Modeling and Simulation of Hydrogen Storage Device for Fuel Cell Plant

The article reviews a brief literature on the modeling of hydrogen storage device for fuel cell. Different dimensional approaches in modeling hydrogen absorption/desorption in a metal hydride reactor for use in fuel cell are summarized. Mathematical modeling equations involved are also stated. The effect of various operating parameters such as temperature, concentration, viscosity, thermal conductivity and time on the gas is also verified. The importance of various simulation software with reference to their major functions is also identified. The review concludes on the opportunities and challenges with the use of hydrogen as an alternative renewable energ

A novel coupler design and analysis with shielding material tests for a CPT system of electric vehicles based on electromagnetic resonant coupling

In this paper, a contactless power transfer (CPT) system using a novel geometrically enhanced energy transfer coupler with three different shielding materials has been built and analysed, along with the evaluations from aspects of electromagnetics and RMS power transmitting based on electromagnetic resonant coupling. A CPT system design improvement with the proposed H-shape ferromagnetic cores and the combined semi-enclosed passive electromagnetic shielding methods have been investigated in terms of generated electromagnetic field characteristics, system power transfer ratings, system efficiency optimization and performances of shielding materials. The results have shown that, across the range of operating frequency of the CPT system, aluminium shielding as a metallic material method could deliver better overall CPT system performance than other two ferromagnetic materials, steel 1010 and ferrite. In addition, the coupler prototype design limitations, misalignment tolerance and the passive shielding design considerations including distance between windings and inner surfaces of shielding shells have been discussed

Optical properties of metal nanoparticles with no center of inversion symmetry: observation of volume plasmons

We present theoretical and experimental studies of the optical response of L-shaped silver nanoparticles. The scattering spectrum exhibits several plasmon resonances that depend sensitively on the polarization of the incident electromagnetic field. The physical origin of the resonances is traced to different plasmon phenomena. In particular, a high energy band with unusual properties is interpreted in terms of volume plasmon oscillations arising from the asymmetry of a nanoparticle.Comment: 14 pages, 5 figures. Physical Review B, 2007, accepte

DEVELOPMENT AND CHARACTERIZATION OF POLYCAPROLACTONE (PCL)/POLY ((R)-3-HYDROXYBUTYRIC ACID) (PHB) BLEND MICROSPHERES FOR TAMOXIFEN DRUG RELESE STUDIES

Objective: The objective of this study was to formulate and evaluate the drug release studies using Poly (ε-caprolactone) (PCL)/and Poly (R)-3-hydroxy butyric acid (PHB) blend microspheres for controlled release of Tamoxifen, an anticancer drug.Methods: Poly (ε-caprolactone), Poly ((R)-3-Hydroxybutyric acid) blend microspheres were prepared through a modified Water/Oil/Water (W/O/W) double emulsion-solvent diffusion method using Dichloromethane as solvent. Tamoxifen (TAM), an anti Cancer drug, was used for encapsulation within PCL/PHB blend microspheres. Morphology, size, encapsulation efficiency and drug release from these microspheres were evaluated by different characterization techniques such as Fourier transform infrared spectroscopy (FT-IR), Differential scanning calorimetry(DSC), Scanning electron microscopy(SEM), X-ray diffraction studies(X-RD) and dissolution test studies respectively.Results: Drug loaded microspheres were analyzed by FT-IR, which indicates the interaction between drug and polymers. DSC thermograms on drug-loaded microspheres confirmed the polymorphism of Tamoxifen and indicated a molecular level dispersion of drug in the microspheres. SEM confirmed the spherical nature and smooth surface of the microspheres produced. X-RD study was performed to understand the crystalline nature of the drug after encapsulation into the microspheres and confirmed the complete dispersion of the drug in the polymer matrix. In-vitro release studies conducted in different pH which indicated a dependence of release rate on the amount of drug loading and the amount of PCL/PHB, but slow release rates were extended up to 12 h. Kinetic analysis of dissolution data showed a good fit in Peppas equation confirming diffusion controlled drug release.Conclusions: The research findings obtained from the studies were found to be satisfactory. It can be concluded that biodegradable polymer blend (PCL/PHB) microspheres can be effectively used for preparation of controlled release matrices. Â

