Texture and sheet resistance of Al alloy thin films on Ti and TiN thin films

Ti films prepared by ionized physical vapor deposition (I-PVD) and TiN films prepared by metalorganic chemical vapor deposition (MOCVD) were examined as the underlayers of the Al interconnect films. The crystallographic texture of the Al films and the sheet resistance of the thin-film stacks were investigated at various thicknesses of the Ti or TiN thin film. The sheet resistance of the thin-film stacks was also measured after annealing at 400 °C in an N₂ ambient. For the I-PVD Ti underlayer, the excellent texture of the Al (1 1 1) was obtained even on a 5-nm thick Ti film. However, the sheet resistance of the multilayer structure increased after the annealing due to the reaction between Al and Ti. MOCVD TiN layers between the Ti film and the Al film could suppress the Al–Ti reaction without severe degradation of the Al (1 1 1) texture. Excellent texture of the Al film was obtained with thin MOCVD TiN films below 5 nm.     

Interfacial reactions and intermetallic compound growth between indium and copper

The growth kinetics of intermetallic compound layers formed between pure indium solder and bare Cu substrate by solid-state isothermal aging were examined at temperatures between 343 and 393 K for 0–4×10⁶ s. A quantitative analysis of the intermetallic compound layer thickness as a function of time and temperature was performed. Experimental results showed that the Cu₁₁In₉ intermetallic compound was observed for bare copper substrate. Additionally, the thickness of the Cu₁₁In₉ intermetallic compound was increased with the aging temperature and time. The layer growth of the intermetallic compound in the couple of the In/Cu system followed a parabolic law over the given temperature range. As a whole, because the values of time exponent (n) were approximately 0.5, the layer growth of the intermetallic compound was mainly controlled by a diffusion mechanism over the temperature range studied. The apparent activation energy of Cu₁₁In₉ intermetallic compound in the couple of the In/Cu was 34.16 kJ mol^–1.     

Baseline Models for Bridge Performance Monitoring

A baseline model is essential for long-term structural performance monitoring and evaluation. This study represents the first effort in applying a neural network-based system identification technique to establish and update a baseline finite element model of an instrumented highway bridge based on the measurement of its traffic-induced vibrations. The neural network approach is particularly effective in dealing with measurement of a large-scale structure by a limited number of sensors. In this study, sensor systems were installed on two highway bridges and extensive vibration data were collected, based on which modal parameters including natural frequencies and mode shapes of the bridges were extracted using the frequency domain decomposition method as well as the conventional peak picking method. Then an innovative neural network is designed with the input being the modal parameters and the output being the structural parameters of a three-dimensional finite element model of the bridge such as the mass and stiffness elements. After extensively training and testing through finite element analysis, the neural network became capable to identify, with a high level of accuracy, the structural parameter values based on the measured modal parameters, and thus the finite element model of the bridge was successfully updated to a baseline. The neural network developed in this study can be used for future baseline updates as the bridge being monitored periodically over its lifetime.     

Wave Propagation and Mode Localization in Simply Supported Multispan Beams with Couplers on Supports

The influences of couplers on wave propagation and mode localization in simply supported multispan beams with couplers consisting of lumped rotational stiffness and mass on supports are studied. A transfer matrix equation governing the vibrational wave propagation in the simply supported multispan beams with couplers is newly derived and simplified. The eigenvalue of the simplified transfer matrix shows that the larger stiffness or the larger mass of the coupler makes the internal coupling between spans weaker and so it makes the system more sensitive to mode localization. As the wave frequency or the eigenvalues of the system increases, the mass effect is increased while the stiffness effect is decreased. In a case considering the large stiffness and mass at the same time, there is a region with relatively wider passbands and narrower stop bands having small attenuation rates and the normal modes in it become delocalized ones. As an example structure, a simply supported two span beam with a coupler at the midspan is considered.     

Geometrically Nonlinear Buffeting Response of a Cable-Stayed Bridge

A geometrically nonlinear buffeting analysis of a cable-stayed bridge in the time domain is described. The bridge structure is modeled with three-dimensional thin-walled beam elements and three-dimensional elastic catenary cable elements. Spatially correlated wind velocity fluctuations are modeled and simulated using an algorithm for generating sample functions of a stationary, multivariate stochastic process according to its prescribed cross-spectral density matrix. Aerodynamic damping and aerodynamic stiffness are formulated based on experimentally determined flutter derivatives. The focus of this paper is on the effect of fluctuating components of the spatially correlated wind velocity on the geometrically nonlinear buffeting response for an 870 m cable-stayed bridge.     

