Effect of Gravity and Confinement on Phase Equilibria: A Density Matrix Renormalization Approach

The phase diagram of the 2D Ising model confined between two infinite walls and subject to opposing surface fields and to a bulk "gravitational" field is calculated by means of density matrix renormalization methods. In absence of gravity two phase coexistence is restricted to temperatures below the wetting temperature. We find that gravity restores the two phase coexistence up to the bulk critical temperature, in agreement with previous mean-field predictions. We calculate the exponents governing the finite size scaling in the temperature and in the gravitational field directions. The former is the exponent which describes the shift of the critical temperature in capillary condensation. The latter agrees, for large surface fields, with a scaling assumption of Van Leeuwen and Sengers. Magnetization profiles in the two phase and in the single phase region are calculated. The profiles in the single phase region, where an interface is present, agree well with magnetization profiles calculated from a simple solid-on-solid interface hamiltonian.Comment: 4 pages, RevTeX and 4 PostScript figures included. Final version as published. To appear in Phys. Rev. Let

Glauber Critical Dynamics: Exact Solution of the Kinetic Gaussian Model

In this paper, we have exactly solved Glauber critical dynamics of the Gaussian model on three dimensions. Of course, it is much easy to apply to low dimensional case. The key steps are that we generalize the spin change mechanism from Glauber's single-spin flipping to single-spin transition and give a normalized version of the transition probability . We have also investigated the dynamical critical exponent and found surprisingly that the dynamical critical exponent is highly universal which refer to that for one- two- and three-dimensions they have same value independent of spatial dimensionality in contrast to static (equilibrium) critical exponents.Comment: 9 page

Nonequilibrium relaxation of the two-dimensional Ising model: Series-expansion and Monte Carlo studies

We study the critical relaxation of the two-dimensional Ising model from a fully ordered configuration by series expansion in time t and by Monte Carlo simulation. Both the magnetization (m) and energy series are obtained up to 12-th order. An accurate estimate from series analysis for the dynamical critical exponent z is difficult but compatible with 2.2. We also use Monte Carlo simulation to determine an effective exponent, z_eff(t) = - {1/8} d ln t /d ln m, directly from a ratio of three-spin correlation to m. Extrapolation to t = infinity leads to an estimate z = 2.169 +/- 0.003.Comment: 9 pages including 2 figure

The plasticity of berry shrivelling in 'Shiraz': A vineyard survey

Berry water loss during late ripening is a cultivar dependent-trait and is accentuated in wine grape varieties such as 'Shiraz'. 'Shiraz' berry development was monitored in twelve vineyards over two seasons to characterise the extent of weight loss that can occur within a grape growing region. From veraison onwards, berry fresh mass was greatest in vineyards using excessive irrigation and least in vineyards using cautious irrigation strategies. In the first season, berry fresh mass increased, reached a maximum and subsequently declined. Conversely, in the second season, characterised by rain and high humidity, berry fresh mass increased, then stabilised without a consistent decline. In both seasons, berry sugar import rates were highest shortly after veraison but then declined gradually, terminating several weeks after the weight maximum. Notwithstanding that berries with large maximum weights tended to undergo greater rates of weight loss, these berries remained heavier at harvest compared to those berries that were smaller prior to the onset of weight loss. Canopy size, yield and crop load were not key determinants of berry weight loss rates. Berry anthocyanin and sugar accumulation were closely correlated during early ripening but anthocyanin degradation took place during the late weight loss phase

Solvable Kinetic Gaussian Model in External Field

In this paper, the single-spin transition dynamics is used to investigate the kinetic Gaussian model in a periodic external field. We first derive the fundamental dynamic equations, and then treat an isotropic d-dimensional hypercubic lattice Gaussian spin system with Fourier's transformation method. We obtain exactly the local magnetization and the equal-time pair correlation function. The critical characteristics of the dynamical, the complex susceptibility, and the dynamical response are discussed. The results show that the time evolution of the dynamical quantities and the dynamical responses of the system strongly depend on the frequency and the wave vector of the external field.Comment: 11 page

New Dynamic Monte Carlo Renormalization Group Method

The dynamical critical exponent of the two-dimensional spin-flip Ising model is evaluated by a Monte Carlo renormalization group method involving a transformation in time. The results agree very well with a finite-size scaling analysis performed on the same data. The value of $z = 2.13 \pm 0.01$ is obtained, which is consistent with most recent estimates

