Is the ubiquitous presence of barium carbonate responsible for the poor aqueous processing ability of barium titanate?

The ubiquitous presence of barium carbonate (BaCO₃ – BC) as an impurity in barium titanate (BaTiO₃ – BT) has been pointed out as the main reason for the well-known difficulties found by many investigators when attempting to process BT powders in aqueous media. Different and controversial arguments have been put forward to justify the observed aqueous processing difficulties of BT, but a satisfactory explanation is still to be found. With this aim, a systematic study was here undertaken to shed further light on the solid/liquid interactions occurring at the surface of BC and BT particles and their impact on the dispersion ability of both powders, separately and mixed in certain proportions. Long term colloidal stability and high solid loadings (60 vol.%) were obtained for BC, while colloidal instability and a lower maximum content of solids (50 vol.%) could be achieved for BT. This responds to the question risen in the title.     

The fast reaction asymptote of the coalescence-redispersion model

The coalescence-redispersion (CRD) model is examined in the fast chemistry limit for the single bimolecular reaction A+B M R and the series parallel reactions A+B M R;B+R M S occurring in a plug flow reactor with unmixed feed streams. For the single bimolecular reaction it is shown that in this limit the CRD model is asymptotically equivalent to the 3E fast closure as t M 0. For the series parallel reactions the CRD model predictions tend to be bracketed by the 3E slow and fast closure formulations. Representative results are presented for the variance decay of the individual reactants, and it is seen that even in the fast reaction limit where mixing is controlling, the shape of the feed stream PDFs has negligible influence on the progress of the reaction.     

Sol- gel synthesis of Ga2O3 nanorods and effect of precursor chemistry on their structural and morphological properties

Synthesis of mono-crystalline Ga₂O₃ Nanorods was done by sol-gel transformation of gallium(III) isopropoxide (Ga(OPrⁱ)₃). XRD studies were done to determine the planes and crystal structure of synthesized nanorods that showed the synthesis of β-Ga₂O₃(a). TEM studies of synthesized Ga₂O₃ confirmed the synthesis of monocrystalline β-Ga₂O₃ nanorods. To study the effect of precursor chemistry and to determine role of precursor structures on the crystal structure, phase and morphology of the Ga₂O₃, a new modified precursor complex was synthesized. The reaction of Ga(OPrⁱ)₃ with N-phenylsalicylaldimine, [C₆H₄(OH)CH=N(C₆H₅)] in 1:1?M ratio yielded [{(H₅C₆)N?=?CH-C₆H₄O}Ga(OPrⁱ)₂]. The newly synthesized complex was characterized by elemental analyses, molecular weight measurement, FT-IR and NMR (¹H and ¹³C) spectral studies. Spectral studies of the modified complex suggest the presence of bi-dentate mode of attachment of Schiff's base in the solution state. Sol-gel transformations of [{(H₅C₆)N?=?CH-C₆H₄O}Ga(OPrⁱ)₂] in organic medium, yielded γ-Ga₂O₃(b), as found by XRD studies. TEM image of the sample (a) revealed the formation of nano-rods of oxide with average diameter of ~100?nm whereas the TEM image of sample (b) showed presence of nano-sized particles of oxide with average particle size of 10?nm. Morphological and compositional studies of synthesized samples (a) and (b) were carried out using SEM and EDX. The method provides a possibility of large scale synthesis of dissimilar shaped and pure Ga₂O₃ nanoparticles.     

LAMINAR FLOW AND HEAT TRANSFER IN BLOCKED ANNULI

Laminar flow and heal transfer in annular passages with axially nonuniform inner tubes are obtained numerically. A characteristic feature of these passages is that the flow separates in the streamwise direction. An axisymmetric coordinate system with an algebraic transformation in the radial direction kas been used. Fully elliptic vorticity-slream function and energy equations in the transformed coordinates are solved using an iterative alternate direction implicit (ADI) method. In an annulus with a smooth blockage, the flow separates immediately downstream of the blockage at Reynolds numbers greater than 100. The main features of the flow are established at a Reynolds number of 1000. The pressure drop is drastic near the maximum constriction. The heat flux is also high in the constricted region. A sharp increase in the heat transfer occurs where the fluid reattaches itself to the wall. The increase in the total pressure drop is about an order of magnitude greater than that in the average Nusselt number.     

Modeling of the sheet‐molding process for poly(methyl methacrylate)

The sheet‐molding process for the production of poly(methyl methacrylate) (PMMA) involves an isothermal batch reactor followed by polymerization in a mold (the latter is referred to as a “sheet reactor”). The temperature at the outer walls of the mold varies with time. In addition, due to finite rates of heat transfer in the viscous reaction mass, spatial temperature gradients are present inside the mold. Further, the volume of the reaction mass also decreases with polymerization. These several physicochemical phenomena are incorporated into the model developed for this process. It was found that the monomer conversion attains high values of near‐unity in most of the inner region in the mold. This is because of the high temperatures there, since the heat generated due to the exothermicity of the polymerization cannot be removed fast enough. However, the temperature of the mold walls has to be increased in the later stages of polymerization so that the material near the outer edges can also attain high conversions of about 98%. This would give PMMA sheets having excellent mechanical strength. The effects of important operating (decision) variables were studied and it was observed that the heat‐transfer resistance in the mold influences the spatial distribution of the temperature, which, in turn, influences the various properties (e.g., monomer conversion, number‐average molecular weight, and polydispersity index) of the product significantly. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 81: 1951–1971, 2001     

