A Direct Approach to Insulin Isotherm Analysis in Reversed Phase Chromatography

Katti, Anita M.; Kmiotek, Kraig; Geng, Junzhe; Goel, Pallavi

doi:10.1365/s10337-009-1131-y

Cited by 2 publications

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“…Control of the temperature and feed concentration can avoid changes in viscosity that may result in viscous fingering, poor separation, and higher operating pressures. The robustness of the process is altered by variations in the operating pressure which causes variability in the column efficiency, fluctuations in the adsorption isotherm, and performance of the separation. , Creating an engineering design and operating conditions that scale-up to meet yield and production rate , targets are critical to effective strategies for marketing, sales, and profitability. Applications of process chromatography show that in low, medium, and high pressure modes, there is an interconnection between the design pressure, the operating parameters, and the outcome of optimization protocols. − …”

Section: Introductionmentioning

confidence: 99%

Prediction of Viscosity−Temperature−Composition Surfaces in a Single Expression for Methanol−Water and Acetonitrile−Water Mixtures

et al. 2008

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The modeling of the surface of viscosity in composition and temperature at atmospheric pressure for methanol−water and acetonitrile−water was performed by interconnecting various elementary functions and testing them in a systematic manner to minimize the least-squares error. The systematic approach involved developing expressions that were the sum or product of elementary functions in temperature and composition, then visually observing their fit and quantitating the error. To reduce the error, transformation of the data using elementary functions was necessary to create a modified surface simpler in form. For MeOH−H2O, the least-squares error was 0.6 and 0.01 for untransformed data and transformed data, respectively. Similarly, for ACN−H2O, the error was 0.3 and 0.008 for untransformed and transformed data, respectively. The expression describing the viscosity−composition−temperature relationship for both the transformed and untransformed data was a quadratic in x with exponential functions of T as coefficients where T° is a nondimensionalizing term of value one. The transformed temperature is log(T/T°) + 2, while the transformed viscosity was η1/8.

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