Assessment of Machine Learning Classifiers for Heart Diseases Discovery

Heart disease (HD) is one of the utmost serious illnesses that afflict humanity. The ability to anticipate cardiac illness permits physicians to deliver better knowledgeable choices about their patient’s wellbeing. Utilizing machine learning (ML) to minimize and realize the symptoms of cardiac illness is a worthwhile decision. Therefore, this study aims to analyze the effectiveness of some supervised ML procedures for detecting heart disease in respect to their accuracy, precision, f1-score, sensitivity, specificity, and false-positive rate (FPR). The outcomes, which were obtained using python programming language were compared. The data employed in this investigation came from an open database of the National Health Service (NHS) heart disease which originated in 2013. Through the machine learning (ML) technique, a dimensionality reduction technique and five classifiers were employed and a performance evaluation between the three classifiers- principal component analysis (PCA), decision tree (DT), random forest (RF), and support vector machine (SVM). The NHS database contains 299 observations. The system was evaluated using confusion matrix measures like accuracy, precision, f1-score, sensitivity (TPR), specificity, and FPR. It is concluded that ML techniques reinforce the true positive rate (TPR) of traditional regression approaches with a TPR of 98.71% and f-measure value of 68.12%. The true positives rate which is the same as the sensitivity was used to evaluate the accuracy of the classifiers and it was deduced that the PCA + DT outperformed that of the other two with a sensitivity of 98.71% and since the value is on the high side, this implies that the classifier will be able to accurately detect a patient with HD in his or her body

Three-Dimensional FDTD Simulation of Biomaterial Exposure to Electromagnetic Nanopulses

Ultra-wideband (UWB) electromagnetic pulses of nanosecond duration, or nanopulses, have been recently approved by the Federal Communications Commission for a number of various applications. They are also being explored for applications in biotechnology and medicine. The simulation of the propagation of a nanopulse through biological matter, previously performed using a two-dimensional finite difference-time domain method (FDTD), has been extended here into a full three-dimensional computation. To account for the UWB frequency range, a geometrical resolution of the exposed sample was $0.25 mm$, and the dielectric properties of biological matter were accurately described in terms of the Debye model. The results obtained from three-dimensional computation support the previously obtained results: the electromagnetic field inside a biological tissue depends on the incident pulse rise time and width, with increased importance of the rise time as the conductivity increases; no thermal effects are possible for the low pulse repetition rates, supported by recent experiments. New results show that the dielectric sample exposed to nanopulses behaves as a dielectric resonator. For a sample in a cuvette, we obtained the dominant resonant frequency and the $Q$-factor of the resonator.Comment: 15 pages, 8 figure

Near-Surface Interface Detection for Coal Mining Applications Using Bispectral Features and GPR

The use of ground penetrating radar (GPR) for detecting the presence of near-surface interfaces is a scenario of special interest to the underground coal mining industry. The problem is difficult to solve in practice because the radar echo from the near-surface interface is often dominated by unwanted components such as antenna crosstalk and ringing, ground-bounce effects, clutter, and severe attenuation. These nuisance components are also highly sensitive to subtle variations in ground conditions, rendering the application of standard signal pre-processing techniques such as background subtraction largely ineffective in the unsupervised case. As a solution to this detection problem, we develop a novel pattern recognition-based algorithm which utilizes a neural network to classify features derived from the bispectrum of 1D early time radar data. The binary classifier is used to decide between two key cases, namely whether an interface is within, for example, 5 cm of the surface or not. This go/no-go detection capability is highly valuable for underground coal mining operations, such as longwall mining, where the need to leave a remnant coal section is essential for geological stability. The classifier was trained and tested using real GPR data with ground truth measurements. The real data was acquired from a testbed with coal-clay, coal-shale and shale-clay interfaces, which represents a test mine site. We show that, unlike traditional second order correlation based methods such as matched filtering which can fail even in known conditions, the new method reliably allows the detection of interfaces using GPR to be applied in the near-surface region. In this work, we are not addressing the problem of depth estimation, rather confining ourselves to detecting an interface within a particular depth range

Improved high-fidelity transport of trapped-ion qubits through a multi-dimensional array

We have demonstrated transport of Be+ ions through a 2D Paul-trap array that incorporates an X-junction, while maintaining the ions near the motional ground-state of the confining potential well. We expand on the first report of the experiment [1], including a detailed discussion of how the transport potentials were calculated. Two main mechanisms that caused motional excitation during transport are explained, along with the methods used to mitigate such excitation. We reduced the motional excitation below the results in Ref. [1] by a factor of approximately 50. The effect of a mu-metal shield on qubit coherence is also reported. Finally, we examined a method for exchanging energy between multiple motional modes on the few-quanta level, which could be useful for cooling motional modes without directly accessing the modes with lasers. These results establish how trapped ions can be transported in a large-scale quantum processor with high fidelity.Comment: 16 page

Evaluation of chitosan/sisal fiber/polyethylene membranes

Composites of ternary blend of chitosan/sisal fiber/high density polyethylene, were prepared by using the Rheomixer, followed by hot press, in order to form dense microfiltration membranes. The effective operation of the membranes was tested via the utilization of distilled water. The structural arrangement of the membranes was examined with the aid of using scanning electron microscopy (SEM). The chemical structure and phase identification of the membranes were examined using attenuation total reflectioninfrared spectroscopy (ATR-IR) and X-ray diffraction (XRD), respectively. The water permeability of the composite membranes is dependent on how rough the surface is, the sizes of pores and the membrane porosity. The membranes with highest amount of sisal fiber, gave highest flux of 1.4 m3/m2/h