Role of carbon nanotube dispersion in fracture toughening of plasma sprayed aluminum oxide-carbon nanotube nanocomposite coating

Aluminum oxide (Al2O3, or alumina) is a conventional ceramic known for applications such as wear resistant coatings, thermal liners, heaters, crucibles, dielectric systems, etc. However applications of Al 2O3 are limited owing to its inherent brittleness. Due to its excellent mechanical properties and bending strength, carbon nanotubes (CNT) is an ideal reinforcement for Al2O3 matrix to improve its fracture toughness. The role of CNT dispersion in the fracture toughening of the plasma sprayed Al2O3-CNT nanocomposite coating is discussed in the current work. Pretreatment of powder feedstock is required for dispersing CNTs in the matrix. Four coatings namely spray dried Al2O 3 (A-SD), Al2O3 blended with 4wt.% CNT (A4C-B), composite spray dried Al2O3-4wt.% CNT (A4C-SD) and composite spray dried A1203-8wt.% CNT (A8C-SD), are synthesized by plasma spraying. Owing to extreme temperatures and velocities involved in the plasma spraying of ceramics, retention of CNTs in the resulting coatings necessitates optimizing plasma processing parameters using an inflight particle diagnostic sensor. A bimodal microstructure was obtained in the matrix that consists of fully melted and resolidified structure and solid state sintered structure. CNTs are retained both in the fully melted region and solid-state sintered regions of processed coatings. Fracture toughness of A-SD, A4C-B, A4C-SD and A8C-SD coatings was 3.22, 3.86, 4.60 and 5.04 MPa m1/2 respectively. This affirms the improvement of fracture toughness from 20% (in A4C-B coating) to 43% (in A4C-SD coating) when compared to the A-SD coating because of the CNT dispersion. Fracture toughness improvement from 43% (in A4C-SD) to 57% (in A8C-SD) coating is evinced because of the CNT content. Reinforcement by CNTs is described by its bridging, anchoring, hook formation, impact alignment, fusion with splat, and mesh formation. The Al2O3/CNT interface is critical in assisting the stress transfer and utilizing excellent mechanical properties of CNTs. Mathematical and computational modeling using ab-initio principle is applied to understand the wetting behavior at the Al2O 3/CNT interface. Contrasting storage modulus was obtained by nanoindentation (∼210, 250, 250-350 and 325-420 GPa in A-SD, A4C-B, A4C-SD, and A8C-SD coatings respectively) depicting the toughening associated with CNT content and dispersion.

Interval and Point Estimators for the Location Parameter of the Three-Parameter Lognormal Distribution

The three-parameter lognormal distribution is the extension of the two-parameter lognormal distribution to meet the need of the biological, sociological, and other fields. Numerous research papers have been published for the parameter estimation problems for the lognormal distributions. The inclusion of the location parameter brings in some technical difficulties for the parameter estimation problems, especially for the interval estimation. This paper proposes a method for constructing exact confidence intervals and exact upper confidence limits for the location parameter of the three-parameter lognormal distribution. The point estimation problem is discussed as well. The performance of the point estimator is compared with the maximum likelihood estimator, which is widely used in practice. Simulation result shows that the proposed method is less biased in estimating the location parameter. The large sample size case is discussed in the paper.

On the Existence and Uniqueness of the Maximum Likelihood Estimators of Normal and Lognormal Population Parameters with Grouped Data

Lognormal distribution has abundant applications in various fields. In literature, most inferences on the two parameters of the lognormal distribution are based on Type-I censored sample data. However, exact measurements are not always attainable especially when the observation is below or above the detection limits, and only the numbers of measurements falling into predetermined intervals can be recorded instead. This is the so-called grouped data. In this paper, we will show the existence and uniqueness of the maximum likelihood estimators of the two parameters of the underlying lognormal distribution with Type-I censored data and grouped data. The proof was first established under the case of normal distribution and extended to the lognormal distribution through invariance property. The results are applied to estimate the median and mean of the lognormal population.

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.

Role of carbon nanotube dispersion in fracture toughening of plasma sprayed aluminum oxide - carbon nanotube nanocomposite coating

Aluminum oxide (A1203, or alumina) is a conventional ceramic known for applications such as wear resistant coatings, thermal liners, heaters, crucibles, dielectric systems, etc. However applications of A1203 are limited owing to its inherent brittleness. Due to its excellent mechanical properties and bending strength, carbon nanotubes (CNT) is an ideal reinforcement for A1203 matrix to improve its fracture toughness. The role of CNT dispersion in the fracture toughening of the plasma sprayed A1203-CNT nanocomposite coating is discussed in the current work. Pretreatment of powder feedstock is required for dispersing CNTs in the matrix. Four coatings namely spray dried A1203 (A-SD), A1203 blended with 4wt.% CNT (A4C-B), composite spray dried A1203-4wt.% CNT (A4C-SD) and composite spray dried A1203-8wt.% CNT (A8CSD), are synthesized by plasma spraying. Owing to extreme temperatures and velocities involved in the plasma spraying of ceramics, retention of CNTs in the resulting coatings necessitates optimizing plasma processing parameters using an inflight particle diagnostic sensor. A bimodal microstructure was obtained in the matrix that consists of fully melted and resolidified structure and solid state sintered structure. CNTs are retained both in the fully melted region and solid-state sintered regions of processed coatings. Fracture toughness of A-SD, A4C-B, A4C-SD and A8C-SD coatings was 3.22, 3.86, 4.60 and 5.04 MPa m1/2 respectively. This affirms the improvement of fracture toughness from 20 % (in A4C-B coating) to 43% (in A4C-SD coating) when compared to the A-SD coating because of the CNT dispersion. Fracture toughness improvement from 43 % (in A4C-SD) to 57% (in A8C-SD) coating is evinced because of the CNT content. Reinforcement by CNTs is described by its bridging, anchoring, hook formation, impact alignment, fusion with splat, and mesh formation. The A1203/CNT interface is critical in assisting the stress transfer and utilizing excellent mechanical properties of CNTs. Mathematical and computational modeling using ab-initio principle is applied to understand the wetting behavior at the A1203/CNTinterface. Contrasting storage modulus was obtained by nanoindentation (~ 210, 250, 250-350 and 325-420 GPa in A-SD, A4C-B, A4C-SD, and A8C-SD coatings respectively) depicting the toughening associated with CNT content and dispersion.

The effect of weathering processes on the vertical turbulent dispersion characteristics of crude oil spilled on the sea

Since the Exxon Valdez accident in 1987, renewed interest has come forth to better understand and predict the fate and transport of crude oil lost to marine environments. The short-term fate of an Arabian Crude oil was simulated in laboratory experiments using artificial seawater. The time-dependent changes in the rheological and chemical properties of the oil under the influence of natural weathering processes were characterized, including dispersion behavior of the oil under simulated ocean turbulence. Methodology included monitoring the changes in the chemical composition of the oil by Gas Chromatography/Mass Spectrometry (GCMS), toxicity evaluations for the oil dispersions by Microtox analysis, and quantification of dispersed soluble aromatics by fluorescence spectrometry. Results for this oil show a sharp initial increase in viscosity, due to evaporative losses of lower molecular weight hydrocarbons, with the formation of stable water-in-oil emulsions occurring within one week. Toxicity evaluations indicate a decreased EC-50 value (higher toxicity) occurring after the oil has weathered eight hours, with maximum toxicity being observed after weathering seven days. Particle charge distributions, determined by electrophoretic techniques using a Coulter DELSA 440, reveal that an unstable oil dispersion exists within the size range of 1.5 to 2.5 um, with recombination processes being observed between sequential laser runs of a single sample.