1987
DOI: 10.1016/0300-9467(87)85028-1
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Simulation and evaluation of chromatographic response curves using various methods

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Cited by 7 publications

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“…These effects can be minimized by proper design of the experimental setup but can never be eliminated. In addition to the above factors, the method of analysis plays a crucial role in determining the accuracy of the estimated value of effective diffusivities (Aust et al, 1987). In order to remove the uncertainty resulting from the presence of end effects and inaccuracies in the data at the tail section of the response, a time domain procedure (Krishnan, 1993) was employed for data analysis and effective diffusivity estimation.…”
Section: Pulse Chromatographic Experiments and Data Analysis
mentioning
confidence: 99%
“…5.4, 5.5, and 5.6 may be seen in Figs. 5.7,5.8, and 5.9, respectively, which give the pore size distributions obtained from nitrogen desorption and mercury intrusion. Nitrogen desorption, which in general gives reliable information for pores with radius less than 1000 A, shows very little particle voidage €or the carbonated sample, whereas mercury porosimetry indicates much higher porosity, even for pores smaller than 1000 A.…”
Section: Pulse Chromatographic Experiments and Data Analysis
mentioning
confidence: 99%
“…The physical changes that the precursor undergoes upon reaction (that is, the development of internal pore space during calcination or the reduction of the size of existing pores during carbonation) can be the only cause of the differences seen in the response curves. The particle voidage and the intraparticle effective diffusivity are in turn (see eqs (5). and (6)) the only parameters of the chromatographic response model that are affected by the internal structure of the particles.…”
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confidence: 99%
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