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Titanium dioxide is one of the earliest materials used in memristors. It is widely studied and researched due to its advantages of the simple preparation process, high dielectric constant, wide bandgap and chemical stability. In this paper, a two-step anodization process was used to prepare the oxidized nanotubes array, which served as the foundation for fabricating Ag/TiO₂/Ti memristors. The research delved into the impact of diverse oxidation voltages on the resistive performance of memristor and discussed the underlying mechanism for resultant performance.

The purpose of this paper is to establish a direct methanol fuel cell (DMFC) prediction model by using the support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm for its parameter selection. Two variables, cell temperature and cell current density were employed as input variables, cell voltage value of DMFC acted as output variable. Using leave-one-out cross-validation (LOOCV) test on 21 samples, the maximum absolute percentage error (APE) yields 5.66%, the mean absolute percentage error (MAPE) is only 0.93% and the correlation coefficient (R²) as high as 0.995. Compared with the result of artificial neural network (ANN) approach, it is shown that the modeling ability of SVR surpasses that of ANN. These suggest that SVR prediction model can be a good predictor to estimate the cell voltage for DMFC system.

A micro-thrust test system based on Michelson interferometer was proposed and tested. The relationship between thrust and output voltage of the calibration component in the system was calculated and verified with numerical modeling. The fitting function of the calibration component was obtained, which will be tested during future thrust test experiments.

Nowadays, the power quality (PQ)-related issues have become more prominent in power electronic devices. For compensating PQ disturbances various types of power devices are used. The unified power quality conditioner (UPQC) is one of the power electronic devices that is used for compensating the PQ. To reduce the PQ disturbances, the performance of series and shunt active power filters (APFs) must be improved. In this paper, an enhanced controller is proposed for improving the performance of series and shunt APFs and compensating the PQ. The enhanced technique used is the combination of artificial neural network (ANN) and gravitational search algorithm (GSA) which is used for generating the control signals of the APF and reducing the PQ problem. The shunt APF is used for reducing the harmonic disturbances. The DC-link voltage is regulated by utilizing the proposed enhanced controller technique. Subsequently, the THD value of the proposed system is measured. The proposed method is implemented in MATLAB/Simulink platform and its performance is evaluated. The performance of the proposed method is evaluated and compared with the base controller and ANN controller.

In distribution systems, it is important to guarantee the protected operating state of the power system by the transmission suppliers. To transmit a secure, dependable and economical supply of electric power, long separation bulk power transmission is fundamental. Despite that, the power transfer capacity of the power system is constrained because of the elements like thermal limits, voltage limits and security limits. Crow Search Optimizations (CSO) have been exhibited to be reasonable methodologies in taking care of nonlinear power system issues with Available Transfer Capability (ATC). It is conceivable to improve transmission capabilities. This proposed method based on the IEEE 30-bus system is considered with two distinct areas, and furthermore, the input source is a typical load system with a distributed network. There is a need to control the reactive power flow at the Point of Common Coupling (PCC) between the grids of various voltage levels. To operate a power system securely and furthermore to acquire the benefit of bulk power transfer, ATC evaluation is required. The load gets raised from 50% to 100% in the distribution side by including the thermal power plant (85% and 95% load is included) and with the procured condition, ATC and losses are to be determined. This ATC is determined for verified power supply to the consumers.

In this paper, a theoretical model was described to analyze the magnetic relaxations of samples of copper oxide thin film cells. Experimentally, the copper oxide thin film was characterized at different oxidation temperatures between 150°C to 450°C. The introduction of the Bloch NMR equations was developed to determine the functionality of the individual samples. The magnetic relaxation characterization confirmed the degree of disordered in the copper oxide sample. This disorderliness of the copper oxide sample engendered a magnetic instability which gave rise to magnetic deflagration. Magnetic deflagration was found to be dependent on the magnetic re-orientation initiated by the RF pulse. A new law was proposed which is a modification of the Arrhenius law.

In this study, two hydrogen sensors with Pd/SiO₂/Si and Ni/SiO₂/Si structures have been fabricated. Palladium nanoparticles are synthesized and then deposited on the oxide surface using spin coating. Capacitance–voltage curves for the Pd/SiO₂/Si sensor at room temperature and for the Ni/SiO₂/Si sensor at 140${}^{\circ }$C in pure nitrogen and 1% H₂–N₂ mixture are described. The time required for reaching 90% of the steady-state signal magnitude ($t_{90\%}$) for Pd/SiO₂/Si capacitor was 1.4s and for Ni/SiO₂/Si capacitor was 90 s. The time interval for recovery from 90% to 10% of steady-state signal magnitude ($t_{10\%})$ for Pd/SiO₂/Si capacitor was 14s and for Ni/SiO₂/Si capacitor was 40min. For the Pd/SiO₂/Si capacitor, the response is 88% and for Ni/SiO₂/Si capacitor the response is 29%. Comparison of Pd nanoparticles capacitive- and resistance-based sensors shows that the metal-oxide-semiconductor capacitive is faster and more sensitive than the resistance-based hydrogen gas sensors.

Magnetic and electronic properties of LiVOPO₄ and VOPO₄ cathodes have been studied using ab initio calculations, high temperature series expansions (HTSEs) calculations and Monte Carlo simulations (MCSs). Self-consistent ab initio calculations, based on Density Functional Theory approach (DFT) and using Full Potential Linear Augmented Plane Wave (FLAPW) method, were performed to investigate both electronic and magnetic properties of the LiVOPO₄. Polarized spin and spin–orbit coupling are included in calculations within the framework of the antiferromagnetic state between two adjacent V plans. Magnetic moments considered to lie along (010) axes are computed. Average equilibrium voltage over a full cycle ($V_{\mathrm{\text{cell}}}$) of the LiVOPO₄, battery have been estimated. Computed magnetic moments are used as input for HTSEs to compute other magnetic parameters using the mean field theory, MCSs and HTSEs. The obtained results by HTSEs and MCSs are comparable with experiments results.

UHV power flow is heavy in the south of Shanxi power grid, and voltage fluctuation is strenuous. Once the unreasonable reactive flow appeared between substations of near UHV grid, their discrete reactive power equipment can’t effectively support the regional voltage, and therewith the depressed reactive power store of the area. In the Automatic Voltage Control (AVC) system of Shanxi power grid, the studied should be focused on the control of near ultra high voltage (UHV) gird. This paper proposed a coordinating technology between 500kV substations in the same voltage area, which use the “active and passive” coordination to realize the refine control of near UHV grid, thus to improve its ability of dynamic reactive reserve and voltage control. 500kV Haihui substation and Jincheng substation of UHV grid nearby are taken for instance to analysis. The results verify that the technology come into effect.