Wear analysis of Cu–Al coating on Ti–6Al–4V substrate under fretting condition

Fretting behavior of Cu–Al coating on Ti–6Al–4V substrate was investigated with and without fatigue load. Soft and rough Cu–Al coating resulted in abrasive wear and a large amount of debris remained at the contact surface, which caused an increase in tangential force during the fretting test under gross slip condition. Fretting in the partial slip condition also showed the wear of coating. To characterize wear, dissipated energies during fretting were calculated from fretting loops and wear volumes were obtained from worn surface profiles. Energy approach of wear analysis showed a linear relationship between wear volume and accumulated dissipated energy. This relationship was independent of fatigue loading condition and extended from partial slip to gross slip regimes. As an alternate but simple approach for wear analysis, accumulated relative displacement range was correlated with the wear volume. This also resulted in a linear relationship as in the case of accumulated dissipated energy suggesting that the accumulated relative displacement range can be used as an alternative parameter for dissipated energy to characterize the wear. When the maximum wear depth was equal to the thickness of Cu–Al coating, harder Ti–6Al–4V substrate inhibited further increase in wear depth. Only when a considerable energy was supplied through a large value of the applied displacement, wear in the substrate material could occur beyond the thickness of coating.     

Ultrafine particles from diesel vehicle emissions at different driving cycles induce differential vascular pro-inflammatory responses: Implication of chemical components and NF-κB signaling

Background

Nanometer silicon dioxide (nano-SiO₂) has a wide variety of applications in material sciences, engineering and medicine; however, the potential cell biological and proteomic effects of nano-SiO₂ exposure and the toxic mechanisms remain far from clear.

Results

Here, we evaluated the effects of amorphous nano-SiO₂ (15-nm, 30-nm SiO₂). on cellular viability, cell cycle, apoptosis and protein expression in HaCaT cells by using biochemical and morphological analysis, two-dimensional differential gel electrophoresis (2D-DIGE) as well as mass spectrometry (MS). We found that the cellular viability of HaCaT cells was significantly decreased in a dose-dependent manner after the treatment of nano-SiO₂ and micro-sized SiO₂ particles. The IC₅₀ value (50% concentration of inhibition) was associated with the size of SiO₂ particles. Exposure to nano-SiO₂ and micro-sized SiO₂ particles also induced apoptosis in HaCaT cells in a dose-dependent manner. Furthermore, the smaller SiO₂ particle size was, the higher apoptotic rate the cells underwent. The proteomic analysis revealed that 16 differentially expressed proteins were induced by SiO₂ exposure, and that the expression levels of the differentially expressed proteins were associated with the particle size. The 16 proteins were identified by MALDI-TOF-TOF-MS analysis and could be classified into 5 categories according to their functions. They include oxidative stress-associated proteins; cytoskeleton-associated proteins; molecular chaperones; energy metabolism-associated proteins; apoptosis and tumor-associated proteins.

Conclusions

These results showed that nano-SiO₂ exposure exerted toxic effects and altered protein expression in HaCaT cells. The data indicated the alterations of the proteins, such as the proteins associated with oxidative stress and apoptosis, could be involved in the toxic mechanisms of nano-SiO₂ exposure.     

Experimental and Morphological Investigations Into Electrical Discharge Surface Grinding (EDSG) of 6061Al/Al2O3p 10% Composite by Composite Tool Electrode

In this study, a special experimental setup of EDSG using EDM and surface grinding machine has been developed in the laboratory to investigate the effect of seven input parameters namely tool polarity, peak current, pulse on-time, pulse off-time, rotational speed, abrasive particle size, and abrasive particle concentration on material removal rate (MRR) as performance measure of the process. The novelty of the present research work is that successful efforts have been made to machine the 6061Al/Al₂O_3p 10% metal matrix composites (MMC) by composite tool itself. The copper-based composite tool electrodes were fabricated by powder metallurgy route with different sizes of abrasives of silicon carbide, while 6061Al/Al₂O_3p 10% MMC were fabricated through stir-casting process. The research outcome will identify the important parameters and their effect on MRR of 6061Al/Al₂O_3p 10% composite in EDSG. The experimental results reveal that tool polarity, peak current, and rotational speed are the most influential parameters that affect MRR in EDSG process. The micro-structural and morphological analysis of machined surfaces has also been carried out to analyze the surface topography. It has been concluded that the abrasive particles substantially improves the MRR after removing the resolidified layer from the machined surface.     

