ε-LiVOPO4 is a promising multielectron cathode material for Li-ion batteries that can accommodate two electrons per vanadium, leading to higher energy densities. However, poor electronic conductivity ...and low lithium ion diffusivity currently result in low rate capability and poor cycle life. To enhance the electrochemical performance of ε-LiVOPO4, in this work, we optimized its solid-state synthesis route using in situ synchrotron X-ray diffraction and applied a combination of high-energy ball-milling with electronically and ionically conductive coatings aiming to improve bulk and surface Li diffusion. We show that high-energy ball-milling, while reducing the particle size also introduces structural disorder, as evidenced by 7Li and 31P NMR and X-ray absorption spectroscopy. We also show that a combination of electronically and ionically conductive coatings helps to utilize close to theoretical capacity for ε-LiVOPO4 at C/50 (1 C = 153 mA h g–1) and to enhance rate performance and capacity retention. The optimized ε-LiVOPO4/Li3VO4/acetylene black composite yields the high cycling capacity of 250 mA h g–1 at C/5 for over 70 cycles.
In networked control systems (NCSs), the presence of communication networks in control loops causes many imperfections such as random delays, packet losses, multipacket transmission, and packet ...disordering. In fact, random delays are usually the most important problems and challenges in NCSs because, to some extent, other problems are often caused by random delays. In order to compensate for random delays which may lead to performance degradation and instability of NCSs, it is necessary to establish the mathematical model of random delays before compensation. In this paper, four major delay models are surveyed including constant delay model, mutually independent stochastic delay model, Markov chain model, and hidden Markov model. In each delay model, some promising compensation methods of delays are also addressed.
Geothermal power generation programs are crucial due to their long-term sustainability and environmentally friendly characteristics, particularly for potential energy-based applications in the ...future. Innovative designs can yield improve efficien by mitigating irreversibility, resulting in enhanced power production. Hence, this study investigates an innovative cascade thermal design model that employs geothermal resources to enhance the efficiency and output of low-temperature power generation systems, specifically through the integration of organic flash and organic Rankine cycles. Additionally, this model introduces a novel cogeneration approach by incorporating a desalination unit based on humidification-dehumidification processes, aiming to concurrently produce electricity and fresh water. Employing a combination of thermodynamic analysis and financial assessment, the system's performance was simulated and optimized in MATLAB, using the Multi-Objective Particle Swarm Optimization (MOPSO) method. A sensitivity analysis preceded the optimization, leading to the development of three distinct optimization scenarios focused on balancing power and freshwater production, maximizing exergetic efficiency and net present value, and optimizing fixed capital investment for maximum financial viability. The results highlight the second scenario as particularly effective, achieving a power generation of 254.3 kW, an exergetic efficiency of 44.84 %, and a net present value of $405,099. Conversely, the third scenario offers the best balance between freshwater production capacity (0.504 kg/s), fixed capital investment ($820,822), and a payback period of 7.12 years. This research demonstrates the potential of integrating advanced thermal models with geothermal resources for sustainable and efficient energy and freshwater production, marking a significant step forward in the development of eco-friendly cogeneration systems.
•Proposing an innovative geothermal-driven combined power plant and desalination process.•Thermodynamic/financial analysis and multi-criteria optimization using MOPSO algorithm.•Conducting comprehensive sensitivity analysis and three different optimization scenarios.•εcycle−NPV scenario shows superior exergy efficiency and NPV at 44.84 % and 405,099 $.•FCI−NPV scenario shows the lowest FCI and payback period of 820,822 $, and 7.12 years.
This article investigates the adaptive event-triggered finite-time dissipative filtering problems for the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy Markov jump systems (MJSs) with asynchronous ...modes. By designing a generalized performance index, the <inline-formula> <tex-math notation="LaTeX">H_{\infty } </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">L_{2}-L_{\infty } </tex-math></inline-formula>, and dissipative fuzzy filtering problems with network transmission delay are addressed. The adaptive event-triggered scheme (ETS) is proposed to guarantee that the IT2 T-S fuzzy MJSs are finite-time boundedness (FTB) and, thus, lower the energy consumption of communication while ensuring the performance of the system with extended dissipativity. Different from the conventional triggering mechanism, in this article, the parameters of the triggering function are based on an adaptive law, which is obtained online rather than as a predefined constant. Besides, the asynchronous phenomenon between the plant and the filter is considered, which is described by a hidden Markov model (HMM). Finally, two examples are presented to show the availability of the proposed algorithms.
