Experimental and thermodynamic assessment of the Ge-Nb-Si ternary phase diagram

Niobium silicide-based in-situ composites have the potential to supersede nickel-based superalloys due to their excellent high temperature mechanical properties and low density. The addition of small amounts of germanium into these systems can significantly improve oxidation resistance. The effect of germanium on the phases formed in bulk niobium silicide-based in-situ composites is not particularly well understood, in particular the effect of introducing germanium on the formation of the Nb5Si3 intermetallic. Limited data is available in the literature. To provide coherent information on the effect of germanium on the phase equilibrium in the Nb-Si system, a comprehensive thermodynamic description of the Ge-Nb-Si system has been developed in the current paper using the CALPHAD method. Initially the Ge-Nb phase diagram was reassessed using the CALPHAD method to take into account recent ab initio data. To supplement limited information on the ternary system in the literature between 800 and 1820 °C, the pseudo binary between Nb5Si3 and Nb5Ge3 was studied experimentally between 1200 and 1500 °C. Experimental and modelling results indicate that the W5Si3 prototype of Nb5Si3 can be stabilised to lower temperatures on the addition of germanium. Ge contents in excess of 12.4 at. % at 1200 °C in stoichiometric Nb5(Ge,Si)3 stabilise the W5Si3 prototype. In non-stoichiometric Nb5(Ge,Si)3, where Nb < 62.5 at. %, lower amounts of Ge are required to stabilised the W5Si3 prototype. The liquidus projection suggests a ternary eutectic with Nb5(Ge,Si)3, Nbss and Nb3Si can form in Nb-Si rich alloys during solidification

Experimental and thermodynamic assessment of the Ge-Nb-Si ternary phase diagram

Niobium silicide-based in-situ composites have the potential to supersede nickel-based superalloys due to their excellent high temperature mechanical properties and low density. The addition of small amounts of germanium into these systems can significantly improve oxidation resistance. The effect of germanium on the phases formed in bulk niobium silicide-based in-situ composites is not particularly well understood, in particular the effect of introducing germanium on the formation of the Nb5Si3 intermetallic. Limited data is available in the literature. To provide coherent information on the effect of germanium on the phase equilibrium in the Nb-Si system, a comprehensive thermodynamic description of the Ge-Nb-Si system has been developed in the current paper using the CALPHAD method. Initially the Ge-Nb phase diagram was reassessed using the CALPHAD method to take into account recent ab initio data. To supplement limited information on the ternary system in the literature between 800 and 1820 °C, the pseudo binary between Nb5Si3 and Nb5Ge3 was studied experimentally between 1200 and 1500 °C. Experimental and modelling results indicate that the W5Si3 prototype of Nb5Si3 can be stabilised to lower temperatures on the addition of germanium. Ge contents in excess of 12.4 at. % at 1200 °C in stoichiometric Nb5(Ge,Si)3 stabilise the W5Si3 prototype. In non-stoichiometric Nb5(Ge,Si)3, where Nb < 62.5 at. %, lower amounts of Ge are required to stabilised the W5Si3 prototype. The liquidus projection suggests a ternary eutectic with Nb5(Ge,Si)3, Nbss and Nb3Si can form in Nb-Si rich alloys during solidification

Hawking-Page Phase Transition of black Dp-branes and R-charged black holes with an IR Cutoff

We show that the confinement-deconfinement phase transition of supersymmetric Yang-Mills theories with 16 supercharges in various dimensions can be realized through the Hawking-Page phase transition between the near horizon geometries of black Dp-branes and BPS Dp-branes by removing a small radius region in the geometry in order to realize a confinement phase, which generalizes the Herzog's discussion for the holographic hard-wall AdS/QCD model. Removing a small radius region in the gravitational dual corresponds to introducing an IR cutoff in the dual field theory. We also discuss the Hawking-Page phase transition between thermal $AdS_5$, $AdS_4$, $AdS_7$ spaces and R-charged AdS black holes coming from the spherical reduction of the decoupling limit of rotating D3-, M2-, and M5- branes in type IIB supergravity and 11 dimensional supergravity in grand canonical ensembles, where the IR cutoff also plays a crucial role in the existence of the phase transition.Comment: 34 pages, 18 figures, JHEP3, v2, references added, v3, some explanations adde

