Boosting the activity of FeOOH via integration of ZIF-12 and graphene to efficiently catalyze the oxygen evolution reaction

Transition metal oxyhydroxides have been used as promising electrocatalysts for water splitting however, their catalytic activity is restricted due to low surface area and poor conductivity. Herein, we report novel composite FeOOH@ZIF-12/graphene composite as electrocatalyst for water oxidation, whereby ZIF-12 provide extra surface for the FeOOH dispersion whilst graphene act as excellent electron mediator. The composite shows a low overpotential value of 291 mV to attain a current density of 10 mA cm^?2 and a low Tafel slope value of 78 mV dec^?1. The catalyst offers a maximum current density of 101 mA cm^?2, while it gives a turnover frequency (TOF) value of 0.031 s^?1 at an overpotential of 291 mV only. The excellent activity and remarkable stability of composite is attributed to highly conductive and porous support.     

Effect of Mg2+-Fe3+ replacement on physical and electrical properties of the system MgxZn0.3Fe2.7−xO4±δ

X-ray analysis and d.c. electrical resistivity have been studied for the system Mg _x Zn_0.3Fe_2.7–x O_4± . The apparent density, X-ray density and porosity were also studied. It was found that the lattice parameter is independent of the substitution of iron ions with magnesium ions. Density, X-ray density and porosity do depend on replacement of the iron ions by magnesium ions. Two regions of resistivity were found; one region indicates the p-type and another one the n-type. This behaviour depends on the excess or deficiency and type of valency of the iron ions in the composition.     

Note: Temperature derivative of the refractive index of binary mixtures measured by using a new thermodiffusion cell

A thermodiffusion cell is developed for performing Soret experiments on binary mixtures at high pressure and in the presence of a porous medium. The cell is validated by performing experiments at atmospheric pressure. The experiments are performed by applying different temperature gradients to binary mixtures in order to determine their thermal contrast factor. These measurements provide a first demonstration of the good reproducibility of this kind of measurements upon calibration.     

Optimal Machine Learning Enabled Performance Monitoring for Learning Management Systems

Learning Management System (LMS) is an application software that is used in automation, delivery, administration, tracking, and reporting of courses and programs in educational sector. The LMS which exploits machine learning (ML) has the ability of accessing user data and exploit it for improving the learning experience. The recently developed artificial intelligence (AI) and ML models helps to accomplish effective performance monitoring for LMS. Among the different processes involved in ML based LMS, feature selection and classification processes find beneficial. In this motivation, this study introduces Glowworm-based Feature Selection with Machine Learning Enabled Performance Monitoring (GSO-MFWELM) technique for LMS. The key objective of the proposed GSO-MFWELM technique is to effectually monitor the performance in LMS. The proposed GSO-MFWELM technique involves GSO-based feature selection technique to select the optimal features. Besides, Weighted Extreme Learning Machine (WELM) model is applied for classification process whereas the parameters involved in WELM model are optimally fine-tuned with the help of Mayfly Optimization (MFO) algorithm. The design of GSO and MFO techniques result in reduced computation complexity and improved classification performance. The presented GSO-MFWELM technique was validated for its performance against benchmark dataset and the results were inspected under several aspects. The simulation results established the supremacy of GSO-MFWELM technique over recent approaches with the maximum classification accuracy of 0.9589.     

Computational modeling of flow over an ogee spillway

This paper presents an investigation into the hydraulics of regular ogee-profile spillways. The free-surfaces of the fluid for several flow heads as measured in the hydraulics laboratory are used as benchmarks. The finite element computational fluid dynamics software, ADINA, was used to predict the free surface over an ogee spillway and thus model the flow field. Since the actual flow is turbulent the k-ε flow model was used. For the cases considered in this paper, ADINA predicted reasonable free surface results that are consistent with general flow characteristics over spillways. The results are also in close agreement with measured free-surface profiles over the entire length of the spillway.     

On the importance of specific interface area in clay nanocomposites of PMMA filled with synthetic nano-mica

In clay nanocomposites, the specific interface area is the key factor determining potential improvements of properties. Nevertheless, in most systematic studies of nanocomposites little emphasis is put on assuring and characterizing dispersion quality. To probe the influence of dispersion quality, we compare nanocomposites filled with two layered silicates which were made by melt compounding and solution blending, respectively. Poly(methyl methacrylate) (PMMA) is chosen here as a thermoplastic model matrix which was compounded with a synthetic nano-mica (O-hect) and commercial Bentone with typical diameters of 5–7 μm and <300 nm, respectively.     

A phase‑locked loop using ESO‑based loop flter for grid‑connected converter: performance analysis

An extended state observer (ESO)-based loop flter is designed for the phase-locked loop (PLL) involved in a disturbed gridconnected converter (GcC). This ESO-based design enhances the performances and robustness of the PLL, and, therefore, improves control performances of the disturbed GcCs. Besides, the ESO-based LF can be applied to PLLs with extra flters for abnormal grid conditions. The unbalanced grid is particularly taken into account for the performance analysis. A tuning approach based on the well-designed PI controller is discussed, which results in a fair comparison with conventional PItype PLLs. The frequency domain properties are quantitatively analysed with respect to the control stability and the noises rejection. The frequency domain analysis and simulation results suggest that the performances of the generated ESO-based controllers are comparable to those of the PI control at low frequency, while have better ability to attenuate high-frequency measurement noises. The phase margin decreases slightly, but remains acceptable. Finally, experimental tests are conducted with a hybrid power hardware-in-the-loop benchmark, in which balanced/unbalanced cases are both explored. The obtained results prove the efectiveness of ESO-based PLLs when applied to the disturbed GcC.     

The Negative Binomial Exponentially Weighted Moving Average Chart with Estimated Control Limits

The control chart based on the compound Poisson distribution (the negative binomial exponentially weighted moving average (EWMA) chart) has been shown to be more effective than the c‐chart to monitor the wafer nonconformities in semiconductor production process. The performance of the negative binomial EWMA chart is generally evaluated with the assumption that the process parameters are known. However, in many control chart applications, the process parameters are usually unknown and are required to be estimated. For an accurate parameter estimate, a very large sample size may be required, which is seldom available in the applications. This article investigates the effect of parameter estimation on the run length properties of the negative binomial EWMA charts. Using a Markov chain approach, we show that the performance of the negative binomial EWMA chart is affected when parameters are estimated compared with the known‐parameter case. We also provide recommendations regarding phase I sample sizes, smoothing constant and clustering parameter. The sample size must be quite large for the in‐control chart performance to be close to that for the known‐parameter case. Finally, a wafer process example has been used to highlight the practical implications of estimation error and to offer advice to practitioners when constructing/analysing a phase I sample. Copyright © 2013 John Wiley & Sons, Ltd.