Observation of Two-Step Neutralization in Conductivity and Potentiometric Titration Curve in Polymer Grafted Charged Colloidal Systems

2006 ◽  
Vol 39 (6) ◽  
pp. 2016-2020 ◽  
Author(s):  
Priti Sundar Mohanty ◽  
Tamotsu Harada ◽  
Kozo Matsumoto ◽  
Hideki Matsuoka
Keyword(s):  
Potentiometric Titration ◽  
Titration Curve ◽  
Potentiometric Titration Curve ◽  
Colloidal Systems

scholarly journals Oligomers-model building in protonation equilibria of sitagliptin

2013 ◽  
Vol 11 (11) ◽  
pp. 1799-1807
Author(s):  
Milan Meloun ◽  
Zuzana Ferenčíková ◽  
Irena Niesnerová ◽  
Tomáš Pekárek
Keyword(s):  
Nonlinear Regression ◽  
Titration Curve ◽  
Model Building ◽  
Protonation Constants ◽  
Potentiometric Titration Curve ◽  
Parameter Estimates ◽  
Regression Diagnostics ◽  
Regression Analyses ◽  
Protonation Equilibria ◽  
Fitness Tests

AbstractMixed protonation constants of sitagliptin phosphate at various ionic strengths I (mol kg−1) in range 0.01 and 0.50 and at 298.15 K are determined using FBSTAC4 and HYPERQUAD nonlinear regression analyses of the potentiometric titration curve. At a low concentration c L = 1.1 mmol kg−1 the monomers L, LH, LH2, LH3 and LH4 dominate, while for a concentration range from c L = 13.7 to 24.7 mmol kg−1 dimers L2H2, L2H3, L2H4 and L2H are mainly present. The regression programme has almost no influence on the precision of the protonation constants. The accuracy of the protonation constants log βqr depends on the accuracy of the group parameters. As two group parameters c L,0, c H,T are ill-conditioned in a model, their determination is therefore uncertain: both can significantly cause a systematic error in the estimated common parameters log10βqr . Fitness tests using regression diagnostics have proven the reliability of the parameter estimates.

Sign in / Sign up

Export Citation Format

Share Document