The existence of a quantum spin liquid (QSL) in which quantum fluctuations of spins are sufficiently strong to preclude spin ordering down to zero temperature was originally proposed theoretically ...more than 40 years ago, but its experimental realization turned out to be very elusive. Here we report on an almost ideal spin liquid state that appears to be realized by atomic-cluster spins on the triangular lattice of a charge-density wave state of 1T-TaS2 . In this system, the charge excitations have a well-defined gap of ∼0.3 eV, while nuclear quadrupole resonance and muon-spin-relaxation experiments reveal that the spins show gapless QSL dynamics and no long-range magnetic order at least down to 70 mK. Canonical T2 power-law temperature dependence of the spin relaxation dynamics characteristic of a QSL is observed from 200 K to Tf = 55 K. Below this temperature, we observe a new gapless state with reduced density of spin excitations and high degree of local disorder signifying new quantum spin order emerging from the QSL.
Display omitted
•Study showed how changes in redox and SEP pools can control As availability.•As bound to Fe oxide phases remained intact in aerobic soil conditions.•Fe amendment enhanced the ...retention of As in amorphous, crystalline Fe oxide phases.•As fractions in soil solid phases can preferably model As availability to rice.•Cd response in rice to cultivation methods was different in wet and dry seasons.
Solid-phase As speciation and bioavailability during rice paddy cultivations depend on changes in cropping techniques and types of soil amendments. Field trials tested the impact of agronomic factors on As fractionation and resulting availability to rice, including aerobic (non-flooded) vs anaerobic rice cultivation (flooded); NPK, calcium silicate, ferrous sulfate, farmyard manure (FYM) and vermicompost (VC) addition. A modified sequential extraction procedure was used to determine As concentrations in the following soil fractions: exchangeable (F1); specifically sorbed (F2); amorphous iron oxide (F3); crystalline iron oxide (F4); organic matter and sulfide (F5); and residual bound (F6). Significant proportions of As were determined in F3, F4, and F6. Exchangeable fraction (F1) contained the lowest proportion of As. Aerobic cultivation practices significantly reduced soil As availability in F1 and resulted in higher retention of As in F2, F3, and F4. Application of ferrous sulfate increased As concentrations in F3 and F4 but when combined with FYM and VC, significantly lowered As concentrations in F1; a potential benefit for rice quality and consumer’s health. Linear regression analyses show that As concentrations in F1, F2, F3, and F4 are the most important factors influencing As accumulation in rice. Arsenic concentration in F1 is a good predictor of As accumulation in rice grain. The phytoavailability coefficient (PC) based on As retained in different fractional pools was determined. The addition of calcium silicate and ferrous sulfate under aerobic conditions reduced the PC in the soil, which could be responsible for reduced As accumulation in rice. There were insignificant variations in rice grain Cd concentrations between aerobic and anaerobic cultivations for monsoon trials, but significantly higher Cd concentrations were detected under aerobic cultivation than flooded cultivation for the post-monsoon trials. These data show that water management under different rice cropping practices can influence mobility and bioavailability of elements like As and Cd during rice paddy growth and can inform agricultural policy intended to attenuate element toxicity in edible crops, reducing their introduction into the food chain.
This paper presents a low‐voltage ride‐through technique for large‐scale grid tied photovoltaic converters using instantaneous power theory. The control strategy, based on instantaneous power theory, ...can directly calculate the active and reactive component of currents using measured grid voltage and currents and generate inverter switching pulses based on the formulated reference current values and thus helping to improve the dynamic response when voltage sag takes place. The dynamic response of the proposed model has been compared with both proportional‐integral and fuzzy current controllers to judge their suitability. The proposed strategy can provide both active and reactive power support dynamically during grid side fault. The proposed active reactive current control based technique shows better dynamic response compared to existing techniques. The proposed method is tested through appropriate simulation on a practical system to show the effectiveness of the proposed control method.
