Structure-property relationship studies

Chen, J., Quan, X., Yan, Y., Yang, F., Peijnenburg, W.J.G.M. (2001) Quantitative structure-property relationship studies on direct photolysis of selected polycyclic aromatic hydrocarbons in atmospheric aerosol. Chemosphere 42, 263-270. 

Z. Chen, N.H.S. Lee, W. Huang, Y. Xu, and Y. Cao, New phenyl-substituted PPY derivatives for polymer light-emitting diodes — synthesis, characterization and structure-property relationship study, Macromolecules, 36 1009-1020, 2003. 

SW Yin, Z Shuai, and Y Wang, A quantitative structure-property relationship study of the glass transition temperature of OLED materials, J. Chem. Inf. Comput. Sci., 43 970-977, 2003. 

To verify such a steric effect a quantitative structure-property relationship study (QSPR) on a series of distinct solute-selector pairs, namely various DNB-amino acid/quinine carbamate CSPpairs with different carbamate residues (Rso) and distinct amino acid residues (Rsa), has been set up [59], To provide a quantitative measure of the effect of the steric bulkiness on the separation factors within this solute-selector series, a-values were correlated by multiple linear and nonlinear regression analysis with the Taft s steric parameter Es that represents a quantitative estimation of the steric bulkiness of a substituent (Note s,sa indicates the independent variable describing the bulkiness of the amino acid residue and i s.so that of the carbamate residue). For example, the steric bulkiness increases in the order methyl < ethyl < n-propyl < n-butyl < i-propyl < cyclohexyl < -butyl < iec.-butyl < t-butyl < 1-adamantyl < phenyl < trityl and simultaneously, the s drops from -1.24 to -6.03. In other words, the smaller the Es, the more bulky is the substituent. The obtained QSPR equation reads as follows ... 

Gao J, Xu J, Chen B et al. (2007) A quantitative structure-property relationship study for refractive indices of conjugated polymers. J Mol Model 13 573-578... 

Stanton, D. T. and Jurs, P. C. (1990) Development and use of charged partial surface area structural descriptors in computer-assisted quantitative structure-property relationship studies. Anal. Chem. 62, 2323-2329. 

Tetko, I.V. Solov ev, V.P Antonov, A.V. Yao, X.J. Fan, B.T. Hoonakker, F. Fourches, D. Lachiche, N. Varnek, A. Benchmarking of linear and non-linear approaches for quantitative structure-property relationship studies of metal complexation with organic ligands. J. Chem. Inf. Model. 2006, 46 (2), 808-819. 

Partial Surface Area Structural Descriptors in Computer-Assisted Quantitative Structure-Property Relationship Studies. 

QSRR are derived statistically. To get reliable statistics one needs a large amount of appropriate data. The great advantage of QSRR analysis over other quantitative structure-property relationship studies is that chromatography can readily produce a laige amount of relatively precise and reproducible data. In addition, in a chromatographic process all conditions may be kept constant and hence the structure of the analyte becomes the single independent variable in the system [12],... 

Zhao H., Chen J., Quan X., Yang F., and Peijnenburg W. J. G. M. (2(X)1) Quantitative structure-property relationship study on reductive dehalogenation of selected halogenated aliphatic hydrocarbons in sediment slurries. Chemosphere 44, 1557-1563. 

Chen, J., Feng, L., Liao, Y., Wang, L. and Hu, H. (1996). Using AMI Hamiltonian in Quantitative Structure-Properties Relationship Studies of Alkyl(l-Phenylsulfonyl)cycloalkane-Carboxy-lates. Chemosphere, 33, 537-546. 

Salo, M., Sama, S. and Vuorela, H. (1994). Statistical Evaluation of Molecular Descriptors and Quantitative Structure-Property Relationship Studies of Retinoids. J.Pharm.Biome Arud., 12, 867-874. 

Stanton, D.T. and Jurs, P.C. (1990). Development and Use of Charged Partial Surface Area Structural Descriptors in Computer-Assisted Quantitative Structure-Property Relationship Studies. Anal.Chem., 62,2323-2329. 

Stanton, D.T., Mattioni, B.E., Knittel, J.J. and Jurs, P.C. (2004) Development and use of hydrophobic surface area (HSA) descriptors for computer-assisted quantitative structure-activity and structure-property relationship studies. Journal of Chemical Information and Computer Sciences, 44, 1010-1023. 

A broad view of principal findings and processes utilized for the development of oriented polymer morphologies has been presented. New trends toward the advancement of this topic are being developed within the realm of multidisciplinary research. Studies of order development in polymers have—for a few years already—transcended beyond traditional disciplines in chemistry and engineering. Genetically engineered polymers, nanoparticles, self-assembled molecules, supercritical fluids, and hybrids are some of the few areas that are now an integral part of macromolecular structural property relationship studies. 

Amboni, D., de, M.C., da Silva Junkes, B., Yunes, R.A. and Heinzen, V.E.F. (2002b) Quantitative structure-property relationship study of chromatographic retention indices and normal boiling point for oxo compounds using the semi-empirical topological method. J. Mol. Struct. (Theochem), 586, 71-80. 

Fatemi, M.H. (2003) Quantitative structure-property relationship studies of migration index in microemulsion electrokinetic chromatography using artificial neural networks./. Chromat., 1002, 221-229. 

Li, Q., Chen, X. and Hu, Z. (2004) Quantitative structure-property relationship studies for estimating boiling points of alcohols using calculated molecular descriptors with radial basis function neural networks. Chemom. Intell. Lab. Syst., 72, 93-100. 

Menezes, F.A.S., Montanari, C.A. and Bruns, R.E. (2000) 3D-WH1M pattern recognition study for bisamidines. A structure-property relationship study./. Braz. Chem. Soc., 11, 393-397. 

Tamm, K., Fara, D.C., Katritzky, A.R., Burk, P. and Karelson, M. (2004) A quantitative structure-property relationship study of lithium cation basicities. /. Phys. Chem. A, 108, 4812-4818. 

Quantitative structure-property relationship study of GC retention indices for PCDFs by DFTand relative position of chlorine substitution. J. Mol. Struct. (Theochem), 724, 115-124. 

Structure-property relationship studies of bidentate phosphine-alkene ligands in the catalytic arylation of heterocycles were pursued with the synthesis of a... 

Because of the above discussed drawbacks of numerical methods, rapid nonnu-merical 2D-3D converters were recently developed. In general, they proceed from molecular topochemistry and produce a reasonable 3D geometry. The 3D models obtained can either be used directly for structure-property relationship studies or further refined by numerical methods. The concepts implemented in nonnumerical 2D-3D converters (or 2D-3D converters only, for brevity) are classified in Figure 3, similarly to the classification presented in Ref. 20. 

Zhou, P Tian, R Li, Z., Quantitative structure-property relationship studies for col-hsion cross sections of 579 singly protonated peptides based on a novel descriptor as molecular graph fingerprint (MoGF), Anal. Chim. Acta 2007, 597, 214—222. 

Therefore traditional systems cannot handle a given category of problems for very large databases due to time limitations. However, the exact solution of the problem is unavoidable in many important cases, e.g., to calculate statistical data for structure-property relationship studies on large databases. 

It must be emphasized that all samples involved in structure-property relationship studies should be thoroughly characterized in terms of molecular weights, average composition, molecular weight, and compositional and architectural uniformity [1]. A variety of characterization methods can and should be employed, as was done in the cases outhned above. Intermediate... 

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