Name: Chemically Based Models to Predict Distribution Coefficients of Metals (en Inglés)
Price: 1539.13 MXN
Availability: InStock
Author: Elhassadi, Abdulmonem
ISBN: 9786138826194

Envío gratis

portada Chemically Based Models to Predict Distribution Coefficients of Metals (en Inglés)

Formato

Libro Físico

Autor

Abdulmonem Elhassadi

Editorial

Scholars' Press

Idioma

Inglés

N° páginas

132

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.8 cm

Peso

0.20 kg.

ISBN13

9786138826194

Categorías

Química industrial e ingeniería química

Chemically Based Models to Predict Distribution Coefficients of Metals (en Inglés)

Abdulmonem Elhassadi (Autor) · Scholars' Press · Tapa Blanda

Libro Nuevo

$ 1,539.13

$ 2,798.41

Ahorras: $ 1,259.29

45% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Lunes 05 de Agosto y el Viernes 16 de Agosto.

Lo recibirás en cualquier lugar de México entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Chemically Based Models to Predict Distribution Coefficients of Metals (en Inglés)"

Chemically Based Models are derived for copper (II) and zinc (II) chloride tri-n-octylamine extraction single and binary systems. The predictive model makes use of the aqueous phase metal chloride complexes stability constants, their extraction mechanism, and the equilibrium constant for the extraction reaction. The distribution coefficients of the metals can be predicted by the equation D=K(alpha)(phi square), where phi is the product of the equilibrated organic concentration and the chloride ion concentration in the aqueous phase, K is the effective equilibrium constant containing the quotient of the activity coefficients of the reacting species and alpha is the degree of formation of the free metal ion in the equilibrated aqueous phase. Excellent agreement between experimental data and predicted values was obtained.The multi-component, binary metal extraction is examined in a quantitative manner. The separation factor can be predicted by the ration of distribution coefficients. This model was based on the assumption of constant activity coefficients. The experimental results show that the data fit the binary model very well.