Nanostructured Zn-Fe2O3 thin film modified by Fe-TiO2 for photoelectrochemical generation of hydrogen

Nanostructured semiconductor thin films of Zn-Fe₂O₃ modified with underlying layer of Fe-TiO₂ have been synthesized and studied as photoelectrode in photoelectrochemical (PEC) cell for generation of hydrogen through water splitting. The Zn-Fe₂O₃ thin film photoelectrodes were designed for best performance by tailoring thickness of the Fe-TiO₂ film. A maximum photocurrent density of 748 μA/cm² at 0.95 V/SCE and solar to hydrogen conversion efficiency of 0.47% was observed for 0.89 μm thick modified photoelectrode in 1 M NaOH as electrolyte and under 1.5 AM solar simulator. To analyse the PEC results the films were characterized for various physical and semiconducting properties using XRD, SEM, EDX and UV–Visible spectrophotometer. Zn-Fe₂O₃ thin films modified with Fe-TiO₂ exhibited improved visible light absorption. A noticeable change in surface morphology of the modified Zn-Fe₂O₃ film was observed as compared to the pristine Zn-Fe₂O₃ film. Flatband potential values calculated from Mott–Schottky curves also supported the PEC response.     

Power control and scheduling for guaranteeing quality of service in cellular networks

Providing quality of service (QoS) guarantees is important in the third generation (3G) and the fourth generation (4G) cellular networks. However, large‐scale fading and non‐stationary small‐scale fading can cause severe QoS violations. To address this issue, we design QoS provisioning schemes, which are robust against time‐varying large scale path loss, shadowing, non‐stationary small scale fading, and very low mobility. In our design, we utilize our recently developed effective capacity technique and the time‐diversity dependent power control proposed in this paper. The key elements of our QoS provisioning schemes are channel estimation, power control, dynamic channel allocation, and adaptive transmission. The advantages of our QoS provisioning schemes are (1) power efficiency, (2) simplicity in QoS provisioning, (3) robustness against large‐scale fading and non‐stationary small‐scale fading. Simulation results demonstrate that the proposed algorithms are effective in providing QoS guarantees under various channel conditions. Copyright © 2006 John Wiley & Sons, Ltd.     

Experimental and first-principles studies of BiVO4/BiV1-xMnxO4-y n-n+ homojunction for efficient charge carrier separation in sunlight induced water splitting

Though bismuth vanadate (BiVO₄) is extensively used as a photoactive material, its performance in harnessing solar energy is limited by ineffective separation of photo-excited charge carriers. We demonstrate here a concept of n-n⁺ homojunction of BiVO₄/BiV_1-xMn_xO_4-y, which improves its charge separation efficiency. Using first-principles theoretical calculations, we determine the effect of Mn substitution on oxygen vacancy formation energies and associated changes in the electronic structure of BiVO₄. Showing that Mn substitution pushes the Fermi level of BiVO₄ towards its conduction band, we predict that the associated enhanced bending of bands at the homojunction (BiVO₄/BiV_1-xMn_xO_4-y) facilitates efficient separation of charge carriers. With Mott-Schottky experiments, we verify the increased band bending at the n-n⁺ homojunction, and show that the maximum photocurrent density measured in a sample with n-n⁺ homojunction is ten times higher than that obtained of the pristine sample. Secondly, Mn substitution in BiVO₄ also reduces the oxygen vacancy formation energy, promoting higher concentration of O-vacancies, further enhancing the photoelectrochemical response.     