Nonlinear Integer Programming

Research efforts of the past fifty years have led to a development of linear integer programming as a mature discipline of mathematical optimization. Such a level of maturity has not been reached when one considers nonlinear systems subject to integrality requirements for the variables. This chapter is dedicated to this topic. The primary goal is a study of a simple version of general nonlinear integer problems, where all constraints are still linear. Our focus is on the computational complexity of the problem, which varies significantly with the type of nonlinear objective function in combination with the underlying combinatorial structure. Numerous boundary cases of complexity emerge, which sometimes surprisingly lead even to polynomial time algorithms. We also cover recent successful approaches for more general classes of problems. Though no positive theoretical efficiency results are available, nor are they likely to ever be available, these seem to be the currently most successful and interesting approaches for solving practical problems. It is our belief that the study of algorithms motivated by theoretical considerations and those motivated by our desire to solve practical instances should and do inform one another. So it is with this viewpoint that we present the subject, and it is in this direction that we hope to spark further research.Comment: 57 pages. To appear in: M. J\"unger, T. Liebling, D. Naddef, G. Nemhauser, W. Pulleyblank, G. Reinelt, G. Rinaldi, and L. Wolsey (eds.), 50 Years of Integer Programming 1958--2008: The Early Years and State-of-the-Art Surveys, Springer-Verlag, 2009, ISBN 354068274

Knowledge-based energy functions for computational studies of proteins

This chapter discusses theoretical framework and methods for developing knowledge-based potential functions essential for protein structure prediction, protein-protein interaction, and protein sequence design. We discuss in some details about the Miyazawa-Jernigan contact statistical potential, distance-dependent statistical potentials, as well as geometric statistical potentials. We also describe a geometric model for developing both linear and non-linear potential functions by optimization. Applications of knowledge-based potential functions in protein-decoy discrimination, in protein-protein interactions, and in protein design are then described. Several issues of knowledge-based potential functions are finally discussed.Comment: 57 pages, 6 figures. To be published in a book by Springe

Multi-Objective Optimization with an Adaptive Resonance Theory-Based Estimation of Distribution Algorithm: A Comparative Study

Proceedings of: 5th International Conference, LION 5, Rome, Italy, January 17-21, 2011.The introduction of learning to the search mechanisms of optimization algorithms has been nominated as one of the viable approaches when dealing with complex optimization problems, in particular with multi-objective ones. One of the forms of carrying out this hybridization process is by using multi-objective optimization estimation of distribution algorithms (MOEDAs). However, it has been pointed out that current MOEDAs have a intrinsic shortcoming in their model-building algorithms that hamper their performance. In this work we argue that error-based learning, the class of learning most commonly used in MOEDAs is responsible for current MOEDA underachievement. We present adaptive resonance theory (ART) as a suitable learning paradigm alternative and present a novel algorithm called multi-objective ART-based EDA (MARTEDA) that uses a Gaussian ART neural network for model-building and an hypervolume-based selector as described for the HypE algorithm. In order to assert the improvement obtained by combining two cutting-edge approaches to optimization an extensive set of experiments are carried out. These experiments also test the scalability of MARTEDA as the number of objective functions increases.This work was supported by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02.Publicad

Effective Field Theory and the Gamow Shell Model: The 6He Halo Nucleus

We combine Halo/Cluster Effective Field Theory (H/CEFT) and the Gamow Shell Model (GSM) to describe the $0^+$ ground state of $\rm{^6He}$ as a three-body halo system. We use two-body interactions for the neutron-alpha particle and two-neutron pairs obtained from H/CEFT at leading order, with parameters determined from scattering in the p$_{3/2}$ and s$_0$ channels, respectively. The three-body dynamics of the system is solved using the GSM formalism, where the continuum states are incorporated in the shell model valence space. We find that in the absence of three-body forces the system collapses, since the binding energy of the ground state diverges as cutoffs are increased. We show that addition at leading order of a three-body force with a single parameter is sufficient for proper renormalization and to fix the binding energy to its experimental value

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

Global Search for New Physics with 2.0/fb at CDF

Data collected in Run II of the Fermilab Tevatron are searched for indications of new electroweak-scale physics. Rather than focusing on particular new physics scenarios, CDF data are analyzed for discrepancies with the standard model prediction. A model-independent approach (Vista) considers gross features of the data, and is sensitive to new large cross-section physics. Further sensitivity to new physics is provided by two additional algorithms: a Bump Hunter searches invariant mass distributions for "bumps" that could indicate resonant production of new particles; and the Sleuth procedure scans for data excesses at large summed transverse momentum. This combined global search for new physics in 2.0/fb of ppbar collisions at sqrt(s)=1.96 TeV reveals no indication of physics beyond the standard model.Comment: 8 pages, 7 figures. Final version which appeared in Physical Review D Rapid Communication

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012