Photochemistry in Real Space: Batho- and Hypsochromism in the Water Dimer

The development of chemical intuition in photochemistry faces several difficulties that result from the inadequacy of the one-particle picture, the Born–Oppenheimer approximation, and other basic ideas used to build models. It is shown herein how real-space approaches can be efficiently used to gain valuable insights in photochemistry through a simple example of red and blue shift effects: the double hypso- and bathochromic shifts in the low-lying valence excited states of (H₂O)₂. It is demonstrated that 1) the use of these techniques allows the perturbative language used in the theory of intermolecular interactions, even in the strongly interacting short-range regime, to be maintained; 2) one and only one molecule is photoexcited in each of the addressed excited states and 3) the electrostatic interaction between the in-the-cluster molecular dipoles provides a fairly intuitive rationalisation of the observed batho- and hypsochromism. The methods exploited and illustrated herein are able to maintain the individuality and properties of the interacting entities in a molecular aggregate, and thereby they allow chemical intuition in general states, at any geometry and using a broad variety of electronic structure methods to be kept and built.     

Enhancement of Photocatalytic Activity for Hydrogen Production by Surface Modification of Pt-TiO2 Nanoparticles with a Double Layer of Photosensitizers

To investigate the effect of the surface structure of dye-sensitized photocatalyst nanoparticles, we prepared three types of Ru^II-photosensitizer (PS)-double-layered Pt-cocatalyst-loaded TiO₂ nanoparticles with different surface structures, Zr- RuCP⁶ -Zr- RuP⁶ @N wt %Pt-TiO₂, RuCP⁶ -Zr- RuP⁶ @N wt %Pt-TiO₂, and RuCP² -Zr- RuP⁶ @N wt %Pt-TiO₂ (N=0.2, 1, and 5), and evaluated their photocatalytic H₂ evolution activity in the presence of redox-reversible iodide as the electron donor. Although the driving force of the electron injection from I⁻ to the photo-oxidized Ru^III PS is comparable, the activity increased in the following order: RuCP² -Zr- RuP⁶ @1 wt %Pt-TiO₂ < RuCP⁶ -Zr- RuP⁶ @1 wt %Pt-TiO₂ < Zr- RuCP⁶ -Zr- RuP⁶ @1 wt %Pt-TiO₂. The apparent quantum yield of Zr- RuCP⁶ -Zr- RuP⁶ @1 wt %Pt-TiO₂ in the first hour reached 1 %. Zeta-potential measurements suggest that the surface Zr⁴⁺-phosphate groups attracted I⁻ anions to the nanoparticle–solution interface. Our results indicate that the surface modification of dye-sensitized photocatalysts is a promising approach to enhance photocatalytic activity with various redox mediators.     

Direct UVC photodegradation of imipramine in aqueous solutions: a mechanistic study

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Analytical and numerical studies for Seiches in a closed basin with bottom friction

A standing wave oscillation in a closed basin, known as a seiche, could cause destruction when its period matches the period of another wave generated by external forces such as wind, quakes, or abrupt changes in atmospheric pressure. It is due to the resonance phenomena that allow waves to have higher amplitude and greater energy, resulting in damages around the area. One condition that might restrict the resonance from occurring is when the bottom friction is present. Therefore, a modified mathematical model based on the shallow water equations will be used in this paper to investigate resonance phenomena in closed basins and to analyze the effects of bottom friction on the phenomena. The study will be conducted for several closed basin shapes. The model will be solved analytically and numerically in order to determine the natural resonant period of the basin, which is the period that can generate a resonance. The computational scheme proposed to solve the model is developed using the staggered grid finite volume method. The numerical scheme will be validated by comparing its results with the analytical solutions. As a result of the comparison, a rather excellent compatibility between the two results is achieved. Furthermore, the impacts that the friction coefficient has on the resonance phenomena are evaluated. It is observed that in the prevention of resonances, the bottom friction provides the best performance in the rectangular type while functioning the least efficient in the triangular basin. In addition, non-linearity effect as one of other factors that provide wave restriction is also considered and studied to compare its effect with the bottom friction effect on preventing resonance.     

Flume testing of passively adaptive composite tidal turbine blades under combined wave and current loading

The tidal energy industry is progressing rapidly, but there are still barriers to overcome to realise the commercial potential of this sector. Large magnitude and highly variable loads caused by waves acting on the turbine are of particular concern. Composite blades with in-built bend-twist elastic response may reduce these peak loads, by passively feathering with increasing thrust. This could decrease capital costs by lowering the design loads, and improve robustness through the mitigation of pitch mechanisms. In this study, the previous research is extended to examine the performance of bend-twist blades in combined wave–current flow, which will frequently be encountered in the field. A scaled 3 bladed turbine was tested in the flume at IFREMER with bend-twist composite blades and equivalent rigid blades, sequentially under current and co-directional wave–current cases. In agreement with previous research, when the turbine was operating in current alone at higher tip speed ratios the bend-twist blades reduced the mean thrust and power compared to the rigid blades. Under the specific wave–current condition tested the average loads were similar on both blade sets. Nevertheless, the bend-twist blades substantially reduced the magnitudes of the average thrust and torque fluctuations per wave cycle, by up to 10% and 14% respectively.     

