications technology infrastructure. The article presents the results of the analysis of approaches to choosing the optimal configuration of microgrids, microgrid ACS and protection system, with an evaluation of the technological and economic effects subject to minimization of investment for the modernization of existing distribution networks.

Lithium titanates are used in various applications, such as anode materials for lithium intercalation (Li4Ti5O12) or breeding materials in fusion reactors (Li2TiO3). Here, we report the formation of nano-crystalline lithium titanates by a mechanochemical approach and present a deeper insight into their structural characteristics by PXRD and solid-state NMR spectroscopy. The compounds were synthesized in a high energy planetary ball mill with varying milling parameters and different grinding tools. NaCl type Li2TiO3 (α-Li2TiO3) was formed by dry milling of lithium hydroxide with titania (rutile or anatase) and by a milling induced structure transformation of monoclinic β Li2TiO3 or spinel type Li4Ti5O12. Heating of mechanochemical prepared α Li2TiO3 induces a phase transformation to the monoclinic phase similar to hydrothermal reaction products, but a higher thermal stability was observed for the mechanochemical formed product. Microstructure and crystallographic structure were characterized by PXRD via Rietveld analysis. Detailed phase analysis shows the formation of the cubic phase from the various educts. A set of two lattice parameters for α Li2TiO3 was refined, depending on the presence of OH- during the milling process. An average crystallite size of less than 15 nm was observed for the mechanochemical generated products. The local Li environment detected by 6Li SPE MAS NMR revealed Li defects in the form of tetrahedral instead of octahedral site occupation. Subsequent adjustment of the structural model for Rietveld refinement leads to better fits, supporting this interpretation.

Adequate energy intake is critical for the healthy longevity of older adults, and the estimated energy requirement is determined by total energy expenditure (TEE). We aimed to identify the relationship between measured aerobic capacity and TEE, activity energy expenditure (AEE) or physical activity level (PAL) with the doubly labeled water (DLW) methods in the advanced older adults. A total of 12 physically independent older adults (10 males and 2 females) aged between 81 to 94 years participated in this study. Aerobic capacity was evaluated according to the lactate threshold (LT). TEE under free-living conditions was assessed using the DLW method, and self-reported physical activity was obtained through the Japanese version of the International Physical Activity Questionnaire (IPAQ). LT was significantly positively correlated with TEE, AEE, and PAL after adjustment for age and sex (ρ= 0.77 (P<0.01), 0.86 (p<0.01), and 0.86 (p<0.01), respectively). We found the LT as an aerobic capacity is positively and independently correlated with TEE, AEE or PAL. The present results suggest that maintaining aerobic capacity is an important factor for preventing frailty, although further research is needed to multisite studies and many samples.

This paper describes a Long Short-Term Memory (LSTM) neural network model used to simulate the dynamics of the OC3 reference design of a Floating Offshore Wind Turbine Spar unit. It crafts an advanced neural network with an encoder-decoder architecture capable of predicting the Spar’s motion and fairlead tensions time series. These predictions are based on wind and wave excitations across various operational and extreme conditions. The LSTM network, trained on an extensive dataset from over 300 fully coupled simulation scenarios using OpenFAST, ensures a robust framework that captures the complex dynamics of floating platform under diverse environmental scenarios. This framework’s effectiveness is further verified by thoroughly evaluating the model’s performance, leveraging comparative statistics and accuracy assessments to highlight its reliability. This methodology contributes to substantial reductions in computational time. This research aims to provide critical insights that facilitate the optimization of offshore wind turbines, marking a step forward in the quest for more efficient and dependable renewable energy solutions.

We try to solve three decades-old physics challenges. List all elementary particles. Describe dark matter. Describe mechanisms that govern the rate of expansion of the universe. We propose new modeling. The modeling uses extensions to harmonic oscillator mathematics. The modeling points to all known elementary particles. The modeling suggests new particles. Based on those results, we do the following. We explain observed ratios of dark matter amounts to ordinary matter amounts. We suggest details about galaxy formation. We suggest details about inflation. We suggest aspects regarding changes in the rate of expansion of the universe. We interrelate the masses of some elementary particles. We interrelate the strengths of electromagnetism and gravity. Our work seems to offer new insight regarding applications of harmonic oscillator mathematics. Our work seems to offer new insight regarding three branches of physics. The branches are elementary particles, astrophysics, and cosmology.

