Enhancing the photoelectrochemical water splitting characteristics of titanium and tungsten oxide based materials via doping and sensitization

To better utilize solar energy for clean energy production, efforts are needed to overcome the natural diurnal variation and the diffuse nature of sunlight. Photoelectrochemical (PEC) hydrogen generation by water splitting is a promising approach to harvest solar energy. Hydrogen gas is a clean and high energy capacity fuel. However, the solar-to-hydrogen conversion efficiency is determined mainly by the properties of the materials employed as photoanodes. Improving the power-conversion efficiency of PEC water splitting requires the design of inexpensive and efficient photoanodes that have strong visible light absorption, fast charge separation, and lower charge recombination rate. In the present study, PEC characteristics of various semiconducting photoelectrodes such as TiO2, WO3 and CuWO4 were investigated. Due to the inherent wide gap, such metal oxides absorb only ultraviolet radiation. Since ultraviolet radiation only composes of 4% of the sun's spectrum, the wide band gap results in lower charge collection and efficiency. Thusto improve optical absorption and charge separation, it is necessary to modify the band gap with low band gap materials.The two approaches followed for modification of band gap are doping and sensitization. Here, TiO2 and WO3 based photoanodes were sensitized with ternary quatum dots, while doping was the primary method utilized to investigate the modification of the band gap of CuWO4.The first part of this dissertation reports the synthesis of ternary quantum dot - sensitized titania nanotube array photoelectrodes. Ternary quantum dots with varying band gaps and composition (MnCdSe, ZnCdSe and CdSSe) were tethered to the surface of TiO2 nanotubes using succcessive ionic layer adsorption and reaction (SILAR) technique. The stoichiometry of ternary quantum dots was estimated to beMn0.095Cd0.95Se, Zn0.16Cd0.84Se and CdS0.54Se0.46. The effect of varying number of sensitization cycles and annealing temperature on optical and photoelectrochemical properties of prepared photoanodes were studied. The absorption properties and surface morphology of the sensitized tubes was analyzed using UV-visible spectroscopy and scanning electron microscopy. The phase composition was determined using X-Ray diffraction and X-ray photoelectron spectroscopy techniques. Electrodes were also evaluated for their stability using inductively coupled plasma optical emission spectrometry. Results show that the sensitization of TiO2 nanotubes with MnCdSe (8.79 mA/cm2), ZnCdSe (12.70 mA/cm2) and CdSSe (15.58 mA/cm2) resulted in up to a 30 fold increase in photocurrent compared to unsensitized nanotubes (0.4 mA/cm2).In the second part, the application of WO3 as photoanode for water splitting was explored. The porous thin films of WO3 films were sensitized with ternary quantum dots (ZnCdSe) using the SILAR technique. The structural, surface morphological and optical properties of the sensitized WO3 thin films were studied. PEC characteristics of the sensitized films were found to be 120 fold increase (8.53 mA/cm2) in comparisonto that of unmodified WO3 films (0.07 mA/cm2).In the last part of this dissertation, CuWO4 was investigated as the potential photoanode material. The band gap of CuWO4 was estimated using density functional theory (DFT) calculations. The band structure was obtained using the first-principles plane wave self-consistent field (pwscf) method and the effect of nickel dopant on the band gap and optical properties of CuWO4 was evaluated. Theoretical calculations showed that doping led to a decrease in band gap. The validity of the theoretical approach was evaluated by experimentally synthesizing Ni-doped CuWO4 electrodes. Experimental results showed that the bandgap indeed decreases when CuWO4 was doped with Ni, and thus validated the DFT approach. Ternary quantum dots were found to increase the PEC activity of TiO2 and WO3 based photoelectrodes by 120 fold. In addition, a method of computing band gap of semiconductor using DFT modeling was developed and validated with experimental results

The influence of a digital storytelling experience on pre-service teacher education students\u27 attitudes and intentions

