28,654 research outputs found

    Superheating systematics of crystalline solids

    Get PDF
    Systematics of superheating (theta= T/Tm–1) of crystalline solids as a function of heating rate (Q) are established as beta= A(Q)(theta+ 1)theta2, where the normalized energy barrier for homogeneous nucleation is beta= 16pigammasl3/(3kTmDeltaHm2), T is temperature, Tm melting temperature, A a Q-dependent parameter, gammasl interfacial energy, DeltaHm heat of fusion, and k Boltzmann's constant. For all elements and compounds investigated, beta varies between 0.2 and 8.2. At 1 and 10^12 K/s, A = 60 and 31, theta= 0.05–0.35 and 0.06–0.45, respectively. Significant superheating is achievable via ultrafast heating. We demonstrate that the degree of superheating achieved in shock-wave loading and intense laser irradiation as well as in molecular dynamics simulations (Q~10^12 K/s) agrees with the theta–beta–Q systematics

    Exclusive Decay of 11^{--} Quarkonia and BcB_c Meson into a Lepton Pair Combined with Two Pions

    Full text link
    We study the exclusive decay of J/ΨJ/\Psi, Υ\Upsilon and BcB_c into a lepton pair combined with two pions in the two kinematic regions. One is specified by the two pions having large momenta, but a small invariant mass. The other is specified by the two pions having small momenta. In both cases we find that in the heavy quark limit the decay amplitude takes a factorized form, in which the nonperturbative effect related to heavy meson is represented by a NRQCD matrix element. The nonperturbative effects related to the two pions are represented by some universal functions characterizing the conversion of gluons into the pions. Using models for these universal functions and chiral perturbative theory we are able to obtain numerical predictions for the decay widths. Our numerical results show that the decay of \jpsi is at order of 10510^{-5} with reasonable cuts and can be observed at BES II and the proposed BES III and CLEO-C. For other decays the branching ratio may be too small to be measured.Comment: 19 pages, Latex 2e file, 12 EPS figures (included). Replaced with version to appear in Eur. Phys. J. C,published online: 8 May 200

    Quantum phonon transport of molecular junctions amide-linked with carbon nanotubes: a first-principle study

    Full text link
    Quantum phonon transport through benzene and alkane chains amide-linked with single wall carbon nanotubes (SWCNTs) is studied within the level of density functional theory. The force constant matrices are obtained from standard quantum chemistry software. The phonon transmission and thermal conductance are from the nonequilibrium Green's function and the mode-matching method. We find that the ballistic thermal conductance is not sensitive to the compression or stretching of the molecular junction. The terminating groups of the SWCNTs at the cutting edges only influence the thermal conductance quantitatively. The conductance of the benzene and alkane chains shows large difference. Analysis of the transmission spectrum shows that (i) the low temperature thermal conductance is mainly contributed by the SWCNT transverse acoustic modes, (ii) the degenerate phonon modes show different transmission probability due to the presence of molecular junction, (iii) the SWCNT twisting mode can hardly be transmitted by the alkane chain. As a result, the ballistic thermal conductance of alkane chains is larger than that of benzene chains below 38 K, while it is smaller at higher temperature.Comment: 5 pages, 5 figure

    NARX-based nonlinear system identification using orthogonal least squares basis hunting

    No full text
    An orthogonal least squares technique for basis hunting (OLS-BH) is proposed to construct sparse radial basis function (RBF) models for NARX-type nonlinear systems. Unlike most of the existing RBF or kernel modelling methods, whichplaces the RBF or kernel centers at the training input data points and use a fixed common variance for all the regressors, the proposed OLS-BH technique tunes the RBF center and diagonal covariance matrix of individual regressor by minimizing the training mean square error. An efficient optimization method isadopted for this basis hunting to select regressors in an orthogonal forward selection procedure. Experimental results obtained using this OLS-BH technique demonstrate that it offers a state-of-the-art method for constructing parsimonious RBF models with excellent generalization performance

    Elastic net prefiltering for two class classification

    No full text
    A two-stage linear-in-the-parameter model construction algorithm is proposed aimed at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage which constructs a sparse linear-in-the-parameter classifier. The prefiltering stage is a two-level process aimed at maximizing a model’s generalization capability, in which a new elastic-net model identification algorithm using singular value decomposition is employed at the lower level, and then, two regularization parameters are optimized using a particle-swarm-optimization algorithm at the upper level by minimizing the leave-one-out (LOO) misclassification rate. It is shown that the LOO misclassification rate based on the resultant prefiltered signal can be analytically computed without splitting the data set, and the associated computational cost is minimal due to orthogonality. The second stage of sparse classifier construction is based on orthogonal forward regression with the D-optimality algorithm. Extensive simulations of this approach for noisy data sets illustrate the competitiveness of this approach to classification of noisy data problems
    corecore