New Polymer Inclusion Membrane in the Separation of Nonferrous Metal Ion from Aqueous Solutions

The new polymer inclusion membrane (PIM) with ethylenediamine-bis-acetylacetone (EDAB-acac) matrix was used for the separation of Zn(II) solutions containing non-ferrous metal ions (Co(II), Ni(II) Cu(II), Cd(II)). The effective conditions for carrying out transport studies by PIMs were determined on the basis of solvent extraction studies. The values of the stability constants and partition coefficients of M(II)-EDAB-acac complexes were determined from the extraction studies. The stability constants increase in series Ni(II) < Cu(II) < Co(II) < Cd(II) < Zn(II), and their logarithms are 8.85, 10.61, 12.73, 14.50, and 16.84, respectively. The transport selectivity of the PIMs were: Zn(II) > Cd(II) > Co(II) > Cu(II) > Ni(II). The established stability constants of the complexes also decrease in this order. The values of three parameters: initial flux, selectivity coefficient, and recovery factor of a given metal after 12 h were selected for the comparative analysis of the transport process. The highest values of the initial fluxes were received for Zn(II), Cd(II), and Co(II). They are, depending on the composition of the mixture, in the range 9.87–10.53 µmol/m2, 5.26–5.61 µmol/m2, and 7.43–7.84 µmol/m2 for Zn(II), Co(II), and Cd(II), respectively. The highest recovery factors were observed for Zn(II) ions (90–98.0%). For Cd, Co and Cu, the recovery factors are high and are within the range 76–83%, 64–79%, and 51–66%, respectively.

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New Polymer Inclusion Membranes in the Separation of Palladium, Zinc and Nickel Ions from Aqueous Solutions

Polymers ◽

10.3390/polym13091424 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1424

Author(s):

Elżbieta Radzyminska-Lenarcik ◽

Ilona Pyszka ◽

Wlodzimierz Urbaniak

Keyword(s):

Metal Ion ◽

Membrane Surface ◽

Nickel Ions ◽

Selectivity Coefficients ◽

Transport Studies ◽

Aqueous Chloride ◽

Metal Ion Transport ◽

The Stability ◽

Kinetics Of ◽

Effective Conditions

The new polymer inclusion membrane (PIM) with a 1-alkyltriazole matrix was used to separate palladium(II) ions from aqueous chloride solutions containing a mixture of Zn-Pd-Ni ions. The effective conditions for transport studies by PIMs were determined based on solvent extraction (SX) studies. Furthermore, the values of the stability constants and partition coefficients of M(II)-alkyltriazole complexes were determined. The values of both constants increase with the growing hydrophobicity of the 1-alkyltriazole molecule and have the highest values for the Pd(II) complexes. The initial fluxes, selectivity coefficients, and recovery factors values of for Pd, Zn and Ni were determined on the basis of membrane transport studies. The transport selectivity of PIMs were: Pd(II) > Zn(II) > Ni(II). The initial metal ion fluxes for all the cations increased with the elongation of the alkyl chain in the 1-alkyltriazole, but the selectivity coefficients decreased. The highest values of the initial fluxes at pH = 4.0 were found for Pd(II) ions. The best selectivity coefficients Pd(II)/Zn(II) and Pd(II)/Ni(II) equal to 4.0 and 13.4, respectively, were found for 1-pentyl-triazole. It was shown that the microstructure of the polymer membrane surface influences the kinetics of metal ion transport. Based on the conducted research, it was shown that the new PIMs with 1-alkyltriazole can be successfully used in an acidic medium to separate a mixture containing Pd(II), Zn(II) and Ni(II) ions.

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Transferrin binding of Al3+ and Fe3+.

