Study on the kinetics of hydrate formation in a bubble column

Gas hydrate formation experiments were performed using methane in the presence of tetrahydrofuran (THF) in aqueous solution in a transparent bubble column in which a single pipe or a sintered plate was used to produce bubbles. The mole fraction of THF in aqueous solution was fixed at 6%. The hydrate formation kinetic behaviors on the surface of the rising bubble, the mechanical stability of hydrate shell formed on the surface of the bubble, the interactions among the bubbles with hydrate shell were observed and investigated morphologically. The rise velocities of individual bubbles with hydrate shells of different thickness and the consumption rates of methane gas were measured. A kinetic model was developed to correlate the experimentally measured gas consumption rate data. It was found that the hydrate formation rate on the surface of the moving bubble was high, but the formed hydrate shell was not very easy to be broken up. The bubbles with hydrate shells tended to agglomerate rather than merge into bigger bubble. This kind of characteristic of hydrate shell hindered the further formation of hydrate and led to the lower consumption rate of methane. The consumption rate of methane was found to increase with the decrease of temperature or increase of pressure. The increase of gas flux led to a linear increase in consumption rate of methane. It was demonstrated that the developed kinetic model could be used to correlate the consumption rate satisfyingly.

Two-dimensional photovoltaic dark spatial solitons of partially spatially incoherent light

We report a successful experimental observation of two-dimensional photovoltaic dark solitons in an anisotropic crystal with partially spatially incoherent light beams. This kind of solitons results from the bulk photovoltaic effect, which depends on the direction of propagation of the optical beam and on the orientation of the intensity gradient, with respect to the principal axes of the crystal.

Deterministic Column-Based Matrix Decomposition

In this paper, we propose a deterministic column-based matrix decomposition method. Conventional column-based matrix decomposition (CX) computes the columns by randomly sampling columns of the data matrix. Instead, the newly proposed method (termed as CX_D) selects columns in a deterministic manner, which well approximates singular value decomposition. The experimental results well demonstrate the power and the advantages of the proposed method upon three real-world data sets.