In the rotating machinery sector, active magnetic bearing (AMB) has drawn great attention due to its benefits over the conventional bearing system. The high-speed technology is enhanced by AMBs, ...which also reduce maintenance costs and eliminate friction loss. This paper presents a unique, simpler, efficient design and hardware implementation for high-speed applications using two-coil I-type active magnetic bearings. To maintain the 10 mm air gap between the actuator and the rotor, two categories of controllers have been designed for the proposed system to control the position and another for detecting the coil current through the power amplifier. The AMB system is incorporated into a 3D finite element model for determining magnetic properties. The magnetic analysis is then carried out under various situations, and the attractive force characteristics have been evaluated for this suggested system to check the performance of the multicoil AMB system along with the stability analysis. The system is designed and simulated in MATLAB Simulink and implemented in hardware to validate the different outputs viz. position response and current response. Finally, an AC magnet is designed to rotate the rotor after the levitation, and a higher speed of 19,643 rpm is achieved in comparison to conventional bearings, which can be utilized in different industrial applications.
Due to their inherent ability and environmentally friendly nature, renewable energy sources are the only real option for producing pollution-free energy in the modern era. Solar energy is one of the ...best possibilities in this family for supplying civilization with the power and energy it needs. Researchers can efficiently boost a PV panel’s efficiency by using the maximum power point tracking (MPPT) approach to extract the most power from the panel and send it to the load. The authors of this study examined and surveyed the sequential advancement of solar PV cell research from one decade to the next, and they elaborated on the upcoming trends and behaviours. Many maximum power point tracking algorithms (MPPTs) that are employed in photovoltaic systems (PVSs) that function under both uniform and partial shade situations are structurally summarized in this work. Well-written descriptions of the features of photovoltaic modules are followed by a variety of effective control strategies, including both AI-based and traditional controllers. In addition, appropriate knowledge of the various controllers is essential when the PV system is exposed to partial shade, keeping in mind the different control systems’ classifications in this situation. A thorough analysis of several soft computing-based techniques is also included, as well as many classical controller-based PV systems. First, well-developed traditional MPPT methods are used, followed by artificial intelligence-based MPPT approaches. Later, a thorough comparison of the various MPPT-controlling approaches is established. For PV systems operating under partial shade conditions (PSCs), the advantages and disadvantages of the various MPPT techniques are outlined, contrasted, and assessed. Future research directions for MPPT are also being investigated. A collection of several datasets pertaining to various control processes that were gleaned from various research articles has also been presented. Researchers working on PV-based MPPT and those working in the sectors of renewable energy production and environmentally sustainable development would be very interested in the findings of this review study.
Sustainable energy exhibited immense growth in the last few years. As compared to other sustainable sources, solar power is proved to be the most feasible source due to some unanticipated ...characteristics, such as being clean, noiseless, ecofriendly, etc. The output from the solar power is entirely unpredictable since solar power generation is dependent on the intensity of solar irradiation and solar panel temperature. Further, these parameters are weather dependent and thus intermittent in nature. To conquer intermittency, power converters play an important role in solar power generation. Generally, photovoltaic systems will eventually suffer from a decrease in energy conversion efficiency along with improper stability and intermittent properties. As a result, the maximum power point tracking (MPPT) algorithm must be incorporated to cultivate maximum power from solar power. To make solar power generation reliable, a proper control technique must be added to the DC–DC power converter topologies. Furthermore, this study reviewed the progress of the maximum power point tracking algorithm and included an in-depth discussion on modern and both unidirectional and bidirectional DC–DC power converter topologies for harvesting electric power. Lastly, for the reliability and continuity of the power demand and to allow for distributed generation, this article also established the possibility of integrating solar PV systems into nanogrids and picogrids in a sustainable environment. The outcome of this comprehensive survey would be of strong interest to the researchers, technologists, and the industry in the relevant field to carry out future research.