We develop and apply new physics theory. The theory suggests specific unfound elementary particles. The theory suggests specific constituents of dark matter. We apply those results. We explain ratios of dark matter amounts to ordinary matter amounts. We suggest details about galaxy formation. We suggest details about inflation. We suggest aspects regarding changes in the rate of expansion of the universe. The theory points to relationships between masses of elementary particles. We show a relationship between the strength of electromagnetism and the strength of gravity. The mathematics basis for matching known and suggesting new elementary particles extends mathematics for harmonic oscillators.

Three isoenergetic diets differing on their fishmeal/ soy protein concentrate (SPC) ratio were assessed on tissue growth and energy budget of juvenile crabs Scylla serrata in postmolt stages (PMolt) and in intermolt stages (IMolt). The average growth rate on dry matter basis, were 2.064 ± 0.324% and 0.492 ± 0.08% initial BW.day-1 during PMolt and IMolt stages respectively. The efficiency in feed conversion (FCE, %), protein retention (PRE, %) and energy retention (ERE, %) were similar for the 3 experimental diets. However, FCE, PRE and ERE in PMolt stages were 4 to 5 times higher than in IMolt stages. Feed intake, energy and protein required for growth in PMolt stages were obviously higher than in IMolt stages. The energy budgets (%total energy intake) were marginally affected by diet but were significantly affected by the molt stage. Maintenance energy was lower in PMolt stages (49.84 ± 4.9%) than in IMolt stages (83.33 ± 2.45%). The excess of maintenance energy in IMolt stages represents the portion set aside for next molt: shell energy content (4.97 ± 0.31%) and energy for ecdysis (± 28%). Conversely, recovery energy was significantly higher in PMolt stages (34.39 ± 0.99%) than in IMolt stages (8.33 ± 1.7%). In conclusion SPC sustained good tissue growth and good feed utilization and can be used as a main source of dietary protein for crab juveniles in captivity.

Quaternion algebra is used both for the description of the motion of material objects in 4D space-time and for the representation of the energy-momentum density tensor in the same quaternion basis, accurate to some arbitrary scalar fields. Quaternionic generating operators applied repeatedly to the energy-momentum density tensor lead to the gravitomagnetic equations that are parent equations for the series of physical equations ranging from the wave equations up to the quantum mechanical ones. Before finally deducing the gravitomagnetic equations, it is necessary to use the Lorentz gauge at a certain stage to cut off the arbitrary scalar fields. We declare that these superfluous scalar fields, inaccessible to direct observation, represent dark matter and dark energy. We show in what way the dark matter can provide a flat profile of the orbital speed of the galaxy's arm rotations.

Life Cycle Assessment (LCA) is a technique developed to measure possible environmental impacts during the manufacture and use of a given product or service. Additive Manufacturing (AM) has proven to be suitable in several industries, especially wire and arc additive manufacturing (WAAM), offering many advantages such as delivery time and reduction in terms of material waste, energy consumption and equivalent CO₂ emissions (CO₂e). This study aimed to develop a methodology to evaluate environmental indicators during the life cycle assessment, from gate-to-gate, in the production of two low-alloy carbon steel metal parts (flanges) using ER-90 wire and allowed identifying the main stages that most influence environmental indicators. The total energy consumption in the production of flanges 1 and 2 were, respectively, 10,239.0 MJ, 12,754.0 MJ and the total carbon footprint, respectively, 714.1 kgCO₂e kg^-1 and 749.3 kgCO₂e kg^-1.

Powder bed fusion (PBF) process is a metal additive manufacturing process which can build parts with any complexity from a wide range of metallic materials. PBF process research has predominantly focused on the impact of only a few parameters on product properties due to the lack of a systematic approach for optimizing a large set of process parameters simultaneously. The pivotal challenges regarding this process require a quantitative approach for mapping the material properties and process parameters onto the ultimate quality; this will then enable the optimization of those parameters. In this study, we propose a two-phase framework for optimizing the process parameters and developing a predictive model for 316L stainless steel material. We also discuss the correlation between process parameters -- i.e., laser specifications -- and mechanical properties and how to achieve parts with high density (> 98%) as well as better ultimate mechanical properties. In this paper, we introduce and test an innovative approach for developing AM predictive models, with a relatively low error percentage of 10.236% that are used to optimize process parameters in accordance with user or manufacturer requirements. These models use support vector regression, random forest regression, and neural network techniques. It is shown that the intelligent selection of process parameters using these models can achieve an optimized density of up to 99.31% with uniform microstructure, which improves hardness, impact strength, and other mechanical properties.