Treatment of High Nitrate-Containing Wastewaters by Sequential Heterotrophic and Autotrophic Denitrification

The treatment performance of sequential heterotrophic and autotrophic denitrification process was evaluated using synthetic wastewaters containing high nitrate concentrations. The effluents from two sequentially connected reactors, for heterotrophic denitrification and sulfur-based autotrophic denitrification, were analyzed for more than 200 days. Experimental results indicated that higher than 95% of the nitrate removal could be achieved with volumetric nitrate loading rates of 2.16, 3.24, and 4.32 kg/m3?d. The maximum denitrification rates, with 1,000 mgN/l influent nitrate concentrations, for the heterotrophic and sulfur-packed autotrophic reactors, were found to be 2.47 and 3.61 kg/m3?d, respectively. A sequential heterotrophic and autotrophic denitrification process is considered a good alternative for the sole autotrophic denitrification process, providing excellent nitrate removal, especially for nitrate-rich wastewaters with very low organic contents.     

Improved Anaerobic Process Efficiency Using Mesophilic and Thermophilic Elutriated Phased Treatment

An innovative anaerobic digestion elutriated phased treatment (ADEPT) has been evaluated at mesophilic (M-ADEPT) (35°C) and thermophilic (T-ADEPT) (55°C) temperatures in which the organic loading rate (OLR) was increased until reactor failure (pH<5.5). Single-stage continuously stirred tank reactors (CSTRs) at both temperatures were also operated as controls (M-CSTR for 35°C and T-CSTR for 55°C). The T-CSTR failed at an OLR of 7.4 g volatile solid (VS)/L?day and the M-CSTR at an OLR of 10 g VS/L?day while the M-ADEPT continued until an OLR of 18 g VS/L?day and the T-ADEPT reached an OLR of 24 g VS/L?day before system failure. The T-CSTR produced the poorest effluent quality as manifested by high propionate concentrations (1,500–2,500 mg/L) while both M-ADEPT and T-ADEPT produced much better quality of effluent with propionate concentrations below 100 mg/L. Thus it appears that the T-ADEPT design may solve effluent quality problems associated with normally high propionate concentrations produced during thermophilic anaerobic digestion. Superior effluent quality, reduced reactor volume requirements, more stable methanogenesis due to the extended solids retention time, and uncoupling of the methanogen wasting from the refractory sludge wasting process resulted in stable and efficient processing at both temperatures for the innovative ADEPT design. Because the higher amounts of volatile fatty acids produced in the acid elutriation phase of the ADEPT system can be a favorable carbon source for biological nutrient removal in wastewater treatment plants, this positive aspect should be considered in future applications of the ADEPT system.     

Links Between Sex-Typed Time Use in Middle Childhood and Gender Development in Early Adolescence.

The authors studied sex-typing in the kinds (e.g., sports, handicrafts) and social contexts (same- vs. other-sex companions) of children's free time activities, and the links between sex-typed activities and gender development over 2 years. Participants were 200 White, working- and middle-class children (103 girls, 97 boys; mean age = 10.86 years). In annual home interviews, children rated their self-esteem, gender role attitudes and sex-typed personality qualities, academic interests, and school grades. During 7 nightly phone interviews each year, children reported on their activities. Boys were more sex-typed than girls in their peer activities, and children were least sex-typed in their activities with siblings. Sex-typed activities in middle childhood predicted individual differences in gender development in early adolescence (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Estimation of break location and size for loss of coolant accidents using neural networks

In this work, a probabilistic neural network (PNN) that has been applied well to the classification problems is used in order to identify the break locations of loss of coolant accidents (LOCA) such as hot-leg, cold-leg and steam generator tubes. Also, a fuzzy neural network (FNN) is designed to estimate the break size. The inputs to PNN and FNN are time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. An automatic structure constructor for the fuzzy neural network automatically selects the input variables from the time-integrated values of many measured signals, and optimizes the number of rules and its related parameters. It is verified that the proposed algorithm identifies very well the break locations of LOCAs and also, estimate their break size accurately.     

Automated Quality Assessment of Stone Aggregates Based on Laser Imaging and a Neural Network

An automated quality assessment technique is proposed for rapidly detecting excessive size variations during the production of stone aggregates. The system uses a laser profiler to scan collections of aggregate particles and obtain three-dimensional data points on the particle surfaces. For computational efficiency, the resulting data are converted into digital images. Wavelet transforms are then applied to the images to extract features indicative of the material gradation. These wavelet-based features are used as inputs to an artificial neural network, which is trained to classify the aggregate sample. Taken together, these components form a neural network-based classification system that can determine whether or not an aggregate product is in compliance with a given specification. Verification tests show that this approach could potentially help to determine, in an accurate and fast (real-time) manner, when adjustments or repairs to the production equipment are needed.