Interface localisation-delocalisation transition in a symmetric polymer blend: a finite-size scaling Monte Carlo study

Using extensive Monte Carlo simulations we study the phase diagram of a symmetric binary (AB) polymer blend confined into a thin film as a function of the film thickness D. The monomer-wall interactions are short ranged and antisymmetric, i.e, the left wall attracts the A-component of the mixture with the same strength as the right wall the B-component, and give rise to a first order wetting transition in a semi-infinite geometry. The phase diagram and the crossover between different critical behaviors is explored. For large film thicknesses we find a first order interface localisation/delocalisation transition and the phase diagram comprises two critical points, which are the finite film width analogies of the prewetting critical point. Using finite size scaling techniques we locate these critical points and present evidence of 2D Ising critical behavior. When we reduce the film width the two critical points approach the symmetry axis $\phi=1/2$ of the phase diagram and for $D \approx 2 R_g$ we encounter a tricritical point. For even smaller film thickness the interface localisation/delocalisation transition is second order and we find a single critical point at $\phi=1/2$. Measuring the probability distribution of the interface position we determine the effective interaction between the wall and the interface. This effective interface potential depends on the lateral system size even away from the critical points. Its system size dependence stems from the large but finite correlation length of capillary waves. This finding gives direct evidence for a renormalization of the interface potential by capillary waves in the framework of a microscopic model.Comment: Phys.Rev.

Renormalized couplings and scaling correction amplitudes in the N-vector spin models on the sc and the bcc lattices

For the classical N-vector model, with arbitrary N, we have computed through order \beta^{17} the high temperature expansions of the second field derivative of the susceptibility \chi_4(N,\beta) on the simple cubic and on the body centered cubic lattices. (The N-vector model is also known as the O(N) symmetric classical spin Heisenberg model or, in quantum field theory, as the lattice O(N) nonlinear sigma model.) By analyzing the expansion of \chi_4(N,\beta) on the two lattices, and by carefully allowing for the corrections to scaling, we obtain updated estimates of the critical parameters and more accurate tests of the hyperscaling relation d\nu(N) +\gamma(N) -2\Delta_4(N)=0 for a range of values of the spin dimensionality N, including N=0 [the self-avoiding walk model], N=1 [the Ising spin 1/2 model], N=2 [the XY model], N=3 [the classical Heisenberg model]. Using the recently extended series for the susceptibility and for the second correlation moment, we also compute the dimensionless renormalized four point coupling constants and some universal ratios of scaling correction amplitudes in fair agreement with recent renormalization group estimates.Comment: 23 pages, latex, no figure

Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks

peer reviewedaudience: researcher, professionalVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods, i.e.multiple linear regression and artificial neural networks, that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalized likelihood uncertainty estimation (GLUE) approach to predict Ks from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from literature demonstrates the importance of site specific calibration. The dataset used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size -Ks pairs. Finally, an application with the optimized models is presented for a borehole lacking Ks data

Timing of N application and water constraints on N accumulation and juice amino N concentration in Chardonnay grapevines

The amount and timing of nitrogen (N) application to a vineyard is critical for must yeast assimilable nitrogen (YAN) concentrations. YAN concentrations and amino acid profiles are important for the fermentation process and wine composition. Commonly, N is applied at flowering to optimize leaf functioning or after harvest to enhance vine productivity the following season. In this study N was applied at various stages of berry development to determine allocation patterns between vine perennial and annual components and to assess when berry YAN concentrations can best be optimized. Five year old potted 'Chardonnay' vines received ammonium sulfate fertilizer at six different times from full bloom to two weeks before harvest and were also exposed to either full or half irrigation during that period. Reduced water supply resulted in a higher allocation of N to the perennial structures and less to the annual components of the vine. N allocation to the annual components of the vine was greatest when it was applied at full bloom, however allocation to the perennial components was greatest when it was applied after fruit-set to veraison. The timing of N supply had a substantial influence on YAN concentrations, and was highest when N was applied about two weeks after veraison. Low water supply also resulted in higher juice YAN concentrations. The perennial N reserves in the roots were highest under low water supply and when N was applied at veraison, while the allocation to the annual parts was lower under this irrigation regime. The study indicates that timing of N application and the application of water constraints during berry development can impact on N partitioning, while the total amount accumulated by the vine is not altered