This article presents a comprehensive study on enhancing grid resilience through advanced forecasting and optimization techniques in the context of power outages. Power outages pose significant challenges to modern societies, affecting various sectors such as industries, households, and critical infrastructures. The research combines statistical analysis, machine learning algorithms, and optimization methods to address this issue to develop a holistic approach for predicting and mitigating power outage events. The proposed methodology involves the use of Monte Carlo simulations in MATLAB for future outage prediction, Long Short-Term Memory (LSTM) networks for forecasting solar irradiance and load profiles, and a hybrid LSTM-Particle Swarm Optimization (PSO) model to improve accuracy. Furthermore, the role of Battery State of Charge (SoC) in enhancing system resilience is explored. The study also assesses the techno-economic advantages of a grid-tied microgrid integrated with solar panels and batteries over conventional grid systems. The results highlight the potential of the proposed approach in strengthening grid resilience, reducing downtime, and fostering sustainable energy utilization.

Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against SARS-CoV-2 virus and resilience against mutational escape. In this work, we combined atomistic simulations and conformational dynamics analysis with the ensemble-based mutational profiling of binding interactions for a diverse panel of SARS-CoV-2 spike complexes with nanobodies. Using this computational toolkit, we identified dynamic signatures and binding affinity fingerprints for the SARS-CoV-2 spike protein complexes with nanobodies Nb6 and Nb20, VHH E, a pair combination VHH E+U, a biparatopic nanobody VHH VE, and a combination of CC12.3 antibody and VHH V/W nanobodies. Through ensemble-based deep mutational profiling of stability and binding affinities, we identify critical hotspots and characterize molecular mechanisms of SARS-CoV-2 spike protein binding with single ultra-potent nanobodies, nanobody cocktails and biparatopic nanobodies. By quantifying dynamic and energetic determinants of the SARS-CoV-2 S binding with nanobodies, we also examine the effects of circulating variants and escaping mutations. We found that mutational escape mechanisms may be controlled through structurally and energetically adaptable binding hotspots located in the host receptor-accessible binding epitope that are dynamically coupled to the stability centers in the distant epitope targeted by VHH U/V/W nanobodies. The results of this study suggested a mechanism in which through cooperative dynamic changes, nanobody combinations and biparatopic nanobody can modulate the global protein response and induce the increased resilience to common escape mutants.

Obesity-associated metabolic abnormalities comprise of a cluster of conditions including dyslipidemia, insulin resistance, diabetes, and cardiovascular diseases that has affected more than 650 million people all over the globe. Obesity results from accumulation of white adipose tissues mainly due to the chronic imbalance of energy intake and energy expenditure. Variety of approaches to treat or prevent obesity, including lifestyle interventions, surgical weight loss procedures and pharmacological approaches to reduce energy intake and increase energy expenditure have failed to substantially decrease the prevalence of obesity. Brown adipose tissue (BAT), the primary source of thermogenesis in infants and small mammals may represent a promising therapeutic target to treat obesity by promoting energy expenditure through non-shivering thermogenesis mediated by mitochondrial uncoupling protein 1 (UCP1). Since the confirmation of functional BAT in adult humans by several groups, approximately a decade ago and its association with a favorable metabolic phenotype, intense interest on the significance of BAT in adult human physiology and metabolic health has emerged within the scientific community to explore its therapeutic potential for the treatment of obesity and metabolic diseases. Substantially decreased BAT activity in individuals with obesity indicates a role for BAT in setting of human obesity. On the other hand, BAT mass and its prevalence has been reported to correlate with lower body mass index (BMI), decreased age and glucose levels, leading to lower incidence of cardio metabolic diseases. Increased cold exposure in adult humans with undetectable BAT was associated with decreased body fat mass and increased insulin sensitivity. Deeper understanding of the role of BAT in human metabolic health and its inter-relationship with body fat distribution and deciphering proper strategies to increase energy expenditure by either increasing functional BAT mass, or inducing white adipose browning holds the promise for possible therapeutic avenues for the treatment of obesity and associated metabolic disorders.