An experimental investigation into non-linear wave loading on horizontal axis tidal turbines

Tidal turbines are subject to large hydrodynamic loads from combinations of currents and waves, which contribute significantly to fatigue, extreme loading and power flow requirements. Physical model testing enables these loads and power fluctuations to be assessed and understood in a controlled and repeatable environment. In this work, a 1:15 scale tidal turbine model is utilised to further the fundamental understanding of the influence of waves on tidal turbines. A wide range of regular waves are generated in both following-current and opposing-current conditions. Wave frequencies range from 0.31 Hz to 0.55 Hz & wave heights from 0.025 m to 0.37 m in a fixed 0.81 m/s current velocity. Waves are selected and programmed specifically to facilitate frequency domain analysis, and techniques are employed to isolate the effect of non-linear waves on turbine power and thrust.Results demonstrate that wave action induces large variations in turbine power and thrust compared to current only conditions. For the range of conditions tested, peak values of thrust and power exceed current-only values by between 7%–65% and 13%–160% respectively. These wave-induced fluctuations are shown to increase with wave amplitude and decrease with wave frequency. Following wave conditions exhibit greater variations than opposing for waves with the same wave height and frequency due to the lower associated wavenumbers.A model is developed and presented to aid the understanding of the high-order harmonic response of the turbine to waves, which is further demonstrated using steady state coefficients under assumptions of pseudo-stationarity. This approach is proven to be effective at estimating wave-induced power and thrust fluctuations for the combinations of waves, currents and turbine state tested. The outcome of which shows promise as a rapid design tool that can evaluate the effect of site-specific wave–current conditions on turbine performance.     

A safe minimum standard,the elasticity of substitution,and the cleanup of the Ganges in Varanasi

Despite repeated calls for a thorough cleanup of water pollution in the Ganges river, there are only two papers in the social sciences by Batabyal and Beladi (2017, 2019) that have shed theoretical light on this cleanup problem and its connection to the sustainability of tourism in Varanasi. Hence, we extend the above‐mentioned analyses and focus on two specific questions. First, we introduce the notion of a safe minimum standard (SMS) into the study and show how to analyze a probabilistic model of the Ganges cleanup problem when the SMS is accounted for. Second, for a representative citizen of Varanasi, we study how the magnitude of the elasticity of substitution between a composite consumption good and water quality in the Ganges—modeled by the SMS—affects the tradeoff between consumption and water quality maintenance.     

Multimetallic Oxynitrides Nanoparticles for a New Generation of Photocatalysts

A versatile synthetic strategy for the preparation of multimetallic oxynitrides has been designed and here exemplarily discussed considering the preparation of nanoscaled zinc–gallium oxynitrides and zinc–gallium–indium oxynitrides, two important photocatalysts of new generation, which proved to be active in key energy related processes from pollutant decomposition to overall water splitting. The synthesis presented here allows the preparation of small nanoparticles (less than 20 nm in average diameter), well-defined in size and shape, yet highly crystalline and with the highest surface area reported so far (up to 80 m² g⁻¹). X-ray diffraction studies show that the final material is not a mixture of single oxides but a distinctive compound. The photocatalytic properties of the oxynitrides have been tested towards the decomposition of an organic dye (as a model reaction for the decomposition of air pollutants), showing better photocatalytic performances than the corresponding pure phases (reaction constant 0.22 h⁻¹), whereas almost no reaction was observed in absence of catalyst or in the dark. The photocatalysts have been also tested for H₂ evolution (semi-reaction of the water splitting process) with results comparable to the best literature values but leaving room for further improvement.     

Microfunnel‐filter‐based emulsification microextraction followed by gas chromatography for simple determination of organophosphorus pesticides in environmental water samples

A simple and fast method named microfunnel‐filter‐based emulsification microextraction is introduced for an efficient determination of some organophosphorus pesticides including diazinon, malathion, and chlorpyrifos in the environmental samples including the river, sea, and well water. This method is based upon the dispersion of a low‐toxicity organic solvent (dihexyl ether), as the extractant, in a high volume of an aqueous sample solution (45 mL). It is implemented without a centrifugation step, and using a syringe filter and a micro‐funnel, the phase separation and transfer of the enriched analytes to the gas chromatograph are simply achieved. By filtration of the extractant phase, a suitable sample clean‐up is obtained, and the total extraction time is just a few minutes. The factors influencing the extraction efficiency are optimized, and under the optimal conditions, the proposed method provides a good linearity (in the range of 15–1500 ng/mL (R² > 0.996). A high enrichment factor is obtained (in the range of 306–342), and the method provides low limits of detection and quantification (in the ranges of 4–8 and 15–25 ng/mL, respectively).     

Neural network modeling of hydrological systems: A review of implementation techniques

This paper presents a review of procedural steps and implementation techniques used in the development of artificial intelligence models, generally referred to as artificial neural networks (ANNs), within the water resources domain. It focusses on identifying different areas wherein ANNs have found application thereby elucidating its advantages and disadvantages as well as various challenges encountered in its use. Results from this review provide useful insights into how the performance of ANNs can be improved and potential areas of application that are yet to be explored in hydrological modeling. Recommendations for Resource Managers

• Development of integrated and hybrid artificial intelligent tools is critical to achieving improved forecasts in hydrological modeling studies.

• Further research into comprehending the internal mechanisms of neural networks is required to obtain a practical meaning of each network component deployed to solve real‐world problems.

• More robust optimization techniques and tools like differential evolution, particle swarm optimization and deep neural nets, are yet to be fully explored in the water resources analysis, and should be given more attention to enhance neural networks aptitude for modeling complex and nonlinear hydrological processes.