The effect of the spatially heterogeneous nature of zeolite pores on molecular arrangement and adsorption is investigated. Three zeolites (MFI, MOR, and BOG) are chosen to represent structures containing dissimilar pore shapes and sizes. Four simple adsorbates (argon, methane, CF4, and SF6) are chosen as probes of varying size and interaction energy. Direct Monte Carlo integration of the partition function is used to determine free energies, potential energies and entropies of adsorption in spatially distinct regions of the zeolites at low loadings. These calculations lead to intuitive explanations of siting seen in one- and two-component grand canonical Monte Carlo simulations of adsorption. Both simulation techniques are implemented using the same potential model in identical zeolites. Owing to the similar nature of the two MFI channels, only small differences in adsorption free energies between channels are seen and segregation effects are minimal. Conversely, the very heterogeneous nature of MOR leads to substantial free energies differences and pronounced segregation. Confinement effects in the MOR side pockets produce a large entropic penalty for adsorption. The dissimilar 10-ring and 12-ring channels in BOG also lead to substantial segregation under many conditions. The siting distributions for the single-component systems are explained using filling and packing effects. The binary data is explained by introducing four qualitative models that can be used to classify the observed segregation.

Process intensification in rotating packed beds has attracted attention. The intensification is due to the large specific surface area of the packing and high liquid- and gas-side mass-transfer coefficients. Recent studies indicate that the slip velocity between the gas and the liquid in a rotating bed is in the same range as in conventional packed columns. Hence, the intensification is limited to a higher surface area of the packing if the resistance for mass transfer is on the gas side. To overcome this limitation, we proposed a rotating packed bed with split packing to promote the slip velocity as high as 30 m/s. To assess its efficacy, we have measured the mass-transfer coefficients on the gas side using the absorption of SO2 from air into aqueous NaOH solution and the one on the liquid side by the stripping of oxygen from water into nitrogen. The volumetric mass-transfer coefficients on the gas side and the liquid side, respectively, were in the ranges 35−280× and 25−250× compared to those of packed columns. Correlations for the local mass-transfer coefficients have been presented. The studies indicate a volume reduction of the units by 2 orders of magnitude is feasible.

This paper presents a brief review on job shop scheduling techniques in semiconductor manufacturing. The manufacturing environment in a semiconductor industry is considered a highly complex job shop, involving multiple types of work centers, large and changing varieties of products, sequencedependent setup times, reentrant process flow, etc., in a dynamic scheduling environment. Due to the stubborn nature of the deterministic job shop scheduling problem itself, many of the solutions proposed are of hybrid construction cutting across the traditional disciplines. The problem has been investigated from a variety of perspectives resulting in several analytical techniques combining generic as well as problem-specific strategies. In this paper, we seek to provide a brief overview of the problem, the techniques used and the researchers involved in solving this problem.

An efficient use of NiCl(2)·6H(2)O, for the cross-coupling of arylboronic acids with various N-nucleophiles, has been demonstrated. The method is practical and offers an alternative to the corresponding Cu-mediated Chan-Lam process for the construction of the C-N bond.

Abstract.Using hidden Markov models (HMMs) and traditional behavior analysis, we have examined the effect of metacognitive prompting on students' learning in the context of our computer-based learning-by-teaching environment. This paper discusses our analysis techniques, and presents evidence that HMMs can be used to effectively determine students' pattern of activities. The results indicate clear differences between different interventions, and links between students learning performance and their interactions with the system.