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The four-fold variation of diffusion rates for aluminum and ferric ions diffusing through the same membrane (Table 5) contradicts the theory that valency is the principle rate-determining characteristic for interdiffusion rates (Prakash and Sengupta, 2003).
The variation of diffusion coefficients also followed the same order.
The variation of diffusion coefficient D with temperature is shown in Figure 2a.
An analysis is presented of the variation of diffusion and reaction performance with catalyst porosity architecture.
The variation of diffusion coefficient with concentration of the solvents has been discussed.
Electrochemical experiments were completed with viscosity measurements to explain the variation of diffusion coefficients for TEA+.
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Variations of diffusion constants and surface adsorbates with crystallographic direction may further contribute to the observed heterogeneity.
However, the variations of diffusion coefficients at different temperatures needs to be considered and the adjustment of sampling constant was a must when sampling at temperatures different from 25°CC.
It is also demonstrated that the accuracy of calculating mass fluxes in membrane extractors became worse when the variation of diffusivities with concentration along the diffusion path is neglected, and also, when the effect of the membrane on interrelationships between the mass fluxes (referred to the stationary system of coordinates) is not taken into account.
The spatial variation of this diffusion coefficient occurs in such a way that it prefers forward diffusion to backward diffusion resulting in effective reconstruction of structural content and detection of weak edges.
Open image in new window Fig. 5 Variation of thermal diffusion factor of C1 with depth Open image in new window Fig. 6 Sensitivity analysis of C1 thermal diffusion factor calculated by Hasse model Open image in new window Fig. 7 Sensitivity analysis of C1 thermal diffusion factor calculated by Kempers model.
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