Surface ionization and complexation models: A comparison of methods for determining model parameters

Koopal, L.K.; Riemsdijk, W.H. van; Roffey, Michael G.

doi:10.1016/0021-9797(87)90441-3

Cited by 103 publications

(41 citation statements)

References 22 publications

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“…In all sampies, the calculated % values as a function of pH and electrolyte concentration show better agreement with the experimental data than the calculated "I'd values do with f measurements, particularly at the higher ionic strength of 0.01 mol dm 3. Koopal et al (1987) found similar results. This could have two causes.…”

Section: Cr O = B([soh~-] + [Sohf -No~-] -[So-] -[So--k+]) (13) R K +supporting

confidence: 62%

The Effect of Surface Modification by an Organosilane on the Electrochemical Properties of Kaolinite

Braggs

Fornasiero

Ralston

et al. 1994

Clays and clay miner.

104

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Abstract--The electrochemical properties of kaolinite before and after modification with chlorodimethyloctadecylsilane have been studied by electrophoretic mobility, surface charge titration, and extrapolated yield stress measurements as a function of pH and ionic strength. A heteropolar model of kaolinite, which views the particles as having a pH-independent permanent negative charge on the basal planes and a pHdependent charge on the edges, has been used to model the data. The zeta potential and surface charge titration experimental data have been used simultaneously to calculate acid and ion complexation equilibrium constants using a surface complex model of the oxide-solution interface. The experimental data were modeled following subtraction of the basal plane constant negative charge, describing only the edge electrical double layer properties. Extrapolated yield stress measurements along with the electrochemical data were used to determine the edge isoelectric points for both the unmodified and modified kaolinite and were found to occur at pH values of 5.25 and 6.75, respectively. Acidity and ion complexation constants were calculated for both sets of data before and after surface modification. The acidity constants, pKat = 5.0 and pKa2 = 6.0, calculated for unmodified kaolinite, correlate closely with acidity constants determined by oxide studies for acidic sites on alumina and silica, respectively, and were, therefore, assigned to pH-dependent specific chemical surface hydroxyl groups on the edges of kaolinite. The parameters calculated for the modified kaolinite indicate that the silane has reacted with these pHdependent hydroxyl groups causing both a change in their acidity and a concomitant decrease in their ionization capacity. Infrared data show that the long chain hydrocarbon silane is held by strong bonding to the kaolinite surface as it remains attached after washing with cyclohexane, heating, and dispersion in an aqueous environment.

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Section: Cr O = B([soh~-] + [Sohf -No~-] -[So-] -[So--k+]) (13) R K +supporting

confidence: 62%

The Effect of Surface Modification by an Organosilane on the Electrochemical Properties of Kaolinite

Braggs

Fornasiero

Ralston

et al. 1994

Clays and clay miner.

104

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“…Titration data for three hydrous oxides, o~-FeOOH, ce-A1203, and TiO2, are used in this analysis of the SCM approach. This work expands upon earlier studies (7)(8)(9) of model parameter estimation from titration data, generalizing previous conclusions for a wider range of conditions and systems, and quantifies, for the first time, the range of parameter values that can be used to fit titration data for three different and widely used SCMs.…”

Section: -9797/91 $300mentioning

confidence: 72%

“…However, the subjective assumptions inherent in the extrapolation methods as described above remain when one attempts to obtain capacitance values from the slopes of data plotted according to Eqs. [ 17 ]- [ 20 ] (8). Hence, C1 should be considered a fitting parameter.…”

Section: Model Parameter Estimationmentioning

confidence: 99%

“…[ 20 ] or [ 21 ] results in the so-called double extrapolation value for the TLM surface constants ( 16,25,26). At present, we feel the extrapolation procedures cannot be used conveniently to produce a unique set of surface constants since, (i) there are no objective methods to determine which range of titration data should be used in the extrapolations, (ii) there is no basis for choosing the form of the extrapolation, e.g., linear versus polynomialfit extrapolation of the data, and (iii) the extrapolation methods ensure that a large difference in the protolysis constants (large ApKA) will be found for all SCMs (8,(27)(28)(29)(30)(31). In the case of the TLM, where a wide range of ApKA values may fit the titration data equally well, these limitations make it especially difficult to use the graphical extrapolation techniques to arrive at a unique set of parameter values.…”

Section: Model Parameter Estimationmentioning

confidence: 99%

“…[2], [3] versus [9], [10] to the observed titration behavior modeled by Eq. [8 ]. One possible method of distinguishing the relative contribution would be to directly measure electrolyte sorption as a function of changing electrolyte concentration and pH.…”

Section: Model Parameter Estimationmentioning

confidence: 99%

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Surface complexation models: An evaluation of model parameter estimation using FITEQL and oxide mineral titration data

Hayes

Redden

Ela

et al. 1991

Journal of Colloid and Interface Science

394

266

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The ability of surface complexation models (SCMs) to fit sets of titration data as a function of changes in model parameters was evaluated using FITEQL and acid-base titration data of a-FeOOH, a-AlzO3, and TiO2. Three SCMs were evaluated: the triple-layer model (TLM), the constant capacitance model (CCM), and the diffuse-layer model (DLM). For all models evaluated, increasing the model input value for the total number of surface sites caused a decrease in the best-fit Log K values of the surface protolysis constants. In the case of the CCM, the best-fit surface protolysis constants were relatively insensitive to changes in the value of the capacitance fitting parameter, G, particularly for values of C1 greater than 1.2 F/m 2. Similarly, the best-fit values of TLM surface electrolyte binding constants were less influenced by changes in the value of C~ when C~ was greater than 1.2 F/m 2. For a given C1 value, the best-fit TLM values of the electrolyte binding constants were sensitive to changes in ApK, up to ApKa values of 3. For ApKa values above 3, no changes in the best-fit electrolyte binding constants were observed. Effects of the quality and extent of titration data on the best-fit values for surface constants are discussed for each model. A method is suggested for choosing a unique set of parameter values for each of the models.

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Colloids

Lagaly¹

2000

Ullmann's Encyclopedia of Industrial Chemistry

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Surface ionization and complexation models: A comparison of methods for determining model parameters

Cited by 103 publications

References 22 publications

The Effect of Surface Modification by an Organosilane on the Electrochemical Properties of Kaolinite

The Effect of Surface Modification by an Organosilane on the Electrochemical Properties of Kaolinite

Surface complexation models: An evaluation of model parameter estimation using FITEQL and oxide mineral titration data

Colloids

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