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It has been shown that chromium(III) and nitrilotriacetic acid (NTA; H3Z) form only a series of 1:1 complexes in solution. The violet uncharged species [CrZ(H2O)2] cannot be extracted by a solution of the long-chain quaternary ammonium chloride, Aliquat-336, in dichloroethane. Its acid dissociation constant (pK1 = 5.87) was determined spectrophotometrically. On increasing the pH of the solution the blue anion CrZ(H2O)(OH)- of pK2=8.74 and its conjugate base the binegative anion CrZ(OH)2-2 of pK3= 11.81 are successively formed. Both of these anionic species are extracted by Aliquat-336 with maximal extraction (ca. 60%) at about pH 9. At still higher pH values the olive-green anion, CrZ(OH)33-of much lower or negligible extractability, is formed.  相似文献   
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Formation of the charge-transfer complexes between various calix[4]crowns (1-4) and [60]fullerene were studied in toluene solution using UV-vis spectrophotometry. The stability constants and the thermodynamic data of the resulting 1:1 complexes were determined and were found to decrease with increasing the size of the crown moiety of the calixcrown. Except the complex of 3, all the complexes were found to be enthalpy stabilized but disfavored in terms of entropy.  相似文献   
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The extraction of anionic complexes of EDTA with Ca. Mg, V(IV), V(V), Cr(III), Mn(II), Mn(III), Fe(III), Co(II), Co(III), Ni, Cu(II), Zn, Cd, Hg(II), Pd(II), Pb and Bi by solutions of Aliquat-336 chloride in 1,2-dichloroethane has been studied as a function of the pH of the aqueous phase. The order and extent of the extractability varies greatly with the pH and provides a number of new possibilities for separation procedures. Thus iron(III) can be separated from many other metals in strongly alkaline solution while the extraction of V(V), V(IV), Hg(II) and Pd(II) exceeds 99% over wide pH ranges. The complex of Mn(III) with EDTA which is very unstable in aqueous solution can be preserved for up to 5 h when extracted by Aliquat-336.One of us (R. H. A1-J.) wishes to thank the Ministry of Oil of the Republic of Iraq for financial support.  相似文献   
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In this work a novel adaptive neuro-fuzzy inference system model has been developed for the prediction of the intrinsic mechanical properties of various cellulosic natural fibers to enhance their selection for better green composite materials. The model combined modeling function of the fuzzy inference system with the learning capability of the artificial neural network. The developed model was built up based on experimental mechanical properties of various cellulosic fiber types commonly used for natural fiber reinforced composites, and the rules have been generated directly from the experimental data. The developed model was capable of predicting all of Young's modulus, ultimate tensile strength, and elongation at break properties from only two intrinsic properties of fibers namely; cellulose and moisture content. The adaptive neural fuzzy inference system (ANFIS) structure included five layers to realize the establishment and calculation of each model. The system architecture included the fuzzy input layer, product layer, normalized layer, de-fuzzy layer and total output layer. Results have been revealed that the model’s predictions were highly in agreement with other experimentally gained properties when compared with experimental results for verifying the approach. The accuracy of the developed model would enhance predicting other cellulosic fiber properties to develop better natural fiber composites in the near future.

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