Synthesis and Dielectric Characterization of Potassium Niobate Tantalate Ceramics

The preparation and dielectric properties of potassium niobate tantalate (KTN) have been investigated with the aim of exploring the material's potential for ferroelectric tunable applications. The samples were prepared both by conventional sintering in air and by uniaxial hot pressing. A relative average density greater than 92% was obtained with both methods. An inhomogeneous Nb/Ta distribution was found in the samples prepared by both methods, but the inhomogeneity extent was lower in the hot-pressed samples. While both sintering processes resulted in ceramics of lower transition temperatures in comparison with the reported results on single crystals, a relative up shift of the temperature ( T _max) at which the dielectric constant is maximum was found for hot-pressed samples compared with that of samples sintered in air. All the samples exhibited strong frequency dispersion in dielectric properties. The effect of DC bias at room temperature was measured and modeled using the Landau–Devonshire model. It was found that the nonlinear coefficient β of KTN, which is important for tunable applications, is comparable with the value reported on KNbO₃ and SrTiO₃ single crystals. A dielectric tunability of 16% and 42% at room temperature was demonstrated under 20 kV/cm for the sintered and hot-pressed ceramics, respectively. The loss tangent, low at megahertz frequencies, was augmented to 9%–17% at low gigahertz frequencies. This is believed to be related to the frequency dispersion observed in the ceramics because of charged defects.     

Hybrid Organic/Inorganic Nanostructures for Highly Sensitive Photoelectrochemical Detection of Dissolved Oxygen in Aqueous Media

Precise, reliable, and remote measurement of dissolved oxygen in aqueous media is of great importance for many industrial, environmental, and biological applications. In particular, photoelectrochemical sensors working in differential mode have recently demonstrated promising properties, in terms of stability, sensitivity, and application potential. Here, a new approach is presented, combining visible light sensitivity, efficient photocurrent generation, and solution‐processed fabrication methods of conjugated polymers, with charge carriers selectivity, energetic alignment favorable to efficient interfacial charge transfer and high surface area achievable by using metal oxide nanostructures. Extensive characterization and optimization of the hybrid organic/inorganic system are carried out, leading to the realization of an oxygen sensor device, based on nanostructured palladium oxide/poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐alt‐5,5‐(4′,7′‐di‐2‐thienyl‐2′,1′,3′‐benzothiadiazole]/[6,6]phenyl‐C61‐butyric acid methyl ester (PdO/APFO‐3:PCBM) as materials of choice. State‐of‐the‐art sensitivity, amounting at ?5.87 μA cm^?2 ppm^?1, low background signal, in the order of ?4.85 μA cm^?2, good electrochemical stability for more than 2 h of continuous functioning and high reproducibility of the signal over the pH 1 to 10 range, are reported, making the hybrid device suitable for several practical uses. The results fully validate the mixed organic/inorganic approach for photoelectrochemical applications, and pave the way for its further exploitation in fields like waste water treatment, environmental monitoring, and water splitting.     

Long Range Self‐Assembly of Polythiophene Breath Figures: Optical and Morphological Characterization

Large‐area, device relevant sized microporous thin films are formed with commercially available polythiophenes by the breath figure technique, a water‐assisted micropatterning method, with such semitransparent thin films exhibiting periodicity and uniformity dictated by the length of the polymer side chain. Compared to drop‐casted thin films, the microporous thin films exhibit increased crystallinity due to stronger packing of the polymer inside the honeycomb frame.     

Effects of multicomponent diffusion on predicted ignition characteristics of an n-heptane diffusion flame

Flamelet models for turbulent combustion typically employ the assumption of unity Lewis number, i.e., equal thermal and species diffusivities. These models have been employed to predict ignition delay times and ignition location in combusting sprays. However, there is the interesting question: what would be the effects of including multicomponent species diffusion on the ignition predictions? In this work, a one-dimensional n-heptane-air diffusion flame is chosen to study the effects of multicomponent diffusion on predicted ignition characteristics. The ambient conditions selected include typical in-cylinder conditions of a medium-duty diesel engine: pressure 10-40 bar and air temperature 850-1000 K. The ignition and oxidation of n-heptane are predicted using a reaction mechanism consisting of 34 species and 56 steps. The mixture fraction is computed separately as a passive species, the diffusion coefficient, of which is equal to the local thermal diffusion coefficient. From these computations, the transient structure of the flamelet, including ignition, is obtained. The results are compared with those obtained with the unity Lewis number assumption. The implications of the unity Lewis number assumption on the predicted ignition characteristics are discussed.     

The effect of different formulations on physical properties of cakes baked with microwave and near infrared-microwave combinations.

The aim of this study was to determine the effect of different formulations on color and textural characteristics of different cakes during baking in microwave and near infrared-microwave combination ovens. For comparison, cakes were also baked in conventional ovens. Color and hardness for both types of baking schemes were found to be dependent on formulation. Cakes containing Simplesse, a fat replacer consisting mostly of whey protein, baked in microwave and near infrared-microwave combination ovens were found to be the firmest cakes.     

Identification in the presence of classes of unmodeled dynamics andnoise

Identification involves obtaining a model from an a priori chosen model class(es) using finite corrupted data. The corruption may be due to several reasons ranging from noise to unmodeled dynamics, since the real system may not belong to the model class. Two popular approaches-probabilistic and set-membership identification-deal with this problem by imposing temporal constraints on the noise sample paths. We differentiate between the two sources of error by imposing different types of constraints on the corruption. If the source of corruption is noise, we model it by imposing temporal constraints on the possible realizations of noise. On the other hand, if it results from unmodeled dynamics informational constraints are imposed. Contrary to probabilistic identification where the parameters of the identified model converge to the true parameters in the presence of noise, current results in set-membership identification do not have this convergence property. Our approach leads to bridging this gap between probabilistic and set-membership identification when the source of corruption is noise. For the case when both unmodeled dynamics and noise are present, we derive consistency results for the case when the unmodeled dynamics can be described either by a linear time-invariant system or by a static nonlinearity