Study of the effect of BDMA catalyst in the epoxy novolac curing process by isothermal DSC

Epoxy novolac/anhydride cure kinetics has been studied by differential scanning calorimetry under isothermal conditions. The system used in this study was an epoxy novolac resin (DEN431), with nadic methyl anhydride as hardener and benzyldimethylamine as accelerator. Kinetic parameters including the reaction order, activation energy and kinetic rate constants, were investigated. The cure reaction was described with the catalyst concentration, and a normalized kinetic model developed for it. It is shown that the cure reaction is dependent on the cure temperature and catalyst concentration, and that it proceeds through an autocatalytic kinetic mechanism. The curing kinetic constants and the cure activation energies were obtained using the Arrhenius kinetic model. A suggested kinetic model with a diffusion term was successfully used to describe and predict the cure kinetics of epoxy novolac resin compositions as a function of the catalyst content and temperature. Copyright © 2003 Society of Chemical Industry     

A Preemptive Algorithm for Maximizing Disjoint Paths on Trees

We consider the on-line version of the maximum vertex disjoint path problem when the underlying network is a tree. In this problem, a sequence of requests arrives in an on-line fashion, where every request is a path in the tree. The on-line algorithm may accept a request only if it does not share a vertex with a previously accepted request. The goal is to maximize the number of accepted requests. It is known that no on-line algorithm can have a competitive ratio better than Ω(log n) for this problem, even if the algorithm is randomized and the tree is simply a line. Obviously, it is desirable to beat the logarithmic lower bound. Adler and Azar (Proc. of the 10th ACM-SIAM Symposium on Discrete Algorithm, pp. 1–10, 1999) showed that if preemption is allowed (namely, previously accepted requests may be discarded, but once a request is discarded it can no longer be accepted), then there is a randomized on-line algorithm that achieves constant competitive ratio on the line. In the current work we present a randomized on-line algorithm with preemption that has constant competitive ratio on any tree. Our results carry over to the related problem of maximizing the number of accepted paths subject to a capacity constraint on vertices (in the disjoint path problem this capacity is 1). Moreover, if the available capacity is at least 4, randomization is not needed and our on-line algorithm becomes deterministic.     

Temporary Tasks Assignment Resolved

Among all basic on-line load balancing problems, the only unresolved problem was load balancing of temporary tasks on unrelated machines. This open problem existed for almost a decade, see [12]. We resolve this problem by providing an inapproximability result. In addition, a newer open question is to identify the dependency of the competitive ratio on the durations of jobs in the case where durations are known. We resolve this problem by characterizing this dependency. Finally, we provide a PTAS for the off-line problem with a fixed number of machines and show a 2 -inapproximability result for the general case.     

The marginal cost of CO2 emissions

Haraden's model for estimating the economic cost of global warming is analysed. We change his method of discounting and some of his input parameters in a manner consistent with physical and economic theory as well as empirical data. We then find much higher costs than Haraden found. These costs are compared to the cost of reducing CO₂ emissions and we find that deep cuts of the emissions of CO₂ are preferable. A check of the sensitivity of our results with respect to some crucial parameter values does not alter that conclusion.     

Characterization of Polyphasic Silicon Carbide Using Surface-Enhanced Raman and Nuclear Magnetic Resonance Spectroscopy

The present report explores the use of cross-polarization (CP) and single-pulse magic angle spinning nuclear magnetic resonance (MAS-NMR) as well as normal and surfaceenhanced Raman spectroscopy (SERS), in concert, for characterizing highly crystalline polymorphic silicon carbide ceramics. The combined use of these techniques provides a wealth of information regarding bulk, near-surface, and surface speciation. Both Raman and SERS are promising techniques for fracture surface characterization of these systems. The application of CPMAS-NMR and SERS to the study of ceramics is reported for the first time in this investigation.     