Mechanism and preventive measures for die soldering during Al casting in a ferrous mold

This work provides a comprehensive understanding of the reactions at the ferrous die/molten metal interface in a metal mold casting operation. The literature has shown that several important factors influence reactions at the ferrous die/molten aluminum interface, including temperature of the melt, temperature of the die, alloy chemistry of the melt and die, die surface engineering, topographical features, and coatings. This article discusses the effect of the more critical factors on soldering, based on the authors’ investigations. Inaddition, based on a mechanistic understanding of the interface reactions between ferrous die and molten aluminum, recommendations are given for specific processing issues to alleviate soldering during die casting of aluminum alloys.     

Machining Performance and Surface Integrity of AISI D2 Die Steel Machined Using Electrical Discharge Surface Grinding Process

The aim of this study is to establish optimum machining conditions for EDSG of AISI D2 die steel through an experimental investigation using Taguchi Methodology. To achieve combined grinding and electrical discharge machining, metal matrix composite electrodes (Cu-SiC_p) were processed through powder metallurgy route. A rotary spindle attachment was developed to perform the EDSG experimental runs on EDM machine. Relationships were developed between various input parameters such as peak current, speed, pulse-on time, pulse-off time, abrasive particle size, and abrasive particle concentration, and output characteristics such as material removal rate and surface roughness. The optimized parameters were further validated by conducting confirmation experiments.     

Gas-Sensing Properties of Zinc Ferrite Nanoparticles Synthesized by the Molten-Salt Route

Zinc ferrite (ZnFe₂O₄) nanoparticles have been synthesized at 700°C using sodium chloride as a growth inhibitor. Single-phase formation of spinel zinc ferrite having crystallite size in the range of 15–20 nm was observed by XRD and confirmed by TEM. In the present work, the gas-sensing properties of these zinc ferrite nanoparticles toward ethanol, LPG, H₂, NO _x . SO _x , and H₂S have been studied. It was found that they exhibit excellent selective sensitivity toward 200 ppm of H₂S at the operating temperature of 250°C, and thus this nanosized ferrite is expected to be useful in an industrial application as a potential H₂S gas sensor.     

Plug-in Selection of the Number of Frequencies in Regression Estimates of the Memory Parameter of a Long-memory Time Series

We consider the problem of selecting the number of frequencies, m , in a log-periodogram regression estimator of the memory parameter d of a Gaussian long-memory time series. It is known that under certain conditions the optimal m , minimizing the mean squared error of the corresponding estimator of d , is given by m ^(opt)= Cn ^4/5, where n is the sample size and C is a constant. In practice, C would be unknown since it depends on the properties of the spectral density near zero frequency. In this paper, we propose an estimator of C based again on a log-periodogram regression and derive its consistency. We also derive an asymptotically valid confidence interval for d when the number of frequencies used in the regression is deterministic and proportional to n ^4/5. In this case, squared bias cannot be neglected since it is of the same order as the variance. In a Monte Carlo study, we examine the performance of the plug-in estimator of d , in which m is obtained by using the estimator of C in the formula for m ^(opt) above. We also study the performance of a bias-corrected version of the plug-in estimator of d . Comparisons with the choice m = n ^1/2 frequencies, as originally suggested by Geweke and Porter-Hudak (The estimation and application of long memory time series models. Journal of Time Ser. Anal. 4 (1983), 221–37), are provided.     