In our previous papers [1,3], using only the concepts of the zero-point energy and quantized space–times, all the fields including gravity were explained. However, the previous papers had the following limitations: First, the concept of the quantized space-time must be experimentally confirmed. Second, we should clarify the meaning of the quantized Einstein’s gravity equation, which is derived in [1]. Moreover, in another paper [2], we succeeded in describing the neutrinos’ self-energy and their oscillations. However, this paper assumes the rest energy of 3-leptons in advance, which is why we needed to uncover the reason why leptons have 3-generations. As mentioned, using the concepts of the zero-point energy and quantized space–times, we derived the quantized Einstein’s gravity equation in our previous paper [1]. The paper provides an analytical solution of this equalized Einstein’s equation, which implies the conservation of angular momentum in terms of quantized space–times. Employing this solution and without the standard big bang model, a unique form of acceleration equation for the acceleration-expansion universe is derived. Moreover, the temperature of the cosmic microwave background (CMB) emission is also obtained. Further, this solution results in an analytical (not numerical) derivation of the gravity wave. Moreover, based on the configuration of quantized space–times in terms of both electric and magnetic fields, we analytically attempted to calculate every equation in terms of electromagnetic and gravity fields, using the solution of the quantized Einstein’s gravity equation. As a result of this theory, first the calculated acceleration and temperature of CMB emission agree with the measurements. Furthermore, the analytical solution of the quantized Einstein’s gravity equation resulted in all the laws of electromagnetic and gravity fields in addition to the analytically derived gravity wave, which agrees well with the recent measurements. Moreover, the calculations of the energies in the basic configuration of the quantized space–times resulted in all 3-leptons’ rest energies. Considering this basic configuration is uniformly distributed everywhere in the universe, we can conclude that τ-particles or static magnetic field energy derived from the basic configuration of the quantized space–times is the identity of dark energy, which also distributes uniformly in the universe.

This paper discusses domestic problem of waiting hot water for the shower use till it reaches satisfactory temperature, which result a lot of wastage in fresh water. The outcome from research survey shows that there is no satisfactory solution till now as all solutions were either expensive or with no effective results. Local small inline electric heater equipped with fuzzy logic controller is proposed in this paper to be installed just before the showerhead to measure the water temperature and flow before the showerhead, as control input-variables, and decide the operating voltage of the heater, as control output-variable (MISO). MATLAB Simulink is used to model the proposed system. Different test cases are simulated to prove the performance and the safe operation of the system. Techno-economic study is carried out to determine the “Direct Benefits” and “Indirect Benefits” that can be achieved if such system is implemented in wide range. Azerbaijan data is taken as an example to calculate the economic benefits. The results show important benefits not only for economy but also for climate and the reduction of CO₂ gas emission. Different economic indices are provided to be an easy reference for decision makers and project managers.

The paper discusses the 2022 Nobel Prize in physics for experiments of entanglement “establishing the violation of Bell inequalities and pioneering quantum information science” in a much wider, including philosophical context legitimizing by the authority of the Nobel Prize a new scientific area out of “classical” quantum mechanics relevant to Pauli’s “particle” paradigm of energy conservation and thus to the Standard model obeying it. One justifies the eventual future theory of quantum gravitation as belonging to the newly established quantum information science. Entanglement, involving non-Hermitian operators for its rigorous description, non-unitarity as well as nonlocal and superluminal physical signals “spookily” (by Einstein’s flowery epithet) synchronizing and transferring some nonzero action at a distance, can be considered to be quantum gravity so that its local counterpart to be Einstein’s gravitation according to general relativity therefore pioneering an alternative pathway to quantum gravitation different from the “secondary quantization” of the Standard model. So, the experiments of entanglement once they have been awarded by the Nobel Prize launch particularly the relevant theory of quantum gravitation grounded on “quantum information science” thus granted to be nonclassical quantum mechanics in the shared framework of the generalized quantum mechanics obeying rather quantum-information conservation than only energy conservation. The concept of “dark phase” of the universe naturally linked to the very well confirmed “dark matter” and “dark energy” and opposed to its “light phase” inherent to classical quantum mechanics and the Standard model obeys quantum-information conservation, after which reversible causality or the mutual transformation of energy and information are valid. The mythical Big Bang after which energy conservation holds universally is to be replaced by an omnipresent and omnitemporal medium of decoherence of the dark and nonlocal phase into the light and local phase. The former is only an integral image of the latter and borrowed in fact rather from religion than from science. Physical, methodological and proper philosophical conclusions follow from that paradigm shift heralded by the 2022 Nobel Prize in physics. For example, the scientific theory of thinking should originate from the dark phase of the universe, as well: probably only approximately modeled by neural networks physically belonging to the light phase thoroughly. A few crucial philosophical sequences follow from the break of Pauli’s paradigm: (1) the establishment of the “dark” phase of the universe as opposed to its “light” phase, only to which the Cartesian dichotomy of “body” and “mind” is valid; (2) quantum information conservation as relevant to the dark phase, furthermore generalizing energy conservation as to its light phase, productively allowing for physical entities to appear “ex nihilo”, i.e., from the dark phase, in which energy and time are yet inseparable from each other; (3) reversible causality as inherent to the dark phase; (4) the interpretation of gravitation only mathematically: as an interpretation of the incompleteness of finiteness to infinity, for example, following the Gödel dichotomy (“either contradiction or incompleteness”) about the relation of arithmetic to set theory; (5) the restriction of the concept of hierarchy only to the light phase; (6) the commensurability of both physical extremes of a quantum and the universe as a whole in the dark phase obeying quantum information conservation and akin to Nicholas of Cusa’s philosophical and theological worldview.