The output of photovoltaic (PV) systems is significantly impacted by the vagaries of ambient temperature, solar irradiance, and environmental fluctuations. To achieve the utmost attainable power from ...PV systems, it is desired to be efficient at the maximum power point in diverse weather climates. Maximum power point tracking (MPPT) is used to schedule a designated location from where the highest power can be harvested. In the context of solar photovoltaic systems connected with DC microgrid platforms, this study introduces a recently developed drone squadron optimization (DSO) scheme that tracks the global maximum power point under PSCS difficulties. Furthermore, an exhaustive comparative analysis has been presented among particle swarm optimization (PSO), cuckoo search algorithm (CUSA), and grey wolf optimization (GWO) under different operating environments to endorse the supremacy of the nominated technique. The suggested method performs noticeably faster than many other methods currently in use, and in addition to offering the highest power, it can also use bidirectional power flow regulation in both constant and variable air conditions. Lastly, an MPPT system interfaced with the DC microgrid based on DSO ensures a sustainable and reliable architecture to provide at load in low power generating situations.
This paper presents an efficient energy management strategy for Fuel Cell Hybrid Electric Vehicles (FCHEV) using a Machine Learning (ML) approach. Petroleum-based fuels are utilised in conventional ...cars to provide good performance and long-distance speed. There are certain disadvantages to using petrol or diesel, such as poor fuel economy and pollution-causing exhaust gas emissions. Furthermore, there are some limitations with existing available work, and the merger of these different optimisation techniques will be advantageous for achieving optimal performance. To address them, the purpose of this research is to create an efficient energy management approach by combining SVM, KNN, and the Naive Bayes technique. Additionally, by combining these classifier techniques better performing EMS is developed. Using the proposed features, the optimisation approach's performance accuracy is increased. Furthermore, these individual classifiers comprising of SVM, KNN & Naïve Bayes is giving accuracy percentage of 96%, 92% & 94% respectively. Finally, after combining these three classifiers we have achieved an accuracy percentage of 98%.
This study confers a novel approach towards fuzzy-PI (proportional–integral) controlled pulse width modulation (PWM) controlled permanent magnet synchronous motor (PMSM) drive operated through a ...conventional voltage source inverter (VSI) supplemented with buck-converter fed current source inverter (CSI). It is observed that in a PWM controlled VSI, output voltage and current obtained contains certain harmonic distortion. A buck-converter fed CSI is capable of minimising the voltage and current ripples prominently even with the application of PWM. Thereby, in this study, an economic, as well as robust design procedure for the buck converter, fed CSI is proposed. Moreover, a particle swarm optimisation (PSO) mechanism is introduced to optimise the performance of the proposed fuzzy logic controller. Additionally, an over-current protection scheme of the PMSM motor is proposed. The performance of a PMSM drive is analysed in MATLAB/SIMULINK platform. Furthermore, the proposed concept is tested and verified in a real-time test-bench developed in the laboratory. Finally, from the performed test conditions, it can be confirmed that the proposed current control strategy of the drive system shows excellent performance in various operating conditions and can be employed in light-weight electric vehicles.
The deployment of renewable energy sources has become more frequent in power system networks over the last few years. The prevalence of global warming and some catastrophic climate changes is rising, ...along with the demand for intricate transport systems, as a result of rapid growth in civilization and modernization in culture. To fight this environmental issue associated with vehicle transmission, almost every nation is promoting electric vehicles (EV). In this article, a novel method for developing a sliding mode maximum power point tracking (MPPT) controller for photovoltaic (PV) systems operating in rapidly varying atmospheric circumstances is put forward. Further, the standard Perturb and observe (Pb&O) algorithm's variable step is driven by the best sliding mode controller (SLMC) gains, which are determined using the Genetic Algorithm (GAO). Additionally, a PI controller, a grid employing current controlling topology, and an effective charging station constructed with GAO-optimized Sliding Mode-based reconfigurable step size Pb&O as an MPPT controller are executed and tested in MATLAB/Simulink for optimal control of power in the EV charging station. The main contribution of this study is to enhance the created controller's tracking performance to reach the maximum power point (MPP) with negligible oscillation, low overshoot, minimum ripple, and excellent speed in conditions of air turbulence that change quickly, as well as ensure continuity in supply to the EV. Furthermore, the developed system as a whole shows good efficacy compared with other existing systems reviewed in the literature. Finally, this proposed strategy ensures continuity of power supply to the charging station even in uncertain weather conditions, as grid integration also plays a vital role in the overall demand.
PDF
