Metal-humate interactions. 1. Discrete ligand and continuous distribution models

Dzombak, David A.; Fish, William; Morel, François M. M.

doi:10.1021/es00149a004

Cited by 187 publications

(70 citation statements)

References 30 publications

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“…Analytical expressions of the CAS underlying NICA isotherm have been reported as well as expressions for the dependence of the main parameters of this distribution (average and variance) with respect to pH Rey-Castro et al, 2009). Notice that the use of the analytical expressions of the CAS underlying NICA overcomes the limitations due to the possible presence of artefacts in the CAS obtained by direct numerical inversion of experimental binding data (Dzombak et al, 1986;Merz, 1980;Vos and Koopal, 1985).…”

Section: Conditional Affinity Spectra At Constant Total Metal Concentmentioning

confidence: 99%

Competition effects in cation binding to humic acid: Conditional affinity spectra for fixed total metal concentration conditions

David

Mongin

Rey-Castro

et al. 2010

Geochimica et Cosmochimica Acta

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Section: Conditional Affinity Spectra At Constant Total Metal Concentmentioning

confidence: 99%

Competition effects in cation binding to humic acid: Conditional affinity spectra for fixed total metal concentration conditions

David

Mongin

Rey-Castro

et al. 2010

Geochimica et Cosmochimica Acta

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“…For an interpretation of the metal binding of HSs, several mathematical models have been proposed. [4][5][6] In the discrete-site model [7][8][9][10][11] , the presence of independent binding sites with various stability is assumed as in the humic molecule. A typical example of this interpretation is the Scatchard-plot method.…”

mentioning

confidence: 99%

“…7,10,11 Moreover, the continuous-site distribution models [12][13][14][15] , in which the stability of metal binding sites is assumed to distribute continuously, have been used in interpreting the metal binding equilibria of heterogeneous polyelectrolytes, such as proteins and HSs. The discrete-site models cannot always represent the actual binding manner 4,6 , whereas the continuous-site distribution models reflect the actual distribution of the stability of the metal binding sites in the humic molecule. The continuous-site distribution models therefore can represent the heterogeneous character of HSs better than the discrete models.…”

mentioning

confidence: 99%

Evaluation of Copper(II) Binding Abilities of Humic Substances by a Continuous Site-Distribution Model Considering Proton Competition

et al. 1999

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“…13,14 This treatment assumes a discrete site model 14,15 which allows the determination of the stoichiometry and pKa of the ionizable sites on the surface of the Spirulina cells. 13 …”

Section: Proton Binding Characterizationmentioning

confidence: 99%

Evaluating Scatchard and Differential Equilibrium Functions to study the binding properties of Cu(II) to the surface of mixed species of lyophilized Spirulina (Cyanobacteria)

Parmeggiani

Masini

2003

J. Braz. Chem. Soc.

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A ligação de Cu(II) à superfície de espécies mistas da microalga Spirulina foi estudada em pH 6.0 por titulação potenciométrica monitorada com eletrodo íon-seletivo para Cu(II). Três materiais foram estudados: a suspensão completa da alga, a água de lavagem obtida por centrifugação da suspensão completa e a suspensão composta por células lavadas com água. Os métodos de Scatchard e de Funções Diferenciais de Equilíbrio (DEF) foram usados para tratamento dos dados de titulação. Os gráficos de Scatchard possibilitaram a determinação de duas classes de sítios de complexação, sendo que os valores de log K' para os sítios mais fortes variaram entre 7,3 e 7,9. Para os sítios mais fracos os valores de log K' foram determinados entre 3,5 e 3,9. As concentrações totais dos sítios de complexação foram 1,6±0,1; 1,5±0,5 e 0,92±0,08 mmol g -1 para a suspensão total, água de lavagem e células lavadas, respectivamente. O método DEF revelou uma variação linear dos valores de log K DEF em função do log θ (θ = grau de ocupação dos sítios de complexação), sendo que os valores de log K DEF decresceram de 9 para 4 em conseqüência do aumento de log θ de -2,5 para -0,25. Os graus de heterogeneidade determinados por DEF ficaram na faixa entre 0,4 e 0,5 para os três materiais estudados.The binding of Cu(II) to the surface of mixed species of Spirulina was studied at pH 6.0 by potentiometric titration monitored with a copper ion selective electrode. Three materials were studied: the total suspension of alga, the washing water that resulted from centrifugation of the total suspension, and the water-washed cells. The Scatchard method and the Differential Equilibrium Functions (DEF) were used for the treatment of the titration data. The Scatchard plots determined two classes of binding sites, with log K' values for stronger sites varying between 7.3 and 7.9. For the weaker sites the log K' values ranged between 3.5 and 3.9. The total concentration of binding sites were 1.6±0.1, 1.5±0.5 and 0.92±0.08 mmol g -1 for the total suspension, washing water, and washed cells, respectively. The DEF approach revealed a linear variation of log K DEF as a function of log θ (θ = degree of site occupation), with log K DEF decreasing from 9 to 4 as a consequence of increasing log θ from -2.5 to -0.25. The degree of site heterogeneity determined by the DEF approach was between 0.4 and 0.5 for the three materials studied.

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Metal-humate interactions. 1. Discrete ligand and continuous distribution models

Cited by 187 publications

References 30 publications

Competition effects in cation binding to humic acid: Conditional affinity spectra for fixed total metal concentration conditions

Competition effects in cation binding to humic acid: Conditional affinity spectra for fixed total metal concentration conditions

Evaluation of Copper(II) Binding Abilities of Humic Substances by a Continuous Site-Distribution Model Considering Proton Competition

Evaluating Scatchard and Differential Equilibrium Functions to study the binding properties of Cu(II) to the surface of mixed species of lyophilized Spirulina (Cyanobacteria)

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