This is a review on social laser theory completed with its new developments and applications. An important methodological step towards similarity with quantum physics is the invention and consistent operation with infons. These are excitations of the quantum social-information field carrying social energy and coarse grained content of communications (their color and quasi-color). We study in more detail interactions of infons with social atoms, the processes of absorption and emission (spontaneous and stimulated). We also analyze the dynamics of iterations of the cascades of infons in the social resonators. The latter are based on social networks coupled to laser's gain medium composed of social atoms. Consideration of the pro-war and pro-peace beams leads to the general discussion on the competing beams of social radiation and the conditions for their creation and coexistence. The role of social networks in lasing is illustrated by the protests during the COVID-19 pandemic. It is highlighted that a human gain medium can approach the state of population inversion with supply of infons of one sort (quasi-color), but the stimulated emission can be induced by injection into the gain medium of infons of a different quasi-color. We call this behavior of social atoms memorylessness. This theoretical property is illustrated with the examples from the modern social-political life.

The hetero Diels-Alder (HDA) reaction between the ambident heterodiene 3-methylene-2,4-chromandione (MCDO) and the non-symmetric methyl vinyl ether (MVE) is investigated within the Molecular Electron Density Theory (MEDT) at the B3LYP/6-311G(d,p) computational level. The aim of this study is to gain insight into the molecular mechanism and to elucidate the factors that control the selectivity found experimentally. DFT-based reactivity indices reveal that MCDO exhibits strong electrophilic character, while MVE displays a strong nucleophilic character. Meanwhile, Parr function explains the ortho regioselectivity of this HDA reaction. The highly polar nature of this HDA reaction, supported by the high global electron density transfer (GEDT) taking place at the transition state structures (TSs), accounts for the very low activation energy associated with the most favorable TS-4on. The ambident nature of MCDO allows the formation of two constitutional isomeric cycloadduct. In the case of MVE, the pseudocyclic selectivity is attained by a thermodynamic control. This polar HDA reaction displays an endo stereoselectivity and a complete ortho regioselectivity. A comparative Relative Interacting Atomic Energy (RIAE) analysis of the two diastereomeric TS-4on and TS-6on indicates a highly likeness between them, which explains the low pseudocyclic selectivity under kinetic control.

The incorporation of electric vehicles (EVs) with vehicle-to-grid (V2G) offers the development of multi-energy microgrid (MMOs) models. However, MMOs have among their goals to decrease electricity costs by coordinating with vehicle-to-grid (V2G) scheduling. Controlling V2G models poses uncertainties about the voltages developed and creates the need for power generation disruptions. In this work, a Feed-Forward-Back-Propagation Network (FFBPN) is developed with Matlab software, based on the Levenberg-Marquardt algorithm by varying the number of hidden neurons to realize better performance thanks to the value of the Maximum Coefficient of De-termination (R2) and the Minimum Mean Squared Error (MSE). In this article, the dataset from NASA PCoE has been used to make proper consideration of the model that best calculates the life cycle of the battery, demonstrating relevant implications for future development of this type of system based on FFBPN for the integration of EV into V2G. The proposed FFBPN demonstrates better performance than other methods taken from the literature. In conclusion, the comparison between the phases of training, validation and test are used to completely represent the validity of the proposed model and precisely to identify the characteristics curves of FFBPN for future ap-plications highlighting its performance to create profitability, efficiency, production, energy saving and minimum environmental impact.