Correlation of interlayer diffusion with the stoichiometric composition of RF sputtered Pt/Co/Pt sandwiched structures

Sandwiched structures comprising Pt/Co/Pt layers with varying cobalt deposition time was studied and its importance on the alloy composition, by correlating the effective interlayer diffusion with the atomic stoichiometry, has been presented. A structural phase transition from ordered L1₂ CoPt₃ –? L1₀ CoPt –? L1₂ Co₃Pt was observed with increasing Co deposition time after annealing at 700 °C. The cross-sectional SEM image of the as-deposited film clearly shows a cobalt layer sandwiched between platinum layers. Rutherford back scattering (RBS) analysis shows a multipeak signature for the as-deposited films. A detailed RBS investigation on the extent of interatomic diffusion reveals an equiatomic composition for 20 and 30 min deposition time after annealing. The equiatomic CoPt phase shows a magnetically hard behaviour with a maximum coercivity of 15000 Oe. The reported dependence of (BH)_max on coercivity concludes that by tailoring an additional parameter of deposition time, diverse combinations of structural and magnetic properties can be achieved for appropriate practical applications.     

Improved hydrogen storage performance of Mg(NH2)2/LiH mixture by addition of carbon nanostructured materials

The effect of different carbon nanostructures specifically carbon nanotubes (CNTs) and carbon nanofibers (CNFs) on the improvement of the de/re-hydrogenation characteristics of a Mg(NH₂)₂/LiH mixture have been studied. Amongst CNTs and CNFs, the improvement in the hydrogenation properties for the Mg(NH₂)₂/LiH mixture is higher when CNFs are used as a catalyst. Investigations are also focused on the deployment of two different types of CNF (a) CNF1 (synthesized using a ZrFe₂ catalyst) and (b) CNF2 (synthesized using a LaNi₅ catalyst). The results show that CNF2 is better. The maximum decomposition temperature for the pristine Mg(NH₂)₂/LiH mixture is found to be ∼250 °C, which is reduced to ∼180 and ∼150 °C for the sample mixed with 4 wt% of multi-walled carbon nanotubes (MWCNTs) and CNF2 respectively. The activation energy for the dehydrogenation reaction is found to be 74 and 68 kJ mol⁻¹ for the samples mixed with MWCNT and CNF2 respectively, whereas the activation energy for the dehydrogenation reaction of the pristine Mg(NH₂)₂/LiH mixture is 97 kJ mol⁻¹. The catalytic activity and the de/re-hydrogenation characteristics of the Mg(NH₂)₂/LiH mixture mixed with different carbon nanostructures are described and discussed.     

Robust optimisation of machining conditions with tool life and surface roughness uncertainties

The economics of the multi-pass turning problem is considered, while accounting for tool life uncertainty. The goal is to minimise the expected production cost per part, given the probability distribution for tool life, and with machining parameters being subject to practical constraints. The cost function accounts for machining cost, idling cost, tool changing cost as well as the cost associated with tool failure. A modified version of the particle swarm optimisation (PSO) algorithm, called the dynamic objective PSO (or DOPSO), is used for minimisation of the cost function. The decision variables include not only the machining parameters but also the tool replacement time. The equality constraint that the total desired depth of cut be achieved by an integral number of roughing passes and a single finishing pass is handled in a novel way, and together with including tool replacement time as a decision variable, this leads to lower costs than those cited by other comparable previous works. To handle uncertain constraints that lead to part failure when violated (e.g. desired surface finish), a robust formulation is also suggested through similar incorporation in the cost function, as for tool failure.     

Classification of organic and biological materials with deep ultraviolet excitation

We show that native fluorescence can be used to differentiate classes or groups of organic molecules and biological materials when excitation occurs at specific excitation wavelengths in the deep ultraviolet (UV) region. Native fluorescence excitation-emission maps (EEMs) of pure organic materials, microbiological samples, and environmental background materials were compared using excitation wavelengths between 200-400 nm with emission wavelengths from 270 to 500 nm. These samples included polycyclic aromatic hydrocarbons (PAHs), nitrogen- and sulfur-bearing organic heterocycles, bacterial spores, and bacterial vegetative whole cells (both Gram positive and Gram negative). Each sample was categorized into ten distinct groups based on fluorescence properties. Emission spectra at each of 40 excitation wavelengths were analyzed using principal component analysis (PCA). Optimum excitation wavelengths for differentiating groups were determined using two metrics. We show that deep UV excitation at 235 (+/-2) nm optimally separates all organic and biological groups within our dataset with >90% confidence. For the specific case of separation of bacterial spores from all other samples in the database, excitation at wavelengths less than 250 nm provides maximum separation with >6sigma confidence.     

