Oxidation Behavior and Flexural Strength of Aluminum Nitride Exposed to Air at Elevated Temperatures

The oxidation behavior of a sintered aluminum nitride containing 3 wt% Y₂O₃ as a sintering aid was investigated. Samples were exposed to air at elevated temperatures for times up to 100 h. The weights of the samples were continuously monitored during exposure at various temperatures and humidity levels. The effects of oxidation on room-temperature flexural strength were also determined, and correlated to the observed weight changes of the samples. At temperatures 1200°C, linear weight gains were observed. However, at temperatures above 1200°C, the weight gains became parabolic with respect to exposure time. The oxidation rates were significantly increased by water vapor in the air. The oxidation products were found by X-ray analysis to be a mixture of Al₂O₃ and 5A1₂O₃·3Y₂O₃. The oxide layer formed on the surface was severely cracked because of the thermal expansion mismatch between the oxide layer and the substrate. The cracks initiated in the oxide layer and propagated into the substrate, resulting in severe reduction in the room-temperature flexural strength of the material. When exposed to ambient air for more than 50 h at temperatures greater than 1100°C, the strengths of the samples decreased to less than half that of the as-received material.     

Introductory remarks

Surface active agents are used in the textile industry during the processing of fibers into yarns and fabrics, the finishing of leather products and during the removal of soil from textile products by laundering or dry cleaning. In these introductory remarks to the symposium, attention is directed to the phenomena occurring at solid-liquid interfaces during these processes. The properties of the surface active agents and the solvents used, the surface free energy and structure of the polymeric textile products and other, often poorly defined, surface chemical and physical characteristics of the products influence the interactions of these agents. The interactions of surface active agents, often derived from fats and oils, dissolved or dispersed in liquids, with textile materials, including natural products such as cotton, wool and leather, as well as man-made fibers, are considered in this symposium. One of eight papers being published from the Symposium “Surface Active Agents in the Textile Industry,” presented at the AOCS meeting in New Orleans, April 1970. So. Utiliz. Res. Dev. Div., ARS, USDA.     

Water‐assisted injection molding of thermoplastic materials: Effects of processing parameters

The objective of this study was to experimentally investigate the effects of various processing parameters on the water‐assisted injection molding of thermoplastic materials. Experiments were carried out on a lab‐developed water‐assisted injection molding system, which included a water pump, a water injection pin, a water tank equipped with a temperature regulator, and a control circuit. Two types of water injection pins designs were proposed to mold the parts. After molding, the lengths of water penetration in molded parts were measured. The effects of different processing parameters on the lengths of water penetration were determined. It was found that the shrinkage rate and the viscosity of the polymeric materials, and the void shapes of the hollowed cores mainly determined the water‐penetration lengths in molded products. In addition, a comparison has been made between the parts molded by water assisted injection molding and gas‐assisted injection molding. It was found that water‐assisted injection molded parts exhibit less uniform void sizes along the water channel. The cycle time for water‐assisted injection molded parts was shorter than that of conventional injection molded parts and gas‐assisted injection molded parts.     

Model-based intelligent user interface adaptation: challenges and future directions

Software and Systems Modeling - Adapting the user interface of a software system to the requirements of the context of use continues to be a major challenge, particularly when users become more...     

The dynamic contact area of elastomers at different velocities

The friction in tribo-systems that contain viscoelastic materials, such as elastomers, is relevant for a large number of applications. Examples include tyres, hoses, transmission and conveyor belts. To quantify the friction in these applications, one must first understand the contact behaviour of such viscoelastic materials, both in static and in dynamic situations. This work discusses an experimental study into the change of the contact area with the sliding velocity and relates the change in contact area with the mechanical properties of the elastomer. The results show that for a tribo-system containing an elastomer, there is a threshold velocity, above which the size of the contact area significantly reduces.     

Fine grinding of thermoplastics by high speed friction grinding assisted by guar gum

High speed friction grinding has been used to grind plant and food substances in water but never been explored for grinding of thermoplastics like polylactic acid (PLA), low and high density polyethylene and polypropylene. Such grinding was investigated in this work and was made possible by using 0.5% guar gum solution instead of just water because increasing the viscosity of water reduced their settling and the speed of passing through the grinder. Tensile, flexural, and impact strengths of the plastics were studied and higher grinding efficiency of PLA could be explained by its low elongation-at-break compared to low density polyethylene, high density polyethylene, and polypropylene. The microplastics (2000–45 μm) were studied for mass and particle size distributions and by scanning electron microscopy, ¹³C CP/MAS NMR, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. In addition, viscosity of guar gum and contact angles was measured. This new technology can produce finely ground microplastics (710–45 μm) for a variety of applications.     

High-throughput drilling of titanium alloys

Experiments of high-throughput drilling of Ti–6Al–4V at 183 m/min cutting speed and 156 mm³/s material removal rate (MRR) using a 4 mm diameter WC–Co spiral point drill were conducted. The tool material and geometry and drilling process parameters, including cutting speed, feed, and fluid supply, were studied to evaluate the effect on drill life, thrust force, torque, energy, and burr formation. The tool wear mechanism, hole surface roughness, and chip light emission and morphology for high-throughput drilling were investigated. Supplying the cutting fluid via through-the-drill holes has proven to be a critical factor for drill life, which can be increased by 10 times compared to that of dry drilling at 183 m/min cutting speed and 0.051 mm/rev feed. Under the same MRR of 156 mm³/s with a doubled feed of 0.102 mm/rev (91 m/min cutting speed), over 200 holes can be drilled. The balance of cutting speed and feed is essential to achieve long drill life and good hole surface roughness. This study demonstrates that, using proper drilling process parameters, spiral point drill geometry, and fine-grained WC–Co tool material, the high-throughput drilling of Ti alloy is technically feasible.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.