A straightforward way to avoid the problem of the infinite zero-point energy principally is to negate the axiom of infinity of Zermelo-Fraenkel set theory. However, in so doing the real numbers and, as a corollary, the concept of infinitesimals would be given up making mathematical analysis, as it is known today, impossible. That said, consider a set whose members uniquely index points comprising a region of space. Providing four binary operations and their properties are defined on an index set, it is a field. The present paper demonstrates that to find the characteristic of an index field of the space of the observable universe is computationally intractable. Accordingly, such field cannot be distinguished from that of characteristic zero in any way possible. Meaning that one can negate the axiom of infinity and still use the real numbers inside the space of the observable universe for all intents and purposes.

Different researchers analyzed effective computational methods that maintain the precision of Allen-Chan (AC) equations and their constant security. This article presents a method known as reduced order model technique by utilizing kernel principle component analysis (KPCA), a nonlinear variation of traditional principal component analysis (PCA). KPCA is utilized on the data matrix created using discrete solution vectors of the AC equation. In order to achieve discrete solutions, small variations are applied for dividing up extraterrestrial elements, while Kahan’s method is used for temporal calculations. Handling the process of backmapping from small-scale space involves utilizing a non-iterative formula rooted in the concept of the multi-dimensional scaling (MDS) method. Using KPCA, we show that simplified sorting methods preserve dissipation of energy structure. The effectiveness of simplified solutions from linear PCA and KPCA, the retention of invariants, and computational speeds are shown through one-, two-, and three-dimensional AC equations.

As is known, the Maxwell stress-energy tensor typically used in electromagnetism is not a canonical tensor in the sense of Noether, since its four-divergence is not zero in the presence of sources, in other words, outside of free space. Indeed, the result provided by the calculation of the four-divergence of this tensor is the opposite of the four-vector generalizing the Lorentz force density. The idea is to associate with it a tensor constructed from potentials and sources, such that its four-divergence is the opposite of that of the Maxwell tensor. The distribution of sources will also be analyzed in light of fluid mechanics, allowing us to account for its influence in terms of generated pressure.

At present, under the background of high-quality development and the “carbon peaking and carbon neutrality” goal, China’s economic structure, industrial structure and energy structure have all begun green transformation and upgrading. The supply chain has become an important starting point for energy conservation and carbon reduction. In this context, enterprises have also ushered in huge environmental risk challenges and innovative development opportunities. This paper adopts Entropy-Weighted TOPSIS comprehensive evaluation method to analyze the green supply chain performance of "B" company, a new energy leading company, based on the theory of green development and corporate social responsibility. By establishing a green supply chain evaluation criteria system including four dimensions of finance performance, environment performance, operation performance and innovation performance, the weight of each evaluation criterion is objectively analyzed and calculated, and the green supply chain performance of "B" company from 2018 to 2022 is ranked. Based on this, comprehensive evaluations and sub-dimension evaluation are carried out and suggestions for improvement are put forward. At the same time, we hope to help other new energy vehicle companies optimize their own green supply chain practice mode.

Industrial buildings have numerous energy-losing equipment, such as engines, ovens, boilers, and heat exchangers. Energy losses are related to inefficient energy use and lousy work conditions for the people inside the buildings. This work is devoted to the recovery of lost energy from industrial buildings. Firstly, the residual energy of the building is extracted to be used to warm water. Consequently, the work conditions of the people inside industrial buildings can be improved by maintaining the adequate temperature. The recovery energy is done by the multipurpose heat pump system (HP system). The working fluid used in the HP system is R134a, which is a traditional and cheap working fluid. The thermophysical properties of R134a are obtained through the PC-SAFT equation of state. This work presents a performance mapping based on the intercepted areas framework to evaluate which working conditions are the optimal operating variables. The latter depends on several key parameters, such as compressor work, heat delivery, heat absorbed, and exergetic efficiency. The results show that the optimal work conditions are found at different condenser and evaporator temperatures, and that may be limited by what the designer considers a good performance of the heat pump system.

