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Good agreement was achieved between experimental dissolution data and the modeling results.
A three-dimensional, bench-scale model aquifer previously designed by Chrysikopoulos et al. (Water Resour. Res. 36 7) (2000) 1687) was employed for collection of the experimental dissolution data.
In addition, the experimental dissolution flux data are used to evaluate predictions made using independently obtained model parameters and analytical mathematical models incorporating the two basic approaches used for mathematically describing the interphase distribution of NAPLs: the local equilibrium (LE) approach; and the mass transfer limited, or nonequilibrium (NE) approach.
Even when the dominant step type is determined from microscopic observations, experimental dissolution data obtained over a range of saturation and temperature are still needed to empirically derive the temperature dependence for the step edge energy, site density, and kinetic coefficient.
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At low pH, the experimental gibbsite dissolution was much lower than expected (0.5 mM at pH 2.2), which may suggest that dissolution equilibrium was not reached within 24 h.
In experimental partnership dissolution problems with complete information, the divide-and-choose mechanism is significantly superior to the winner's-bid auction.
Therefore, to characterize the drug release rates in different experimental conditions, another dissolution parameter used for comparing the formulations was mean dissolution time (MDT).
As experimental time increased, dissolution became important that the linear relationship would no longer exist.
Under the latter experimental conditions the dissolution rate increased, as qualitatively expected, over that predicted by theory.
To explore the influence of bacterial CA on CO2 capture capacity in CO2-H2O-carbonate system, a flow dissolution experimental device was designed to simulate CO2 absorption by rainwater infiltration or surface water flushing.
In this study the selection of in vivo predictive in vitro dissolution experimental set-ups using a multivariate analysis approach, in line with the Quality by Design (QbD) principles, is explored.
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