Clinical Chemistry ◽

10.1093/clinchem/33.3.405 ◽

1987 ◽

Vol 33 (3) ◽

pp. 405-407 ◽

Cited By ~ 138

Author(s):

R B Martin ◽

J Savory ◽

S Brown ◽

R L Bertholf ◽

M R Wills

Keyword(s):

Stability Constant ◽

Blood Plasma ◽

Stability Constants ◽

Metal Ion ◽

Equilibrium Dialysis ◽

Ion Binding ◽

Metal Ion Binding ◽

Quantitative Studies ◽

Intensity Changes ◽

The Stability

Abstract An understanding of Al3+-induced diseases requires identification of the blood carrier of Al3+ to the tissues where Al3+ exerts a toxic action. Quantitative studies demonstrate that the protein transferrin (iron-free) is the strongest Al3+ binder in blood plasma. Under plasma conditions of pH 7.4 and [HCO3-]27 mmol/L, the successive stability constant values for Al3+ binding to transferrin are log K1 = 12.9 and log K2 = 12.3. When the concentration of total Al3+ in plasma is 1 mumol/L, the free Al3+ concentration permitted by transferrin is 10(-14.6) mol/L, less than that allowed by insoluble Al(OH)3, by Al(OH)2H2PO4, or by complexing with citrate. Thus transferrin is the ultimate carrier of Al3+ in the blood. We also used intensity changes produced by metal ion binding to determine the stability constants for Fe3+ binding to transferrin: log K1 = 22.7 and log K2 = 22.1. These constants agree closely with a revision of the reported values obtained by equilibrium dialysis. By comparison with Fe3+ binding, the Al3+ stability constants are weaker than expected; this suggests that the significantly smaller Al3+ ions cannot coordinate to all the transferrin donor atoms available to Fe3+.

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Reduced graphene oxide based a novel polymer inclusion membrane: Transport studies of Cr(VI)

Journal of Molecular Liquids ◽

10.1016/j.molliq.2016.04.023 ◽

2016 ◽

Vol 219 ◽

pp. 1124-1130 ◽

Cited By ~ 23

Author(s):

Ahmet Kaya ◽

Canan Onac ◽

H.Korkmaz Alpoğuz ◽

Shilpi Agarwal ◽

Vinod Kumar Gupta ◽

...

Keyword(s):

Graphene Oxide ◽

Membrane Transport ◽

Reduced Graphene Oxide ◽

Inclusion Membrane ◽

Polymer Inclusion Membrane ◽

Transport Studies ◽

Reduced Graphene

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The affinity of aldehydic compounds to complex formation. Nickel(II) and cobalt(II) complexes with 2-pyridinecarboxaldehyde

Canadian Journal of Chemistry ◽

10.1139/v77-362 ◽

1977 ◽

Vol 55 (14) ◽

pp. 2613-2619 ◽

Cited By ~ 3

Author(s):

M. S. El-Ezaby ◽

M. A. El-Dessouky ◽

N. M. Shuaib

Keyword(s):

Complex Formation ◽

Aqueous Solutions ◽

Stability Constants ◽

Metal Ion ◽

Experimental Conditions ◽

Complex Species ◽

Spectrophotometric Methods ◽

Complex Equilibria ◽

The Stability ◽

Hydroxy Groups

The interactions of Ni(II) and Co(II) with 2-pyridinecarboxaldehyde have been investigated in aqueous solutions at μ = 0.10 M (KNO3) at 30 °C. The stability constants of different complex equilibria have been determined using potentiometric methods. Spectrophotometric methods were also used in the case of the nickel(II) – 2-pyridinecarboxaldehyde system. It was concluded that nickel(II) and cobalt(II), analogous to copper(II), enhance hyrdation of 2-pyridinecarboxaldehyde prior to deprotonation of one of the geminal hydroxy groups. Complex species of 1:1 as well as 1:2 metal ion to ligand composition exist under the experimental conditions used.