Effective parameter estimation within a multi-dimensional population balance model framework

This study considers optimization problems with multi-dimensional population balance models embedded. The objective function is formulated as a least-squares problem, minimizing the difference between target data and simulated model output and the goal is to find model parameter values that best fit the data. Results show that derivative-free methods, such as the Nelder–Mead simplex method, fail to converge to an optimal solution. A similar result was obtained with gradient-based methods such as BFGS, quasi-Newton, Newton, Gauss–Newton, Levenberg–Marquardt and SQP, and with a stochastic genetic algorithm. It was hypothesized that three main issues could contribute to these convergence failures: (1) gradients were calculated based on finite differences, and as a result of improper step size determination, the numerical error could be prohibitive resulting in inaccurate derivative information, (2) the parameters may not be identifiable and (3) numerical instability could occur during the course of optimization. To circumvent these issues, this work addresses the calculation of derivative information based on automatic differentiation and sensitivity analysis to ensure increased accuracy. Issues such as parameter identifiability are also dealt with by analyzing an accurate Fisher information matrix. Given the computational burden in calculating accurate Jacobians and Hessians, compounded by the potential nonsmoothness introduced into the objective function as a result of granule nucleation, other optimization strategies may be warranted and this work addresses those accordingly. Overall, by systematically assessing the problem formulation and mechanisms, the results show that substantial improvements in convergence can be achieved by utilizing appropriate optimization techniques, thus leading to more successful and optimal parameter estimation.     

Residence time distribution and oxygen transfer in a novel constructed soil filter

BACKGROUND: The constructed soil filter (CSF), also known as soil biotechnology is a system for water renovation, which makes use of formulated media, culture of soil micro‐ and macro‐organisms, additives and plantation to purify water and wastewater. The process gives benefits in terms of applicability across very small to large scale, natural aeration, absence of moving parts, no biological sludge generation, odor free green aesthetic ambience. RESULTS: Residence time distribution (RTD) studies were carried out using laboratory scale CSF. Pulse potassium bromide tracer tests were carried out to determine RTD, and the Peclet number found to be 9–13 for a 2 m bed, and 2–3 for a 0.30 m bed with oxygen transfer of 0.08 h^?1. CONCLUSION: The two‐channel dispersion model for flow behavior shows a good fit to the experimental data, indicating a reactor Peclet number 9–13 for a 2 m bed and 2–3 for a 0.3m bed. Oxygen transfer studies carried out using various methods gave an oxygen transfer coefficient of about 0.08 h^?1. Wastewater purification studies indicate overall COD removal rate of around 50 mg L^?1 h^?1, suggesting that highly aerobic conditions are prevalent in the CSF system. Copyright © 2009 Society of Chemical Industry     

Effect of AlN addition on the electrical resistivity of pressureless sintered SiC ceramics with B4C and C

The effect of 0–12 wt% AlN addition on the electrical resistivity of SiC ceramics pressureless sintered with 0.7 wt% B₄C and 2.5 wt% C additives was investigated. The elemental analysis of SiC grains revealed a codoping of Al and N in the SiC lattice with a higher N concentration with 1 wt% AlN addition and a higher Al concentration with 12 wt% AlN addition. The electrical resistivity decreased by four orders of magnitude (1.7 × 10⁵ → 8.3 × 10¹ Ω cm) with 1 wt% AlN addition due to the increased carrier density (1.7 × 10¹⁰ → 2.3 × 10¹⁵ cm⁻³) caused by excess N-derived donors. However, subsequent AlN addition (4 → 12 wt%) led to an increase (2.9 × 10³ → 1.2 × 10⁴ Ω‧cm) in electrical resistivity due to (1) increased Al dopants which act as deep acceptors for trapping N-derived carriers causing a decrease in carrier density (2.3 × 10¹⁵ → 5.9 × 10¹³ cm⁻³), (2) the formation of electrically insulating SiC-AlN solid solution, and (3) the presence of electrically insulating AlN grains at the grain boundaries.