This study explores the experiences of pre-service teachers\u27 with digital storytelling over a period of four weeks and examines their attitudes and intentions towards digital storytelling change during the course of the action research study. Both quantitative and qualitative data were collected for the study and mixed methods were used for analysis. There were no significant differences found between the means of pre and post-survey attitudes and intentions towards digital storytelling. Since the pre-survey attitudes and intentions were very positive, it is possible that the ceiling effect explains the lack of significant change. Significant themes emerged out of the three sets of qualitative data including expansion of knowledge beyond reading from a textbook, value of the research component, learning about the software, celebrating each other\u27s stories, personal connection with the topic, importance of storyboarding and the complete experience from beginning to end. In general, the pre-service teachers emerged from the digital storytelling experience with positive attitudes towards it and with plans to use this approach in their teaching. The study also provides recommendations for strengthening the digital storytelling experience in future pre-service teacher education class

Experimental Studies Towards Understanding the Aeromechanics of a Flexible Robotic Hummingbird Wing in Hover

This study investigated the aeroelastic mechanics of a flexible flapping wing designed and implemented on a two-winged, flapping wing, robotic hummingbird capable of hovering. The investigation focused first on measuring aerodynamic and inertial forces and using these results to quantify efficiency; second, on measuring vertical inertial forces on the flexible flapping wing for the first time using Digital Image Correlation; and three, on quantifying the flowfield using Particle Image Velocimetry at the 70% spanwise location of the wing. The purpose of these experiments was to optimize the lift generation and increase the efficiency of the hover-capable robotic hummingbird. A bench-top experimental setup was designed and developed which flapped a duplicate of the wing used in the actual flying vehicle, and utilized the same flapping kinematics. This setup allowed for the variation of flapping parameters, as well as measurement of performance metrics through sensors which measured the instantaneous lift, torque, flap angle, and current draw. The results found that 108° flapping amplitude at 20 Hz was the most power efficient. This is the first time instantaneous vertical force and torque measurements have been successfully conducted on a flexible, hover capable flapping wing used on a flying vehicle. Additionally, this study calculates vertical inertial loads for the same type of wing using deflection measurements. Results from this investigation can be used for further refinement and structural tuning of flexible flapping wing design for hovering flight

Local Image Patterns for Counterfeit Coin Detection and Automatic Coin Grading

Abstract Local Image Patterns for Counterfeit Coin Detection and Automatic Coin Grading Coins are an essential part of our life, and we still use them for everyday transactions. We have always faced the issue of the counterfeiting of the coins, but it has become worse with time due to the innovation in the technology of counterfeiting, making it more difficult for detection. Through this thesis, we propose a counterfeit coin detection method that is robust and applicable to all types of coins, whether they have letters on them or just images or both of these characteristics. We use two different types of feature extraction methods. The first one is SIFT (Scale Invariant Feature transform) features, and the second one is RFR (Rotation and Flipping invariant Regional Binary Patterns) features to make our system complete in all aspects and very generic at the same time. The feature extraction methods used here are scale, rotation, illumination, and flipping invariant. We concatenate both our feature sets and use them to train our classifiers. Our feature sets highly complement each other in a way that SIFT provides us with most discriminative features that are scale and rotation invariant but do not consider the spatial value when we cluster them, and here our second set of features comes into play as it considers the spatial structure of each coin image. We train SVM classifiers with two different sets of features from each image. The method has an accuracy of 99.61% with both high and low-resolution images. We also took pictures of the coins at 90˚ and 45˚ angles using the mobile phone camera, to check the robustness of our proposed method, and we achieved promising results even with these low-resolution pictures. Also, we work on the problem of Coin Grading, which is another issue in the field of numismatic studies. Our algorithm proposed above is customized according to the coin grading problem and calculates the coin wear and assigns a grade to it. We can use this grade to remove low-quality coins from the system, which are otherwise sold to coin collectors online for a considerable price. Coin grading is currently done by coin experts manually and is a time consuming and expensive process. We use digital images and apply computer vision and machine learning algorithms to calculate the wear on the coin and then assign it a grade based on its quality level. Our method calculates the amount of wear on coins and assign them a label and achieve an accuracy of 98.5%