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Interaction of Ampicillin and Amoxicillin with Mn2+: A Speciation Study in Aqueous Solution

Molecules ◽

10.3390/molecules25143110 ◽

2020 ◽

Vol 25 (14) ◽

pp. 3110

Author(s):

Claudia Foti ◽

Ottavia Giuffrè

Keyword(s):

Aqueous Solution ◽

Stability Constants ◽

Metal Ion ◽

Formation Constants ◽

Enthalpy Change ◽

Ligand Concentration ◽

Empirical Parameter ◽

Speciation Study ◽

Potentiometric Measurements ◽

The Stability

A potentiometric and UV spectrophotometric investigation on Mn2+-ampicillin and Mn2+-amoxicillin systems in NaCl aqueous solution is reported. The potentiometric measurements were carried out under different conditions of temperature (15 ≤ t/°C ≤ 37). The obtained speciation pattern includes two species for both the investigated systems. More in detail, for system containing ampicillin MLH and ML species, for that containing amoxicillin, MLH2 and MLH ones. The spectrophotometric findings have fully confirmed the results obtained by potentiometry for both the systems, in terms of speciation models as well as the stability constants of the formed species. Enthalpy change values were calculated via the dependence of formation constants of the species on temperature. The sequestering ability of ampicillin and amoxicillin towards Mn2+ was also evaluated under different conditions of pH and temperature via pL0.5 empirical parameter (i.e., cologarithm of the ligand concentration required to sequester 50% of the metal ion present in traces).

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Solid^|^#8211;Liquid Extraction and Transport of Metal Ion with the Polymer Inclusion Membrane Using a New Alkylated Pyrrolidinecarboxylic Acid

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN ◽

10.1252/jcej.11we264 ◽

2012 ◽

Vol 45 (10) ◽

pp. 816-822 ◽

Cited By ~ 7

Author(s):

Shintaro Kanemaru ◽

Tatsuya Oshima ◽

Yoshinari Baba

Keyword(s):

Metal Ion ◽

Liquid Extraction ◽

Inclusion Membrane ◽

Polymer Inclusion Membrane

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Predicting the Stability Constants of Metal-Ion Complexes from First Principles

Inorganic Chemistry ◽

10.1021/ic401037x ◽

2013 ◽

Vol 52 (18) ◽

pp. 10347-10355 ◽

Cited By ~ 36

Author(s):

Ondrej Gutten ◽

Lubomír Rulíšek

Keyword(s):

Stability Constants ◽

First Principles ◽

Metal Ion ◽

Metal Ion Complexes ◽

The Stability

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IN SILICO MODEL QSPR FOR PREDICTION OF STABILITY CONSTANTS OF METAL-THIOSEMICARBAZONE COMPLEXES

HUE UNIVERSITY JOURNAL OF SCIENCE NATURAL SCIENCE ◽

10.26459/hueuni-jns.v127i1a.4791 ◽

2018 ◽

Vol 127 (1A) ◽

pp. 67

Author(s):

Nguyen Minh Quang ◽

Tran Xuan Mau ◽

Pham Van Tat ◽

Tran Nguyen Minh An ◽

Vo Thanh Cong

Keyword(s):

Neural Network ◽

Stability Constants ◽

In Silico ◽

Metal Ion ◽

Test Group ◽

Structure And Property ◽

The Neural Network ◽

Complex Solutions ◽

Artificial Neural Network Ann ◽

The Stability

In the present work, the stability constants logb11 and the concentration of metal ion and thiosemicarbazone in complex solutions were determined by using in silico models. The 2D, 3D, physicochemical and quantum descriptors of complexes were generated from the molecular geometric structure and semi-empirical quantum calculation PM7 and PM7/sparkle. The quantitative structure and property relationships (QSPRs) were constructed by using the ordinary linear regression (OLR) and artificial neural network (ANN). The best linear model QSPROLR (with k of 6) involved descriptors k0, core-core repulsion, xp5, xch5, valence, and SHHBd. The quality of model QSPROLR had the statistical values: R2train = 0.898, R2adj = 0.889, Q2LOO = 0.846, MSE = 1.136, and Fstat = 91.348. The neural network model QSPRANN with architecture I(6)-HL(6)-O(1) had the statistical values: R2train = 0.9768, and Q2LOO = 0.8687. The predictability of QSPR models for complexes of the test group turned out to be in good agreement with those from the experimental data in the literature.

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