This research review explores the synthesis of graphene quantum dots (GQDs) from biowaste for supercapacitor applications, driven by the need for sustainable and efficient energy storage technologies. GQDs, with their unique properties like high surface area and excellent conductivity, hold promise for enhancing supercapacitor performance. Various synthesis methods, including hydrothermal/solvothermal processes, chemical exfoliation, carbonization/pyrolysis, and microwave-assisted synthesis, are discussed alongside characterization techniques to evaluate GQD properties. Biowaste-derived GQDs demonstrate significant potential by improving specific capacitance and cycling stability in supercapacitor electrodes. Challenges such as scalability and material purity are identified, with future directions focusing on enhancing energy density, cycle life, and cost-effectiveness to propel the adoption of biowaste-derived GQDs in commercial energy storage applications.

This qualitative research investigates the effectiveness of certification programs in ensuring supply chain sustainability within the renewable energy sector. Through interviews and content analysis, the study explores stakeholder perceptions, challenges, and impacts of certification initiatives. Findings reveal diverse motivations driving certification adoption, including regulatory compliance, market differentiation, and corporate social responsibility. However, challenges such as greenwashing and limited transparency undermine the credibility and effectiveness of certification programs. Despite these challenges, certification initiatives drive incremental improvements in environmental performance and stakeholder engagement, fostering a culture of continuous improvement and innovation. Multi-stakeholder collaboration and context-specific approaches are essential to address regional disparities and promote sector-wide transformation. Strategies for improvement include strengthening monitoring and enforcement mechanisms, integrating emerging technologies, and aligning certification standards with broader sustainability goals. Overall, certification programs offer a pathway for promoting transparency, accountability, and responsible business practices within the renewable energy supply chain, contributing to the transition towards a more sustainable and resilient energy future.

: Climate change necessitates urgent actions to mitigate carbon dioxide (CO2) emissions from fossil fuel-based energy generation. Among various strategies, the deployment of carbon capture and storage (CCS) solutions are critical for reducing emissions from point sources such as power plants and heavy industries. In this context, cryogenic carbon capture (CCC) via desublimation has emerged as a promising technology. While CCC offers high separation efficiency, minimal downstream compression work, and integration potential with existing industrial processes, challenges such as low operating temperatures and equipment costs persist. Ongoing research aims to address these hurdles in order to optimize the desublimation processes for widespread implementation. This review consolidates diverse literature works, providing insights into the strengths and limitations of CCC technology, including the latest pilot plant scale demonstrations. The transformative potential of CCC is first assessed on a theoretical basis, such as thermodynamic aspects and mass transfer phenomena. Then, recent advancements in the proposed process configurations are critically assessed and compared through key performance indicators. Furthermore, future research directions for this technology are clearly highlighted.

The work aims to improve the battery performance in hybrid electric vehicles (HEVs) by reducing the vehicle speed. We develop a specific protocol for managing battery use and optimizing the energy consumption rate to achieve this goal. The protocol automatically controls the driving operation, avoiding incompatible driving patterns with energy-saving mode and performance improvement. The protocol is submitted to a simulation process to predict the energy rate lowering and battery performance enhancement. The proposed protocol applies to any hybrid electric vehicle type and route conditions since it uses vehicle mass, drag and rolling coefficients, and road slope as variable parameters to determine the minimum energy consumption rate. We run experimental tests to validate the simulation data and the proposed protocol. Furthermore, the protocol applies to variable starting vehicle speeds, from 10 to 50 km/h, corresponding to the current driving patterns, sport, normal, and eco, set up by car manufacturers. A reduction of 10% in vehicle speed in urban and peripheral routes achieves a minimum energy rate, enhancing battery management. Current vehicle speed shows a deviation from optimum management of 18% while applying the vehicle speed reduction limits the deviation to 0.2%. Experimental results show a good agreement with simulation data with 94% accuracy. We tested the protocol for urban and peripheral routes with maximum vehicle speed limits of 60 and 90 km/h.

Entropy generation, formulated by combining the first and second laws of thermodynamics with an appropriate thermodynamic potential, emerges as the difference between a phenomenological entropy function and a reversible entropy function. The phenomenological entropy function is evaluated over an irreversible path through thermodynamic state space via real time measurements of thermodynamic states. The reversible entropy function is calculated along an ideal reversible path through the same state space. Entropy generation models for various classes of systems—thermal, externally loaded, internally reactive, open and closed––are developed via selection of suitable thermodynamic potentials. Here we simplify thermodynamic principles to specify convenient and consistently accurate system governing equations and characterization models. The formulations introduce a new and universal Phenomenological Entropy Generation (PEG) theorem. The systems and methods presented––and demonstrated on grease degradation, battery charging and discharging, metal fatigue and pump flow––can be used for design, analysis, and support of diagnostic monitoring and optimization.

