88 resultados para heterogeneous nucleation
Resumo:
There are p heterogeneous objects to be assigned to n competing agents (n > p) each with unit demand. It is required to design a Groves mechanism for this assignment problem satisfying weak budget balance, individual rationality, and minimizing the budget imbalance. This calls for designing an appropriate rebate function. When the objects are identical, this problem has been solved which we refer as WCO mechanism. We measure the performance of such mechanisms by the redistribution index. We first prove an impossibility theorem which rules out linear rebate functions with non-zero redistribution index in heterogeneous object assignment. Motivated by this theorem,we explore two approaches to get around this impossibility. In the first approach, we show that linear rebate functions with non-zero redistribution index are possible when the valuations for the objects have a certain type of relationship and we design a mechanism with linear rebate function that is worst case optimal. In the second approach, we show that rebate functions with non-zero efficiency are possible if linearity is relaxed. We extend the rebate functions of the WCO mechanism to heterogeneous objects assignment and conjecture them to be worst case optimal.
Resumo:
A study of the deposition of aluminium oxide films by low-pressure metalorganic chemical vapour deposition from the complex aluminium acetylacetonate, in the absence of an oxidant gas, has been carried out. Depositions on to Si(100), stainless steel, and TiN-coated cemented carbide are found to be smooth, shiny, and blackish. SIMS, XPS and TEM analyses reveal that films deposited at temperatures as low as 600 degreesC contain small crystallites Of kappa-Al2O3, embedded in an amorphous matrix rich in graphitic carbon. Optical and scanning electron microscopy reveal a surface morphology made up of spherulites that suggests that film growth might involve a melting process. A nucleation and growth mechanism, involving the congruent melting clusters of precursor molecules on the hot substrate surface, is therefore invoked to explain these observations. An effort has been made experimentally to verify this proposed mechanism. (C) 2002 Elsevier Science B.V. All rights reserved.
Resumo:
Phase transformations of Al2O3 and Na2O · 6Al2O3 prepared by the gel route have been investigated for the first time by 27Al MAS NMR spectroscopy in combination with x-ray diffraction. Of particular interest in the study is the kinetics of the γ → α and γ → β transformations, respectively, in these two systems. Analysis of the kinetic data shows the important role of nucleation in both these transformations.
Resumo:
MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.
Resumo:
In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.
Resumo:
The theory of phase formation is generalised for any arbitrary time dependence of nucleation and growth rates. Some sources of this time dependence are time-dependent potential inputs, ohmic drop and the ingestion effect. Particular cases, such as potentiostatic and, especially, linear potential sweep, are worked out for the two limiting cases of nucleation, namely instantaneous and progressive. The ohmic drop is discussed and a procedure for this correction is indicated. Recent results of Angerstein-Kozlowska, Conway and Klinger are critically investigated. Several earlier results are deduced as special cases. Evans' overlap formula is generalised for the time-dependent case and the equivalence between Avrami's and Evans' equations established.
Resumo:
A new class of models which are based on adsorption, nucleation growth and their coupling is discussed. In particular, the potentiostatic response of a model that involves nucleative phase growth via direct incorporation and adsorptive discharge of metal ions on the free area is analysed for both instantaneous and progressive nucleation. This model is able to predict certain experimental features in the potentiostatic transient, like the initial fall, shoulder or maximum (as well as minimum) which have not been predicted by models analysed hitherto.Limiting behaviour for short and long times as well as a description of the above-mentioned features in terms of model parameters are given.A special case of the above model, viz. a reversible adsorption–nucleation model, wherein the adsorption is very fast, is shown to give rise to transients which can be distinguished from the pure nucleation-growth transients only by its parametric dependence, but not by the form.
