109 resultados para IMPULSE-APPROXIMATION CALCULATIONS


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The self-consistent field theory (SCFT) introduced by Helfand for diblock copolymer melts is expected to converge to the strong-segregation theory (SST) of Semenov in the asymptotic limit, $\chi N \rightarrow \infty$. However, past extrapolations of the lamellar/cylinder and cylinder/sphere phase boundaries, within the standard unit-cell approximation, have cast some doubts on whether or not this is actually true. Here we push the comparison further by extending the SCFT calculations to $\chi N = 512,000$, by accounting for exclusion zones in the coronae of the cylindrical and spherical unit cells, and by examining finite-segregation corrections to SST. In doing so, we provide the first compelling evidence that SCFT does indeed reduce to SST.

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Time-resolved studies of chlorosilylene, ClSiH, generated by the 193 nm laser flash photolysis of 1-chloro-1-silacyclopent-3-ene, are carried out to obtain rate constants for its bimolecular reaction with ethene, C2H4, in the gas-phase. The reaction is studied over the pressure range 0.13-13.3 kPa (with added SF6) at five temperatures in the range 296-562 K. The second order rate constants, obtained by extrapolation to the high pressure limits at each temperature, fitted the Arrhenius equation: log(k(infinity)/cm(3) molecule(-1) s(-1))=(-10.55 +/- 0.10) + (3.86 +/- 0.70) kJ mol(-1)/RT ln10. The Arrhenius parameters correspond to a loose transition state and the rate constant at room temperature is 43% of that for SiH2 + C2H4, showing that the deactivating effect of Cl-for-H substitution in the silylene is not large. Quantum chemical calculations of the potential energy surface for this reaction at the G3MP2//B3LYP level show that, as well as 1-chlorosilirane, ethylchlorosilylene is a viable product. The calculations reveal how the added effect of the Cl atom on the divalent state stabilisation of ClSiH influences the course of this reaction. RRKM calculations of the reaction pressure dependence suggest that ethylchlorosilylene should be the main product. The results are compared and contrasted with those of SiH2 and SiCl2 with C2H4.

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The design of high-voltage equipment encompasses the study of oscillatory surges caused by transients such as those produced by switching. By obtaining a model, the response of which reconstructs that observed in the actual system, simulation studies and critical tests can be carried out on the model rather than on the equipment itself. In this paper, methods for the construction of simplified models are described and it is shown how the use of a complex model does not necessarily result in superior response pattern reconstruction.

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Time-resolved studies of chlorosilylene, CISiH, generated by the 193 nm laser flash photolysis of 1-chloro-1-silacyclopent-3-ene, have been carried out to obtain rate constants for its bimolecular reaction with trimethylsilane, Me3SiH, in the gas phase. The reaction was studied at total pressures up to 100 torr (with and without added SF6) over the temperature range 297-407 K. The rate constants were found to be pressure independent and gave the following Arrhenius equation: log(k/cm(3) molecule(-1) s(-1)) = (-13.97 +/- 0.25) + (12.57 +/- 1.64) kJ mol(-1)/RT In 10. The Arrhenius parameters are consistent with a mechanism involving an intermediate complex, whose rearrangement is the rate-determining step. Quantum chemical calculations of the potential energy surface for this reaction and also the reactions of CISiH with SiH4 and the other methylsilanes support this conclusion. Comparisons of both experiment and theory with the analogous Si-H insertion processes of SiH2 and SiMe2 show that the main factor causing the lower reactivity of ClSiH is the secondary energy barrier. The calculations also show the existence of a novel intramolecular H-atom exchange process in the complex of ClSiH with MeSiH3.

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Time-resolved kinetic studies of the reactions of silylene, SiH2, and dideutero-silylene, SiD2, generated by laser. ash photolysis of phenylsilane and phenylsilane-d(3), respectively, have been carried out to obtain rate coefficients for their bimolecular reactions with 2-butyne, CH3C CCH3. The reactions were studied in the gas phase over the pressure range 1-100 Torr in SF6 bath gas at five temperatures in the range 294-612 K. The second-order rate coefficients, obtained by extrapolation to the high pressure limits at each temperature, fitted the Arrhenius equations where the error limits are single standard deviations: log(k(H)(infinity)/cm(3) molecule(-1) s(-1)) = (-9.67 +/- 0.04) + (1.71 +/- 0.33) kJ mol(-1)/RTln10 log(k(D)(infinity)/cm(3) molecule(-1) s(-1)) = (-9.65 +/- 0.01) + (1.92 +/- 0.13) kJ mol(-1)/RTln10 Additionally, pressure-dependent rate coefficients for the reaction of SiH2 with 2-butyne in the presence of He (1-100 Torr) were obtained at 301, 429 and 613 K. Quantum chemical (ab initio) calculations of the SiC4H8 reaction system at the G3 level support the formation of 2,3-dimethylsilirene [cyclo-SiH2C(CH3)=C(CH3)-] as the sole end product. However, reversible formation of 2,3-dimethylvinylsilylene [CH3CH=C(CH3)SiH] is also an important process. The calculations also indicate the probable involvement of several other intermediates, and possible products. RRKM calculations are in reasonable agreement with the pressure dependences at an enthalpy value for 2,3-dimethylsilirene fairly close to that suggested by the ab initio calculations. The experimental isotope effects deviate significantly from those predicted by RRKM theory. The differences can be explained by an isotopic scrambling mechanism, involving H - D exchange between the hydrogens of the methyl groups and the D-atoms in the ring in 2,3-dimethylsilirene-1,1-d(2). A detailed mechanism involving several intermediate species, which is consistent with the G3 energy surface, is proposed to account for this.

