Computational study of boron nitride nanotube synthesis: how catalyst morphology stabilizes the boron nitride bond

In an attempt to understand why catalytic methods for the growth of boron nitride nanotubes work much worse than for their carbon counterparts, we use first-principles calculations to study the energetics of elemental reactions forming N2, B2 and BN molecules on an iron catalyst. We observe that in the case of these small molecules, the catalytic activity is hindered by the formation of B2 on the iron surface. We also observe that the local morphology of a step edge present in our nanoparticle model stabilizes the boron nitride molecule with respect to B2 due to the ability of the step edge to offer sites with different coordination simultaneously for nitrogen and boron. Our results emphasize the importance of atomic steps for a high yield chemical vapor deposition growth of BN nanotubes and may outline new directions for improving the efficiency of the method.Comment: submitted to physical review

OGSA/Globus Evaluation for Data Intensive Applications

We present an architecture of Globus Toolkit 3 based testbed intended for evaluation of applicability of the Open Grid Service Architecture (OGSA) for Data Intensive Applications.Comment: To be published in the proceedings of the XIX International Symposium on Nuclear Electronics and Computing (NEC'2003), Bulgaria, Varna, 15-20 September, 200

Hexahydrite (MgSO46H2O) as an Effloreschence of Some Ohio Dolomites

Author Institution: Department of Mineralogy, The Ohio State University, Columbus 10 Ohio Division of Geological Survey, Columbu

String amplitudes in arbitrary dimensions

We calculate gravitational dressed tachyon correlators in non critcal dimensions. The 2D gravity part of our theory is constrained to constant curvature. Then scaling dimensions of gravitational dressed vertex operators are equal to their bare conformal dimensions. Considering the model as d+2 dimensional critical string we calculate poles of generalized Shapiro-Virasoro amplitudes.Comment: 14 page

Link and subgraph likelihoods in random undirected networks with fixed and partially fixed degree sequence

The simplest null models for networks, used to distinguish significant features of a particular network from {\it a priori} expected features, are random ensembles with the degree sequence fixed by the specific network of interest. These "fixed degree sequence" (FDS) ensembles are, however, famously resistant to analytic attack. In this paper we introduce ensembles with partially-fixed degree sequences (PFDS) and compare analytic results obtained for them with Monte Carlo results for the FDS ensemble. These results include link likelihoods, subgraph likelihoods, and degree correlations. We find that local structural features in the FDS ensemble can be reasonably well estimated by simultaneously fixing only the degrees of few nodes, in addition to the total number of nodes and links. As test cases we use a food web, two protein interaction networks (\textit{E. coli, S. cerevisiae}), the internet on the autonomous system (AS) level, and the World Wide Web. Fixing just the degrees of two nodes gives the mean neighbor degree as a function of node degree, $_k$, in agreement with results explicitly obtained from rewiring. For power law degree distributions, we derive the disassortativity analytically. In the PFDS ensemble the partition function can be expanded diagrammatically. We obtain an explicit expression for the link likelihood to lowest order, which reduces in the limit of large, sparse undirected networks with $L$ links and with $k_{\rm max} \ll L$ to the simple formula $P(k,k') = kk'/(2L + kk')$. In a similar limit, the probability for three nodes to be linked into a triangle reduces to the factorized expression $P_{\Delta}(k_1,k_2,k_3) = P(k_1,k_2)P(k_1,k_3)P(k_2,k_3)$.Comment: 17 pages, includes 11 figures; first revision: shortened to 14 pages (7 figures), added discussion of subgraph counts, deleted discussion of directed network

The true reinforced random walk with bias

We consider a self-attracting random walk in dimension d=1, in presence of a field of strength s, which biases the walker toward a target site. We focus on the dynamic case (true reinforced random walk), where memory effects are implemented at each time step, differently from the static case, where memory effects are accounted for globally. We analyze in details the asymptotic long-time behavior of the walker through the main statistical quantities (e.g. distinct sites visited, end-to-end distance) and we discuss a possible mapping between such dynamic self-attracting model and the trapping problem for a simple random walk, in analogy with the static model. Moreover, we find that, for any s>0, the random walk behavior switches to ballistic and that field effects always prevail on memory effects without any singularity, already in d=1; this is in contrast with the behavior observed in the static model.Comment: to appear on New J. Phy

Two-dimensional laser collision-induced fluorescence measurements of plasma properties near an RF plasma cathode extraction aperture

A dense plasma structure was observed to form near the extraction aperture of a helium RF plasma cathode. Laser collision-induced fluorescence was used to generate two-dimensional spatial maps of the electron density and the effective electron temperature within the structure over a range of operating conditions. The aperture plasma reached densities nearly an order of magnitude higher than the surrounding bulk plasma. The sharp spatial change in density at the plasma structure boundary suggests the presence of a double layer sheath. Higher temperature electrons were also observed at the periphery of the plasma structure. Variations in the observed plasma structure with extracted electron current were found to be consistent with reported low pressure anode spot behavior. Measurements of plasma density within and at the boundary of the structure, and the dependence of these on the current extracted across the external gap, are compared with calculations and discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98614/1/0963-0252_21_5_055030.pd

Four Centuries of Change in Northeastern United States Forests

The northeastern United States is a predominately-forested region that, like most of the eastern U.S., has undergone a 400-year history of intense logging, land clearance for agriculture, and natural reforestation. This setting affords the opportunity to address a major ecological question: How similar are today's forests to those existing prior to European colonization? Working throughout a nine-state region spanning Maine to Pennsylvania, we assembled a comprehensive database of archival land-survey records describing the forests at the time of European colonization. We compared these records to modern forest inventory data and described: (1) the magnitude and attributes of forest compositional change, (2) the geography of change, and (3) the relationships between change and environmental factors and historical land use. We found that with few exceptions, notably the American chestnut, the same taxa that made up the pre-colonial forest still comprise the forest today, despite ample opportunities for species invasion and loss. Nonetheless, there have been dramatic shifts in the relative abundance of forest taxa. The magnitude of change is spatially clustered at local scales (<125 km) but exhibits little evidence of regional-scale gradients. Compositional change is most strongly associated with the historical extent of agricultural clearing. Throughout the region, there has been a broad ecological shift away from late successional taxa, such as beech and hemlock, in favor of early- and mid-successional taxa, such as red maple and poplar. Additionally, the modern forest composition is more homogeneous and less coupled to local climatic controls

Resonant forcing of select degrees of freedom of multidimensional chaotic map dynamics

We study resonances of multidimensional chaotic map dynamics. We use the calculus of variations to determine the additive forcing function that induces the largest response, that is, the greatest deviation from the unperturbed dynamics. We include the additional constraint that only select degrees of freedom be forced, corresponding to a very general class of problems in which not all of the degrees of freedom in an experimental system are accessible to forcing. We find that certain Lagrange multipliers take on a fundamental physical role as the efficiency of the forcing function and the effective forcing experienced by the degrees of freedom which are not forced directly. Furthermore, we find that the product of the displacement of nearby trajectories and the effective total forcing function is a conserved quantity. We demonstrate the efficacy of this methodology with several examples.Comment: 11 pages, 3 figure