Resumo:
Theoretical and computational investigations of nucleation have been plagued by the sensitivity of the phase diagram to the range of the interaction potential. As the surface tension depends strongly on the range of interaction potential and as the classical nucleation theory (CNT) predicts the free energy barrier to be directly proportional to the cube of the surface tension, one expects a strong sensitivity of nucleation barrier to the range of the potential; however, CNT leaves many aspects unexplored. We find for gas-liquid nucleation in Lennard-Jones system that on increasing the range of interaction the kinetic spinodal (KS) (where the mechanism of nucleation changes from activated to barrierless) shifts deeper into the metastable region. Therefore the system remains metastable for larger value of supersaturation and this allows one to explore the high metastable region without encountering the KS. On increasing the range of interaction, both the critical cluster size and pre-critical minima in the free energy surface of kth largest cluster, at respective kinetic spinodals, shift towards smaller cluster size. In order to separate surface tension contribution to the increase in the barrier from other non-trivial factors, we introduce a new scaling form for surface tension and use it to capture both the temperature and the interaction range dependence of surface tension. Surprisingly, we find only a weak non-trivial contribution from other factors to the free energy barrier of nucleation. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3685835]
Resumo:
The effect of incorporation of a centrally positioned Ac(6)c-Xxx segment where Xxx = (L)Val/(D)Val into a host oligopeptide composed of L-amino acid residues has been investigated. Studies of four designed octapeptides Boc-Leu-Phe-Val-Ac(6)c-Xxx-Leu-Phe-Val-OMe (Xxx = (D)Val 1, (L)Val 2) Boc-Leu-Val-Val-Ac(6)c-Xxx-Leu-Val-Val-OMe (Xxx = (D)Val 3, (L)Val 4) are reported. Diagnostic nuclear Overhouse effects characteristic of hairpin conformations are observed for Xxx = (D)Val peptides (1 and 3) while continuous helical conformation characterized by sequential NiH <-> Ni+1H NOEs are favored for Xxx = (L)Val peptides (2 and 4) in methanol solutions. Temperature co-efficient of NH chemical shifts are in agreement with distinctly different conformational preferences upon changing the configuration of the residue at position 5. Crystal structures of peptides 2 and 4 (Xxx = (L)Val) establish helical conformations in the solid state, in agreement with the structures deduced from NMR data. The results support the design principle that centrally positioned type I beta-turns may be used to nucleate helices in short peptides, while type I' beta-turns can facilitate folding into beta-hairpins.
Resumo:
In order to resolve some missing micromechanistic details regarding contact deformation in nitride multilayer coatings we report here observations from cross-sectional transmission electron microscopy and focused ion beam studies of the Vickers indentations on TiN/TiAlN multilayer films of various total thicknesses as well as bilayer periods. The study of damage induced by contact deformation in a nitride multilayer coating is complemented by stress calculated using an analytical model. Kinked boundaries of sliding columns give rise to cracks which propagate at an angle to the indentation axis under a combination of compressive and shear stresses. It is seen that multilayers provide more distributed columnar sliding, thereby reducing the stress intensity factor for shear cracking, while interfacial dislocations provide a stress relief mechanism by enabling lateral movement of material. (C) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Resumo:
A steady state kinetic model has been developed for the vapor-liquid-solid growth of Si whiskers or nanowires from liquid catalyst droplets. The steady state is defined as one in which the net injection rate of Si into the droplet is equal to the ejection rate due to wire growth. Expressions that represent specific mechanisms of injection and ejection of Si atoms from the liquid catalyst droplet have been used and their relative importance has been discussed. The analysis shows that evaporation and reverse reaction rates need to be invoked, apart from just surface cracking of the precursor, in order to make the growth rate radius dependent. When these pathways can be neglected, the growth rate become radius independent and can be used to determine the activation energies for the rate limiting step of heterogeneous precursor decomposition. The ejection rates depend on the mechanism of wire growth at the liquid-solid interface or the liquid-solid-vapor triple phase boundary. It is shown that when wire growth is by nucleation and motion of ledges, a radius dependence of growth rate does not just come from the Gibbs-Thompson effect on supersaturation in the liquid, but also from the dependence of the actual area or length available for nucleation. Growth rates have been calculated using the framework of equations developed and compared with experimental results. The agreement in trends is found to be excellent. The same framework of equations has also been used to account for the diverse pressure and temperature dependence of growth rates reported in the literature. © 2012 American Institute of Physics.
Resumo:
Temperature dependent X-ray powder diffraction and dielectric studies have been carried out on tetragonal compositions of (1-x) PbTiO 3(x) BiMeO 3; Me similar to Sc and Zn 1/2 Ti 1/2. The cubic and the tetragonal phases coexist over more than 100 degrees C for 0.70 PbTiO 30.3 Bi ( Zn 1/2 Ti 1/2) O 3 and 0.66 PbTiO 30.34 BiScO 3. The wide temperature range of phase coexistence is shown to be an intrinsic feature of the system, and is attributed to the increase in the degree of the covalent character of the ( Pb +Bi ) O bond with increasing concentration of Bi at the Pb -site. The d-values of the {111} planes of the coexisting phases are nearly identical, suggesting this plane to be the invariant plane for the martensitic type cubic-tetragonal transformation occurring in these systems.
Resumo:
Practical usage of machine learning is gaining strategic importance in enterprises looking for business intelligence. However, most enterprise data is distributed in multiple relational databases with expert-designed schema. Using traditional single-table machine learning techniques over such data not only incur a computational penalty for converting to a flat form (mega-join), even the human-specified semantic information present in the relations is lost. In this paper, we present a practical, two-phase hierarchical meta-classification algorithm for relational databases with a semantic divide and conquer approach. We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables. The proposed algorithm was evaluated on three diverse datasets. namely TPCH, PKDD and UCI benchmarks and showed considerable reduction in classification time without any loss of prediction accuracy. (C) 2012 Elsevier Ltd. All rights reserved.
Resumo:
MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.