Experimental Study of Alumina Particle Removal From a Plane surface

Micron and submicron alumina particles are often used for the mechanical polishing of the GaAs wafers processed in the microelectronic industry. A better understanding of the adhesion mechanisms is the key factor for the particle removal and for the optimisation of the industrial chemical cleaning. However, the nature and the strength of the complex interactions occurring between asymmetrical alumina particles and the surface remain unclear. Thus, an experimental study of the detachment of asymmetrical alumina particles in adhesive contact with a glass plate was done using a specially designed shear stress flow chamber. A series of experiments was performed to measure the shear stress necessary to remove individual alumina particles (of 3 and 0.3 µm nominal size) under various chemical solutions (diluted ammonia, surfactant and glycerol). Then the effects of the particle size, the resting time, the pH and the nature of the chemical solutions used for the removal of the alumina particles was characterised in terms of percentage of alumina particles detached. Results have shown that the longer the resting time, the more adherent the particles are. Moreover, it was found that the ammonia solution gives the best particle removal rate (80%) because of the strong repulsive electrostatic interactions between the alumina particles and the glass surface, both being charged negatively in a basic solution.     

The prospects of non-volatile phase-change RAM

Phase-change read-and-write memory (PRAM) is a promising memory that can solve the problems of conventional memory—scalability, read/write speed, and reliability. We will review the opportunities and technical challenges of PRAM. The most important challenge of PRAM is the reduction of the writing current. Various approaches to reduce the writing current will be reviewed and the prospects of PRAM are discussed.     

Feature-based classifiers for design optimization

We present a design optimization method for systems with high-dimensional parameter spaces using inductive decision trees. The essential idea is to map designs into a relatively low-dimensional feature space, and to derive a classifier to search for high-performing design alternatives within this space. Unlike learning classifier systems that were pioneered by Holland and Goldberg, classifiers defined by inductive decision trees were not originally developed for design optimization. In this paper, we explore modifications to such classifiers to make them more effective in the optimization problem. We expand the notions of feature space, generalize the tree construction heuristic beyond the original information-theoretic definitions, increase the reliance on domain expertise, and facilitate the transfer of design knowledge between related systems. There is a relatively small but rapidly growing body of work in the use of inductive trees for engineering design; the method presented herein is complementary to this research effort.     

Organizational determinants of IT adoption in the pharmaceutical distribution sector

The aim of this paper is to propose new organizational factors that might explain the differences in the extent and the speed of IT adoption. With this in mind, we carried out an analysis of 16 cases in the pharmaceutical distribution sector in Spain. The results indicate that there are certain intangible assets that favour the introduction and development of IT. Among these are a frank and fluid communication between departments and members of the organization, low levels of conflict, the explicit support of top management towards IT adoption and learning and creative skills of IT-staff. In addition to these factors, we found others that we propose as catalysts of IT adoption. Among these we might mention the special relationship between the member-clients and the company in the case of cooperative firms.     

Phytochemical and biological investigation of <Emphasis Type="Italic">Stevia rebaudiana</Emphasis> Bertoni; 1-labdane-type diterpene

Five labdane diterpenoids, austroinulin, iso-austroinulin, sterebin E, sterebin E acetate, and sterebin A acetate, along with hydrocarbons, aliphatic alcohols, β-amyrin, β-sitosterol and stigmasterol were isolated from the chloroform soluble fraction of the methanol extract of Stevia rebaudiana leaves. Chlorogenic and caffeic acids were isolated from the EtOAc fraction. All the isolated compounds were identified using spectral tools. The chloroform and methanol extracts proved significant anti-inflammatory effect and caused marked inhibition of carrageenan-induced paw oedema in rats.     

Uncertainty Matters: Computer Models at the Science–Policy Interface

The use of computer models offers a general and flexible framework that can help to deal with some of the complexities and difficulties associated with the development of water management plans as prescribed by the Water Framework Directive. However, despite the advantages modelling presents, the integration of information derived from models into policy is far away from being trivial or the norm. Part of the difficulties of this integration is rooted in the lack of confidence policy makers have on the incorporation of modelling information into policy formulation. In this paper we examine the reasons for this apparent lack of confidence and explore how some tools, presently in use, address this problem. We conclude that public confidence in models is highly dependent on the way uncertainties are addressed and suggest possible directions of action to improve the current situation. Four real case studies illustrate how computer models have been used in The Netherlands for carrying out management plans at regional and national scale. We suggest that the solution to integrate modelling information into policy formulation lies on both the modelling and the policy-making communities.