Learning Noise-Assisted Robust Image Features for Fine-Grained Image Retrieval

Fine-grained image search is one of the most challenging tasks in computer vision that aims to retrieve similar images at the fine-grained level for a given query image. The key objective is to learn discriminative fine-grained features by training deep models such that similar images are clustered, and dissimilar images are separated in the low embedding space. Previous works primarily focused on defining local structure loss functions like triplet loss, pairwise loss, etc. However, training via these approaches takes a long training time, and they have poor accuracy. Additionally, representations learned through it tend to tighten up in the embedded space and lose generalizability to unseen classes. This paper proposes a noise-assisted representation learning method for fine-grained image retrieval to mitigate these issues. In the proposed work, class manifold learning is performed in which positive pairs are created with noise insertion operation instead of tightening class clusters. And other instances are treated as negatives within the same cluster. Then a loss function is defined to penalize when the distance between instances of the same class becomes too small relative to the noise pair in that class in embedded space. The proposed approach is validated on CARS-196 and CUB-200 datasets and achieved better retrieval results (85.38% recall@1 for CARS-196% and 70.13% recall@1 for CUB-200) compared to other existing methods.     

Optimal coverage of an infrastructure network using sensors with distance-decaying sensing quality

Motivated by recent applications of wireless sensor networks in monitoring infrastructure networks, we address the problem of optimal coverage of infrastructure networks using sensors whose sensing performance decays with distance. We show that this problem can be formulated as a continuous p-median problem on networks. The literature has addressed the discrete p-median problem   on networks and in continuum domains, and the continuous p$p$-median problem in continuum domains extensively. However, in-depth analysis of the continuous p$p$-median problem on networks has been lacking. With the sensing performance model that decays with distance, each sensor covers a region equivalent to its Voronoi partition on the network in terms of the shortest path distance metric. Using Voronoi partitions, we define a directional partial derivative of the coverage metric with respect to a sensor’s location. We then propose a gradient descent algorithm to obtain a locally optimal solution with guaranteed convergence. The quality of an optimal solution depends on the choice of the initial configuration of sensors. We obtain an initial configuration using two approaches: by solving the discrete p$p$-median problem on a lumped   network and by random sampling. We consider two methods of random sampling: uniform sampling and D²$D^2$-sampling. The first approach with the initial solution of the discrete p$p$-median problem leads to the best coverage performance for large networks, but at the cost of high running time. We also observe that the gradient descent on the initial solution with the D²$D^2$-sampling method yields a solution that is within at most 7% of the previous solution and with much shorter running time.     

Studies on the hot corrosion of a nickel-base superalloy,Udimet 700

The hot corrosion of a nickel-base superalloy, Udimet 700, has been studied in the temperature range 900–950°C. The effect of the amount of Na ₂SO₄ on the corrosion kinetics was determined. Large weight gains and severe corrosion were associated with two different modes of degradation: (1) formation of large, interconnected sulfides beneath the external scale, and (2) formation of a Na₂MoO₄-MoO₃ melt. The corrosion due to formation of the Na₂MoO₄-MoO₃ melt occurred for all the salt-coating thicknesses, whereas, large sulfides were formed only for the heavier coatings of Na₂SO₄. The formation of Na₂MoO₄-MoO₃ melt required an induction period, and the length of the induction period was observed to be a function of the amount of Na₂SO₄ and of temperature.Work funded under NASA Grant NCC 3-43.     

Design stage optimization of an industrial low-density polyethylene tubular reactor for multiple objectives using NSGA-II and its jumping gene adaptations

Design stage optimization of an industrial low-density polyethylene (LDPE) tubular reactor is carried out for two simultaneous objectives: maximization of monomer conversion and minimization of normalized side products (methyl, vinyl, and vinylidene groups), both at the reactor end, with end-point constraint on number-average molecular weight (M_n,f) in the product. An inequality constraint is also imposed on reactor temperature to avoid run-away condition in the tubular reactor. The binary-coded elitist non-dominated sorting genetic algorithm (NSGA-II) and its jumping gene (JG) adaptations are used to solve the optimization problem. Both the equality and inequality constraints are handled by penalty functions. Only sub-optimal solutions are obtained when the equality end-point constraint on M_n,f is imposed. But, correct global optimal solutions can be assembled from among the Pareto-optimal sets of several problems involving a softer constraint on M_n,f. A systematic approach of constrained-dominance principle for handling constraints is applied for the first time in the binary-coded NSGA-II-aJG and NSGA-II-JG, and its performance is compared to the penalty function approach. A three-objective optimization problem with the compression power (associated with the compression cost) as the third objective along with the aforementioned two objectives, is also studied. The results of three-objective optimization are compared with two different combinations of two-objective problems.     

Organic Semiconductor Growth and Morphology Considerations for Organic Thin‐Film Transistors

Analogous to conventional inorganic semiconductors, the performance of organic semiconductors is directly related to their molecular packing, crystallinity, growth mode, and purity. In order to achieve the best possible performance, it is critical to understand how organic semiconductors nucleate and grow. Clever use of surface and dielectric modification chemistry can allow one to control the growth and morphology, which greatly influence the electrical properties of the organic transistor. In this Review, the nucleation and growth of organic semiconductors on dielectric surfaces is addressed. The first part of the Review concentrates on small‐molecule organic semiconductors. The role of deposition conditions on film formation is described. The modification of the dielectric interface using polymers or self‐assembled mono­layers and their effect on organic‐semiconductor growth and performance is also discussed. The goal of this Review is primarily to discuss the thin‐film formation of organic semiconducting species. The patterning of single crystals is discussed, while their nucleation and growth has been described elsewhere (see the Review by Liu et. al). 1 The second part of the Review focuses on polymeric semiconductors. The dependence of physico‐chemical properties, such as chain length (i.e., molecular weight) of the constituting macromolecule, and the influence of small molecular species on, e.g., melting temperature, as well as routes to induce order in such macromolecules, are described.