Extraction of Cu2+ Ions from Aqueous Solutions of Bromide Ions using 1-Phenyl-3-Methyl-4-Trichloroacetylpyrazolone-5 and Molecular Modeling of the Complex

Chukwu      U. John; Uzoukwu      B. Augustus

Abstract

Extraction of Cu2+ , Co2+ and Ni2+ ions from aqueous solutions of bromide ion using 1-phenyl-3-methyl-4- trichloroacetylpyrazolone-5 (HTcP) in benzene and hexane organic medium has been studied. From the results, extraction of Co2+ and Ni2+ ions was masked by anionic complexes of the bromide ions throughout the pH range of 0 - 6. Cu2+ ions were quantitatively extracted from aqueous solutions of bromide ions, thereby presenting a technique for the efficient separation of Cu2+ ions from Co2+ and Ni2+ ions. Increase in bromide ion concentration from 0.05 to 0.3M had a salting out effect on the extraction of Cu2+ ions from 97.44% to 98.79% in benzene/HTcP medium and 97.13% to 98.33% in hexane/ HTcP. On application of statistical treatment using slope analysis, the values of pH1/2, log Kex and log Kd have been calculated and presented. Hence, the complex formed is Cu(TcP)2. Generally, extraction of Cu2+ ions was found to be more efficient in hexane/HTcP at relatively lower pH value in comparison to extraction into benzene/HTcP, while optimal percentage yield was slightly higher in benzene/HTcP than hexane/HTcP solution. This can be attributed to the lower dielectric constants of hexane (2.02) and lower dipole moment in comparison to that of benzene (2.28). Finally, molecular modeling shows that the stable structure of the ligand derivative (HTcP) was quite different in orientation from the parent ligand (1-phenyl-3-methyl-4-acetylpyrazolone-5 HPMAP) and has been attributed to the bulky nature of the trichloro unit. This has been discussed in line with relevant patents.

Keywords: Bromide ion, molecular modeling, 1-phenyl-3-methyl-4-trichloroacetylpyrazolone-5, slope analysis, Buffer Solutions, Extraction plots, Molecular Modeling Computation, hexane organic medium, modelled ligand derivative, HyperChem molecular modelling computation DFT