Reaction mechanism studies for platinum nanoparticle growth by atomic layer deposition

Mass spectrometry is used to study the reaction mechanism of platinum (Pt) atomic layer deposition (ALD) on large quantities of high surface area silica gel particles in a fluidized bed reactor. (Methylcyclopentadienyl)trimethylplatinum [(MeCp)PtMe₃] and oxygen are used as precursors. Studies are conducted at a substrate temperature of 320 °C. The self-limiting behavior of ALD appears to be disrupted with overexposure of Pt precursor. The amount of the deposited Pt and the size of the Pt nanoparticles increase with an increasing overdose time of Pt precursor. This can be explained by the thermal decomposition of Pt precursor at the reaction temperature of 320 °C and the in situ sintering of Pt nanoparticles forming larger particles. This finding is significant and its understanding is essential for better control of Pt deposition to achieve desirable morphological and structural properties for different application requirements.     

Bivariant Chern character and longitudinal index

In this paper we consider a family of Dirac-type operators on fibration P→B equivariant with respect to an action of an étale groupoid. Such a family defines an element in the bivariant K theory. We compute the action of the bivariant Chern character of this element on the image of Connes' map Φ in the cyclic cohomology. A particular case of this result is Connes' index theorem for étale groupoids [A. Connes, Noncommutative Geometry, Academic Press, 1994] in the case of fibrations.     

Solving Multi-dimensional Evolution Problems with Localized Structures using Second Generation Wavelets

A dynamically adaptive numerical method for solving multi-dimensional evolution problems with localized structures is developed. The method is based on the general class of multi-dimensional second-generation wavelets and is an extension of the second-generation wavelet collocation method of Vasilyev and Bowman to two and higher dimensions and irregular sampling intervals. Wavelet decomposition is used for grid adaptation and interpolation, while O ( N ) hierarchical finite difference scheme, which takes advantage of wavelet multilevel decomposition, is used for derivative calculations. The prowess and computational efficiency of the method are demonstrated for the solution of a number of two-dimensional test problems.     

Optimizing the periodic pick-up of raw materials for a manufacturer of auto parts

We describe a solution procedure for a special case of the periodic vehicle routing problem (PVRP). Operation managers at an auto parts manufacturer in the north of Spain described the optimization problem to the authors. The manufacturer must pick up parts (raw material) from geographically dispersed locations. The parts are picked up periodically at scheduled times. The problem consists of assigning a pickup schedule to each of its supplier’s locations and also establishing daily routes in order to minimize total transportation costs. The time horizon under consideration may be as long as 90 days. The resulting PVRP is such that the critical decision is the assignment of locations to schedules, because once this is done, the daily routing of vehicles is relatively straightforward. Through extensive computational experiments, we show that the metaheuristic procedure described in this paper is capable of finding high-quality solutions within a reasonable amount of computer time. Our main contribution is the development of a procedure that is more effective at handling PVRP instances with long planning horizons when compared to those proposed in the literature.     

Lowest breathing mode of bosonic helium clusters

We analyze various microscopic calculations of vibrational frequencies for ⁴He_N clusters, N = 3-728. The lowest breathing frequency with total angular momentum J = 0 varies smoothly as a function of N, with a maximum around N = 50-120. Received 11 July 2001     

A network-related nuclear power plant model with an intelligent branch-and-bound solution approach

This paper presents a network model with discrete requirements for a nuclear power plant. The model determines the batch size and timing for nuclear unit refueling and how much energy should be produced by nuclear and non-nuclear units for each time period to satisfy forecasted demand with minimum total operating costs over the planning horizon. Efficient modeling and solution strategies are developed which constitute a merger of operations research and artificial intelligence. A branch-and-bound solution approach is combined with a pattern recognition component, involving non-parametric discrimination analyses, to select branching variables and directions. By coupling this approach with network optimization techniques to exploit the underlying network structure of the problem, substantial improvements are obtained both in solution quality and solution efficiency.This research was supported in part by the Center for Business Decision Analysis, the Hugh Roy Cullen Centennial Chair in Business Administration, and the Office of Naval Research under contract N00014-87-K-0190. Reproduction in whole or in part is permitted for any purpose of the U.S. Government. CENTER FOR BUSINESS DECISION ANALYSIS Darwin Klingman, Director The University of Texas at Austin Austin, TX 78712, U.S.A.