245,091 research outputs found
Crystal nuclei templated nanostructured membranes prepared by solvent crystallization and polymer migration
Currently, production of porous polymeric membranes for filtration is predominated by the phase-separation process. However, this method has reached its technological limit, and there have been no significant breakthrough over the last decade. Here we show, using polyvinylidene fluoride as a sample polymer, a new concept of membrane manufacturing by combining oriented green solvent crystallization and polymer migration is able to obtain high performance membranes with pure water permeation flux substantially higher than those with similar pore size prepared by conventional phase-separation processes. The new manufacturing procedure is governed by fewer operating parameters and is, thus, easier to control with reproducible results. Apart from the high water permeation flux, the prepared membranes also show excellent stable flux after fouling and superior mechanical properties of high pressure load and better abrasion resistance. These findings demonstrate the promise of a new concept for green manufacturing nanostructured polymeric membranes with high performances
Generalized Dynamic Scaling for Critical Relaxations
The dynamic relaxation process for the two dimensional Potts model at
criticality starting from an initial state with very high temperature and
arbitrary magnetization is investigated with Monte Carlo methods. The results
show that there exists universal scaling behaviour even in the short-time
regime of the dynamic evolution. In order to describe the dependence of the
scaling behaviour on the initial magnetization, a critical characteristic
function is introduced.Comment: Latex, 8 pages, 3 figures, to appear in Phys. Rev. Let
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Plasma fluctuations as Markovian noise
Noise theory is used to study the correlations of stationary Markovian fluctuations that are homogeneous and isotropic in space. The relaxation of the fluctuations is modeled by the diffusion equation. The spatial correlations of random fluctuations are modeled by the exponential decay. Based on these models, the temporal correlations of random fluctuations, such as the correlation function and the power spectrum, are calculated. We find that the diffusion process can give rise to the decay of the correlation function and a broad frequency spectrum of random fluctuations. We also find that the transport coefficients may be estimated by the correlation length and the correlation time. The theoretical results are compared with the observed plasma density fluctuations from the tokamak and helimak experiments.Physic
The impacts of surface conditions on the vapor-liquid-solid growth of germanium nanowires on Si (100) substrate
The impacts of surface conditions on the growth of Ge nanowires on a Si (100) substrate are discussed in detail. On SiO2-terminated Si substrates, high-density Ge nanowires can be easily grown. However, on H-terminated Si substrates, growing Ge nanowires is more complex. The silicon migration and the formation of a native SiO2 overlayer on a catalyst surface retard the growth of Ge nanowires. After removing this overlayer in the HF solution, high-density and well-ordered Ge nanowires are grown. Ge nanowires cross vertically and form two sets of parallel nanowires. It is found that nanowires grew along ?110? direction
Dynamics of neural systems with discrete and distributed time delays
In real-world systems, interactions between elements do not happen instantaneously, due to the time
required for a signal to propagate, reaction times of individual elements, and so forth. Moreover,
time delays are normally nonconstant and may vary with time. This means that it is vital to introduce
time delays in any realistic model of neural networks. In order to analyze the fundamental
properties of neural networks with time-delayed connections, we consider a system of two coupled
two-dimensional nonlinear delay differential equations. This model represents a neural network,
where one subsystem receives a delayed input from another subsystem. An exciting feature of the
model under consideration is the combination of both discrete and distributed delays, where distributed
time delays represent the neural feedback between the two subsystems, and the discrete
delays describe the neural interaction within each of the two subsystems. Stability properties are
investigated for different commonly used distribution kernels, and the results are compared to the
corresponding results on stability for networks with no distributed delays. It is shown how approximations
of the boundary of the stability region of a trivial equilibrium can be obtained analytically
for the cases of delta, uniform, and weak gamma delay distributions. Numerical techniques are used
to investigate stability properties of the fully nonlinear system, and they fully confirm all analytical
findings
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