Computational Approaches for Studying the Granular Dynamics of Continuous Blending Processes, 2 – Population Balance and Data‐Based Methods

The application of computationally inexpensive modeling methods for a predictive study of powder mixing is discussed. A multidimensional population balance model is formulated to track the evolution of the distribution of a mixture of particle populations with respect to position and time. Integrating knowledge derived from a discrete element model, this method can be used to predict residence time distribution, mean and relative standard deviation of the API concentration in a continuous mixer. Low‐order statistical models, including response surface methods, kriging, and high‐dimensional model representations are also presented. Their efficiency for design optimization and process design space identification with respect to operating and design variables is illustrated.

     

Dynamic optimization of a dividing-wall column using model predictive control

Dividing-wall column (DWC) is one of the best examples of process intensification, as it can bring significant reduction in the capital invested as well as savings in the operating costs. Conventional ternary separations progressed from the (in-)direct sequences to thermally coupled columns such as Petlyuk configuration, and later to the DWC compact design that integrates the two distillation columns into a single shell. Nevertheless, this integration leads also to changes in the control and operating mode due to the higher number of degrees of freedom.In this work we explore the dynamic optimization and advanced control strategies based on model predictive control (MPC), coupled or not with PID. These structures were enhanced by adding an extra loop controlling the heavy component in the top of the feed side of the column, using the liquid split as manipulated variable, thus implicitly achieving energy minimization. To allow a fair comparison with previously published references, this work considers as a case-study the industrially relevant separation of the mixture benzene–toluene–xylene (BTX) in a DWC.The results show that MPC leads to a significant increase in performance, as compared to previously reported conventional PID controllers within a multi-loop framework. Moreover, the optimization employed by the MPC efficiently accommodates the goal of minimum energy requirements – possible due to the addition of an extra loop – in a transient state. The practical benefits of coupling MPC with PID controllers are also clearly demonstrated.     

Classification of Sunflower Oil Blends Stabilized by Oleoresin Rosemary (Rosmarinus officinalis L.) Using Multivariate Kinetic Approach

The sunflower oil–oleoresin rosemary (Rosmarinus officinalis L.) blends (SORB) at 9 different concentrations (200 to 2000 mg/kg), sunflower oil–tertiary butyl hydroquinone (SO_TBHQ) at 200 mg/kg and control (without preservatives) (SO_control) were oxidized using Rancimat (temperature: 100 to 130 °C; airflow rate: 20 L/h). The oxidative stability of blends was expressed using induction period (IP), oil stability index and photochemiluminescence assay. The linear regression models were generated by plotting ln IP with temperature to estimate the shelf life at 20 °C (SL₂₀; R² > 0.90). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to classify the oil blends depending upon the oxidative stability and kinetic parameters. The Arrhenius equation adequately described the temperature‐dependent kinetics (R² > 0.90, P < 0.05) and kinetic parameters viz. activation energies, activation enthalpies, and entropies were calculated in the range of 92.07 to 100.50 kJ/mol, 88.85 to 97.28 kJ/mol, ?33.33 to ?1.13 J/mol K, respectively. Using PCA, a satisfactory discrimination was noted among SORB, SO_TBHQ, and SO_control samples. HCA classified the oil blends into 3 different clusters (I, II, and III) where SORB₁₂₀₀ and SORB₁₅₀₀ were grouped together in close proximity with SO_TBHQ indicating the comparable oxidative stability. The SL₂₀ was estimated to be 3790, 6974, and 4179 h for SO_control, SO_TBHQ, and SORB₁₅₀₀, respectively. The multivariate kinetic approach effectively screened SORB₁₅₀₀ as the best blend conferring the highest oxidative stability to sunflower oil. This approach can be adopted for quick and reliable estimation of the oxidative stability of oil samples.