We consider the restrictions on photovoltaic (PV) capacity that are caused by limitations on where panels can be sited, and find quantitative evidence for the need for high efficiencies. We define 15% of the UK’s energy consumption as a “significant” contribution and, with London as an exemplar, we perform an idealised calculation that makes the most optimistic possible assumptions about the capabilities of future PV technologies, and use published surveys of energy usage, dwelling type and insolation. We find that covering every UK domestic roof with the highest power-conversion efficiency (PCE) solar panels currently commercially available, could produce up to 9% of the UK's energy. A 15% contribution would require PV technologies with &gt;37% PCE, more than the theoretical Shockley-Queisser limit. Replacing the idealising assumptions with more realistic estimates increases this by 2-3 times. Alternatively, a solar farm using the currently available PCEs would require a politically challenging ~1200km2 of new land, roughly the area of Greater London, for this 15% contribution. We conclude that PCEs must be driven higher even than the Shockley-Queisser limit for PV to play a significant part in carbon mitigation.

Domestic heating systems in the UK and across northern Europe are responsible for a substantial fraction of their countries’ carbon footprints. In the UK the vast majority of home space heating is via natural gas boilers with ’wet’ hydronic radiator systems. Most of those use TRVs (Thermostatic Radiator Valves) to avoid overheating, improve comfort and save energy. To meet Net Zero targets 20 million such UK gas systems may be retrofitted with heat pumps. Heat pump system designers and installers are cautious about retaining TRVs in such retrofitted systems in part because of worries that TRV temperature setbacks that lower heat demand may actually raise heat pump electricity demand in a "bad setback effect", thus wasting energy. This paper presents a new view of heat pump control and provides the first exploration of this issue, modelling one such industry claim, and finds that though real it should not apply to typical UK retrofits with weather compensation. The energy efficiency benefits of TRVs for older and partly-occupied homes, and to keep bedrooms cooler, remain valid. Comfort-seeking householders and installers should know that setting ’stiff’ temperature regulation may invoke the bad setback effect and cost dearly in energy and carbon footprint.

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. Carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China's future carbon quota allocation will gradually transition from free allocation to auction allocation,the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism and constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model and systematically researches the power generation structure under different auction ratios with the time scale of months and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions.The results of the study show that after comprehensively comparing the total economic cost, renewable energy development and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits.

The present state of the natural environment is significantly influenced by the construction sector. Due to the large amounts of consumed natural resources and materials as well as the high volume of emitted pollutants, the building industry is considered to have a key influence in achieving a global sustainable development. A considerable part of the ecological impact of the built environment is influenced by the energy consumed for creating appropriate indoor conditions as well as by the greenhouse gases that are emitted during the operation stage of a building’s life cycle. Therefore, the energy performances of existing buildings must be significantly improved in the near future. This paper analyzes the influence of the thermal insulation thickness of walls on the linear thermal transmittances and the heating demand of an existing building. The resulted values show that while increasing the insulation of the walls leads to a serious heat demand reduction, a deep renovation of the building cannot be achieved solely by using this solution.

Zambia recently experienced extended hours of load shedding due to reduced hydroelectricity generation attributed to poor rainfall patterns. The inability to meet energy demand has influenced the government to consider alternative energy sources. This study aims to assess the economic feasibility of the eight sites using a 25-turbine layout for a 4 MW generic wind turbine at 130m hub height. An economic evaluation mathematical model was developed to analyze the economic feasibility using net present value, simple payback period, internal rate of return, and levelized cost of electricity (LCOE). The study shows that the Lusaka wind farm was the most economical with 386 GWh energy yield analysis (EYA), wind speed of 8 m/s, NPV of 316 million dollars, SPP of 2.9 years, IRR of 82%, and LCOE of $0.182/ kWh. The results also show that the other seven sites are economically feasible, with Petauke being the lowest. The study's economic sensitivity analysis conducted by varying the average electricity tariff shows that Lusaka was the most financially viable site. Therefore, policymakers should develop cost-reflective feed-in tariff (FiT) schemes and power purchase agreements for the country to have cost-reflective electricity tariffs that will motivate independent power producers to invest in Zambia.