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Zn(CN)2 and Ni(CN)2 are known for exhibiting anomalous thermal expansion over a wide temperature range. The volume thermal expansion coefficient for the cubic, three dimensionally connected material, Zn(CN)2, is negative (alpha(V) = −51  10(-6) K-1) while for Ni(CN)2, a tetragonal material, the thermal expansion coefficient is negative in the two dimensionally connected sheets (alpha(a) = −7  10(-6) K-1), but the overall thermal expansion coefficient is positive (alpha(V) = 48  10(-6) K-1). We have measured the temperature dependence of phonon spectra in these compounds and analyzed them using ab initio calculations. The spectra of the two compounds show large differences that cannot be explained by simple mass renormalization of the modes involving Zn (65.38 amu) and Ni (58.69 amu) atoms. This reflects the fact that the structure and bonding are quite different in the two compounds. The calculated pressure dependence of the phonon modes and of the thermal expansion coefficient, alpha(V), are used to understand the anomalous behavior in these compounds. Our ab initio calculations indicate that phonon modes of energy approx. 2 meV are major contributors to negative thermal expansion (NTE) in both the compounds. The low-energy modes of approx.8 and 13 meV in Zn(CN)2 also contribute significantly to the NTE in Zn(CN)2 and Ni(CN)2, respectively. The measured temperature dependence of the phonon spectra has been used to estimate the total anharmonicity of both compounds. For Zn(CN)2, the temperature-dependent measurements (total anharmonicity), along with our previously reported pressure dependence of the phonon spectra (quasiharmonic), is used to separate the explicit temperature effect at constant volume (intrinsic anharmonicity).

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An alternative blind deconvolution algorithm for white-noise driven minimum phase systems is presented and verified by computer simulation. This algorithm uses a cost function based on a novel idea: variance approximation and series decoupling (VASD), and suggests that not all autocorrelation function values are necessary to implement blind deconvolution.

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In this article a simple and effective controller design is introduced for the Hammerstein systems that are identified based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a B-spline neural network. The controller is composed by computing the inverse of the B-spline approximated nonlinear static function, and a linear pole assignment controller. The contribution of this article is the inverse of De Boor algorithm that computes the inverse efficiently. Mathematical analysis is provided to prove the convergence of the proposed algorithm. Numerical examples are utilised to demonstrate the efficacy of the proposed approach.

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In this paper we introduce a new Wiener system modeling approach for memory high power amplifiers in communication systems using observational input/output data. By assuming that the nonlinearity in the Wiener model is mainly dependent on the input signal amplitude, the complex valued nonlinear static function is represented by two real valued B-spline curves, one for the amplitude distortion and another for the phase shift, respectively. The Gauss-Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first order derivatives recursion. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.

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This paper examines the equilibrium phase behavior of thin diblock-copolymer films tethered to a spherical core, using numerical self-consistent field theory (SCFT). The computational cost of the calculation is greatly reduced by implementing the unit-cell approximation (UCA) routinely used in the study of bulk systems. This provides a tremendous reduction in computational time, permitting us to map out the phase behavior more extensively and allowing us to consider far larger particles. The main consequence of the UCA is that it omits packing frustration, but evidently the effect is minor for large particles. On the other hand, when the particles are small, the UCA calculation can be readily followed up with the full SCFT, the comparison to which conveniently allows one to quantitatively assess the effect of packing frustration.

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Road transport and shipping are copious sources of aerosols, which exert a 9 significant radiative forcing, compared to, for example, the CO2 emitted by these sectors. An 10 advanced atmospheric general circulation model, coupled to a mixed-layer ocean, is used to 11 calculate the climate response to the direct radiative forcing from such aerosols. The cases 12 considered include imposed distributions of black carbon and sulphate aerosols from road 13 transport, and sulphate aerosols from shipping; these are compared to the climate response 14 due to CO2 increases. The difficulties in calculating the climate response due to small 15 forcings are discussed, as the actual forcings have to be scaled by large amounts to enable a 16 climate response to be easily detected. Despite the much greater geographical inhomogeneity 17 in the sulphate forcing, the patterns of zonal and annual-mean surface temperature response 18 (although opposite in sign) closely resembles that resulting from homogeneous changes in 19 CO2. The surface temperature response to black carbon aerosols from road transport is shown 20 to be notably non-linear in scaling applied, probably due to the semi-direct response of clouds 21 to these aerosols. For the aerosol forcings considered here, the most widespread method of 22 calculating radiative forcing significantly overestimates their effect, relative to CO2, 23 compared to surface temperature changes calculated using the climate model.

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This work provides a framework for the approximation of a dynamic system of the form x˙=f(x)+g(x)u by dynamic recurrent neural network. This extends previous work in which approximate realisation of autonomous dynamic systems was proven. Given certain conditions, the first p output neural units of a dynamic n-dimensional neural model approximate at a desired proximity a p-dimensional dynamic system with n>p. The neural architecture studied is then successfully implemented in a nonlinear multivariable system identification case study.

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The problem of adjusting the weights (learning) in multilayer feedforward neural networks (NN) is known to be of a high importance when utilizing NN techniques in various practical applications. The learning procedure is to be performed as fast as possible and in a simple computational fashion, the two requirements which are usually not satisfied practically by the methods developed so far. Moreover, the presence of random inaccuracies are usually not taken into account. In view of these three issues, an alternative stochastic approximation approach discussed in the paper, seems to be very promising.