The Effect of Earnings Announcement Distraction on Individual Trading Behaviour: An Attention-based Hypothesis

Research has shown that trading decisions by individual investors are influenced by behavioural factors such as attention effects. The literature examining the effects of attention on individual trading behaviour measures attention using proxies such as abnormal trading volume and stocks covered in the media. These proxies do not separate the effect of trading due to changing fundamentals from attention-based trading. I use the distraction caused by earning announcements to study the effect of attention on individual trading behaviour. Consistent with the literature, I find that investors net buy stocks with extreme positive and extreme negative earnings. However, this result is only significant when investors are most attentive (least distracted); that is, on days when the number of competing announcements is low. On high distraction days when investors make the wrong trading decision initially, they amend their prior trading decision after a lag (delayed reaction) when they eventually observe the true earnings of the stock. The most active investors amend this prior trading decision before relatively nonactive investors do. The delayed reaction by active investors is not portrayed for stocks with no analyst coverage, as evident in consistent net buying. The results remain robust even if surprise is measured using analyst forecasts; announcement distractions are limited to announcements in similar or very different industries

Sliding Window Persistence of Quasiperiodic Functions

A function is called quasiperiodic if its fundamental frequencies are linearly independent over the rationals. With appropriate parameters, the sliding window point clouds of such functions can be shown to be dense in tori with dimension equal to the number of independent frequencies. In this paper, we develop theoretical and computational techniques to study the persistent homology of such sets. Specifically, we provide parameter optimization schemes for sliding windows of quasiperiodic functions, and present theoretical lower bounds on their Rips persistent homology. The latter leverages a recent persistent K\"{u}nneth formula. The theory is illustrated via computational examples and an application to dissonance detection in music audio samples.Comment: 31 pages, 11 figure

Anti-microbial screening of some sulphonanilide complexes with Tm(III) ion against gram positive cocci & gram negative bacilli

A series of different sulphonanilide complexes with Tm(III) metal ion were prepared and the systems have been screened for anti-microbial activities by Bauer-Kirby discdiffusion technique against bacterial species such as Staphylococcus aureus, Pseudomonas aeruginosa and E.Coli (gram positive and gram negative) and were found to have moderate to significant activity against bacterialspecies

Regulation of neuronal differentiation by activity-induced calcium influx in striatal neural precursors

Neuronal activity induces Ca2+ influx that regulates neurogenesis and distinct aspects of neuronal differentiation in the embryonic and adult brain. This thesis focusses on the regulation of neuronal differentiation in striatal neural precursors (NPCs) by activity induced Ca2+ influx. Neurons arising from differentiating striatal NPCs show spontaneous Ca2+ transients, which are L type VGCC dependent. Neural activity increases the frequency of L type VGCC dependent Ca2+ transients. It also accelerates neuronal differentiation of striatal NPC derived neurons by promoting GABA expression and neurite outgrowth that are essential steps in establishing neuronal identity and enabling neurons to form functional connections. Although excitatory activity activates CREB, its effects on neuronal differentiation are transcription and translation independent. Furthermore, regulation of GABA expression and neurite outgrowth by neural activity involve distinct signaling pathways. Neurite outgrowth is regulated by NMDAR mediated localized Ca2+ influx that activates MAPK/CaMK and release of sAPP. On the other hand, GABA expression is regulated by PKA and PKC that are activated by VGCC induced global rise in Ca2+. Interestingly, a brief Ca2+ influx through VGCCs, induced by a short depolarizing stimuli, is sufficient to trigger an increase in GABA expression, whereas changes in neurite outgrowth require longer exposure to depolarization. Furthermore, neural activity accelerates GABA expression in neurons restricted to GABAergic fate, suggesting that these neurons express GABA synthesizing enzyme, GAD. Thus, it is conceivable that regulation of GABA expression by VGCC induced Ca2+ influx is achieved via phosphorylation/dephosphorylation of GAD by PKA and PKC. Thus, neural activity modulates NPC differentiation by inducing rapid responses that are transcription independent and that may be important in timely functional integration of newly generated neurons in the mammalian brain