This paper focuses on delay-dependent stability for a class of Markovian jumping systems with time delay, whose transition rates are not completely known. Taking into account the influence of time ...delay and partial information on transition probabilities, double integral inequality and extended Wirtinger's inequality are used to value the bounds of Lyapunov-Krasovskii function and their weak infinitesimal generator operator, and free-connection is applied to separate the unknown transition rates. As a result, improved stability criteria are derived. Finally, two examples are provided to show the effectiveness and the benefits of the proposed criteria.
A novel gain-scheduled switching control method for the longitudinal motion of a flexible air-breathing hypersonic vehicle (FAHV) is proposed. Firstly, velocity and altitude are selected as ...scheduling variables, a polytopic linear parameter varying (LPV) model is developed to represent the complex nonlinear longitudinal dynamics of the FAHV. Secondly, based on the obtained polytopic LPV model, the flight envelope is divided into four smaller subre-gions, and four gain-scheduled controllers are designed for these parameter subregions. Then, by the defined switching characteristic function, these gain-scheduled controllers are switched in order to guarantee the closed-loop FAHV system to be asymptotically stable and satisfy a given tracking error performance criterion. The condition of gain-scheduled switching controller synthesis is given in terms of linear matrix inequalities (LMIs) which can be easily solved by using standard software packages. Finally, simulation results show the effectiveness of the presented method.
Diamond-like carbon (DLC) coatings have demonstrated significant potential as solid lubricants for a wide range of applications. However, thermal-induced structural changes lead to alterations in its ...mechanical and frictional properties. In this study, we investigate the friction properties of DLC films after high-temperature annealing, by conducting reciprocating single asperity scanning experiments of self-mated hydrogen-free DLC tribopair under ultra-high vacuum (UHV) conditions. As the annealing temperature increases, the coefficients of friction (COFs) first increase owing to the desorption of water molecules; while, with the further increase of temperature, friction shows a decreasing trend because of the high-temperature-induced sp3-to-sp2 rehybridization which lowers the interfacial shear strength. The insights gained from this study provide a better understanding of the frictional properties of DLC films.
To comprehensively enhance the robust tracking performance, a leader–follower Stackelberg game oriented adaptive robust constraint-following control scheme has been proposed for a class of uncertain ...mechanical systems. In the proposed scheme, a fuzzy set-theoretic description represents the uncertainties (possibly fast time-varying), and an adaptive robust constraint-following control ensures the robust stability. With the fuzzy uncertainty description and control performance analysis, a leader–follower game theory is employed to obtain multiple optimal gains for the proposed control scheme. Further, the existence of these optimal parameters can be verified. The proposed approach is successfully applied to a lower limb exoskeleton (LLE) robot system for rehabilitation training.
The brain has been traditionally thought to be insensitive to insulin, primarily because insulin does not stimulate glucose uptake/metabolism in the brain (as it does in classic insulin-sensitive ...tissues such as muscle, liver, and fat). However, over the past 20 years, research in this field has identified unique actions of insulin in the brain. There is accumulating evidence that insulin crosses into the brain and regulates central nervous system functions such as feeding, depression, and cognitive behavior. In addition, insulin acts in the brain to regulate systemic functions such as hepatic glucose production, lipolysis, lipogenesis, reproductive competence, and the sympathoadrenal response to hypoglycemia. Decrements in brain insulin action (or brain insulin resistance) can be observed in obesity, type 2 diabetes (T2DM), aging, and Alzheimer's disease (AD), indicating a possible link between metabolic and cognitive health. Here, we describe recent findings on the pleiotropic actions of insulin in the brain and highlight the precise sites, specific neuronal population, and roles for supportive astrocytic cells through which insulin acts in the brain. In addition, we also discuss how boosting brain insulin action could be a therapeutic option for people at an increased risk of developing metabolic and cognitive diseases such as AD and T2DM. Overall, this perspective article serves to highlight some of these key scientific findings, identify unresolved issues, and indicate future directions of research in this field that would serve to improve the lives of people with metabolic and cognitive dysfunctions.
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