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Sci. Pharm.
Volume 77
Issue 7
10.3797/scipharm.oephg.21.PO-34
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Scientia Pharmaceutica is published by MDPI from Volume 84 Issue 3 (2016). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Austrian Pharmaceutical Society (Österreichische Pharmazeutische Gesellschaft, ÖPhG).
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Abstract

Cellulose Derivatives: Optimization of Regression Equation to Predict Viscosity of Aqueous Solutions

by
Z. ŠKLUBALOVÁ
Department of Pharmaceutical Technology, Faculty of Pharmacy, Charles University in Prague, Heyrovského 1203, 500 05 Hradec Králové, Czech Republic
Sci. Pharm. 2009, 77(7), 233; https://doi.org/10.3797/scipharm.oephg.21.PO-34
Submission received: 16 April 2009 / Accepted: 16 April 2009 / Published: 16 April 2009
Versions Notes

Abstract

For over 50 years, cellulose derivatives have been used as excellent pharmaceutical excipients. Commercially, cellulose products are designated with viscosity grade, proportional to the molecular weight or chain length, which identifies the product numerically based on viscosity value (in mPa⋅s) measured at 2% w/v concentration in water at 20°C using an Ubbelohde viscometer. A wide range of viscosity grades are available.

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MDPI and ACS Style

ŠKLUBALOVÁ, Z. Cellulose Derivatives: Optimization of Regression Equation to Predict Viscosity of Aqueous Solutions. Sci. Pharm. 2009, 77, 233. https://doi.org/10.3797/scipharm.oephg.21.PO-34

AMA Style

ŠKLUBALOVÁ Z. Cellulose Derivatives: Optimization of Regression Equation to Predict Viscosity of Aqueous Solutions. Scientia Pharmaceutica. 2009; 77(Posters (PO)):233. https://doi.org/10.3797/scipharm.oephg.21.PO-34

Chicago/Turabian Style

ŠKLUBALOVÁ, Z. 2009. "Cellulose Derivatives: Optimization of Regression Equation to Predict Viscosity of Aqueous Solutions" Scientia Pharmaceutica 77, Posters (PO): 233. https://doi.org/10.3797/scipharm.oephg.21.PO-34

APA Style

ŠKLUBALOVÁ, Z. (2009). Cellulose Derivatives: Optimization of Regression Equation to Predict Viscosity of Aqueous Solutions. Scientia Pharmaceutica, 77(Posters (PO)), 233. https://doi.org/10.3797/scipharm.oephg.21.PO-34

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