Plant oil bioconversion into increase biological activity through lipases derived from wastes

The aim of this study was to show that abundant and inexpensive plant oils can be biotransformed to increase biological activity (antioxidant, antimicrobial and cytotoxicity) through hydrolysis reaction catalysed by lipases. We tested homemade and commercial lipases through the biotransformation of nine different plant oils in forty different combinations. First, the chemical composition of the samples was investigated. Thereafter, biological tests were conducted to assess the antioxidant and antimicrobial activity of the sampled biotransformation products, as well as analyzed their influence on the viability of healthy and cancer cells. Summarising, sunflower, corn and olive oils modified by orange waste-obtained lipases presented the most promising results, reaching up to 90% of antioxidant activity increase and significant growth inhibition of bacteria colonies belonging to genera Escherichia, Listeria, Staphylococcus, Pseudomonas and Salmonella. In addition, those compounds affected human oral squamous carcinoma cells. The bioconversion of plant oils through lipases improves their biological properties and might be an option for biotechnological application.     

Soft Matter Technology at KIT: Chemical Perspective from Nanoarchitectures to Microstructures

Bioinspiration has emerged as an important design principle in the rapidly growing field of materials science and especially its subarea, soft matter science. For example, biological cells form hierarchically organized tissues that not only are optimized and designed for durability, but also have to adapt to their external environment, undergo self‐repair, and perform many highly complex functions. Being able to create artificial soft materials that mimic those highly complex functions will enable future materials applications. Herein, soft matter technologies that are used to realize bioinspired material structures are described, and potential pathways to integrate these into a comprehensive soft matter research environment are addressed. Solutions become available because soft matter technologies are benefitting from the synergies between organic synthesis, polymer chemistry, and materials science.     

Removal of aqueous Fe2+ using MnO2–clinoptilolite in a batch slurry reactor: Catalyst synthesis,characterization and modeling of catalytic behavior

An Iranian clinoptilolite has been modified with MnO₂ for the catalytic removal of Fe²⁺ cations from water in a batch slurry reactor. The modified zeolite was subjected to FESEM, XRD, WDX, XRF and specific surface area analysis. A correlation for the intrinsic catalytic reaction rate incorporating both Fe²⁺ and dissolved oxygen concentration as a function of reaction temperature has been presented. The effect of the modified zeolite aggregate particle size on the iron removal kinetics has been investigated. It was shown that for particles larger than 150 μm, diffusion through the mesopores of the zeolite aggregate is rate controlling. The effective diffusion coefficient through the particles at RT has been calculated as 2.3 × 10^?6 cm² s^?1. It is shown that liquid phase molecular diffusion within the mesopores is the dominating mass transfer mechanism.     

Tell Me Who I Am: An Interactive Recommendation System

We consider a model of recommendation systems, where each member from a given set of players has a binary preference to each element in a given set of objects: intuitively, each player either likes or dislikes each object. However, the players do not know their preferences. To find his preference of an object, a player may probe it, but each probe incurs unit cost. The goal of the players is to learn their complete preference vector (approximately) while incurring minimal cost. This is possible if many players have similar preference vectors: such a set of players with similar “taste” may split the cost of probing all objects among them, and share the results of their probes by posting them on a public billboard. The problem is that players do not know a priori whose taste is close to theirs. In this paper we present a distributed randomized peer-to-peer algorithm in which each player outputs a vector which is close to the best possible approximation of the player’s real preference vector after a polylogarithmic number of rounds. The algorithm works under adversarial preferences. Previous algorithms either made severely limiting assumptions on the structure of the preference vectors, or had polynomial overhead. Research of N. Alon supported in part by the Israel Science Foundation and by the Von Neumann Fund. B. Awerbuch supported by NSF grants ANIR-0240551, CCF-0515080 and CCR-0311795. Research of Y. Azar supported in part by the German-Israeli Foundation and by the Israel Science Foundation. Research of B. Patt-Shamir supported in part by Israel Ministry of Science and Technology and by the Israel Science Foundation (grant 664/05).