International Mathematical School ?Potential Theory? (Katsiveli, June 26 ?July 7, 1993)

1994 ◽  
Vol 46 (7) ◽  
pp. 1060-1062
Author(s):  
P. M. Tamrazov ◽  
A. V. Bondar ◽  
N. V. Zorii
Keyword(s):  
Potential Theory ◽  
Mathematical School ◽  
International Mathematical

Potential Theory and Right Processes

2004 ◽  
Author(s):  
Lucian Beznea ◽  
Nicu Boboc
Keyword(s):  
Potential Theory

Sorption of phenols on hexadecyltrimethylammonium- modified bentonite: Application of Polanyi−Manes potential theory

2020 ◽  
pp. 0958305X2097728
Author(s):  
Jiyeon Choi ◽  
Dong-Ik Slong ◽  
Won Sik Shin
Keyword(s):  
Molar Volume ◽  
Potential Theory ◽  
Characteristic Curve ◽  
Chemical Compositions ◽  
Pore Filling ◽  
Sorption Data ◽  
Similar Chemical ◽  
Competitive Model ◽  
Sorption Potential ◽  
Sorption Systems

This study investigated the sorption of phenol and 4-chlorophenol (4-CP) on natural bentonite modified with hexadecyltrimethylammonium (HDTMA) cation. The Freundlich, Langmuir, Dubinin−Radushkevich (DR), Sips, and Polanyi−Dubinin−Manes (PDM) models fitted the sorption data well (R2 > 0.92). The Freundlich coefficient and the maximum sorbed amount of the Langmuir and PDM models of 4-CP were higher than phenol because of higher hydrophobicity (log Kow = 2.39 for 4-CP and 1.46 for phenol). The PDM model that includes solubility and molar volume was highly useful in predicting the sorption of phenols having widely different hydrophobicity and solubility. The characteristic curves, the plot of sorbed volume ( qv) versus the sorption potential per molar volume ( ε/ Vm) of 4-CP and phenol were distinctly different although they have similar chemical compositions. The selectivity of 4-CP (3.72) was higher than that of phenol (0.27) in binary sorption systems. The sorbed volume ( qv) in the binary sorption was remarkably reduced and the characteristic curve had wider distribution owing to competition in pore-filling. The sorption behaviors were elucidated by partitioning and pore-filling mechanisms. Among the tested binary sorption models, the modified Langmuir competitive model was the best in the prediction of the binary sorption (R2 > 0.98).

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