Lattice Boltzmann study of hydrodynamic effects in lamellar ordering process of two-dimensional quenched block copolymers

By incorporating self-consistent field theory with lattice Boltzmann method, a model for polymer melts is proposed. Compared with models based on Ginzburg-Landau free energy, our model does not employ phenomenological free energies to describe systems and can consider the chain topological details of polymers. We use this model to study the effects of hydrodynamic interactions on the dynamics of microphase separation for block copolymers. In the early stage of phase separation, an exponential growth predicted by Cahn-Hilliard treatment is found. Simulation results also show that the effect of hydrodynamic interactions can be neglected in the early stage.

Defect evolution and hydrodynamic effects in lamellar ordering process of two-dimensional quenched block copolymers

The effects of hydrodynamic interactions on the lamellar ordering process for two-dimensional quenched block copolymers in the presence of extended defects and the topological defect evolutions in lamellar ordering process are numerically investigated by means of a model based on lattice Boltzmann method and self-consistent field theory. By observing the evolution of the average size of domains, it is found that the domain growth is faster with stronger hydrodynamic effects. The morphological patterns formed also appear different. To study the defect evolution, a defect density is defined and is used to explore the defect evolutions in lamellar ordering process. Our simulation results show that the hydrodynamics effects can reduce the density of defects. With our model, the relations between the Flory-Huggins interaction parameter chi, the length of the polymer chains N, and the defect evolutions are studied.

Polymer concentration, shear and stretch field effects on the surface morphology evolution during the spin-coating

Polymer concentration and shear and stretch field effects on the surface morphology evolution of three different kinds of polymers (polystyrene (PS), polybutadiene (PB) and polystyrene-b-polybutadiene-b-polystyrene (SBS)) during the spin-coating were investigated by means of atomic force microscopy (AFM). For PS and SBS, continuous film, net-like structure and particle structure were observed at different concentrations. For PB, net-like structures were not observed and continuous films and radial array of droplets emerged. Moreover, we compared surface morphology transitions on different substrate locations from the center to the edge. For PS, net-like structure, broken net-like structure and irregular array of particles were observed. For SBS, net-like structure, periodically orientated string-like structure and broken-line structure appeared. But for PB, flower-like holes in the continuous film, distorted stream-like structure and irregular distributions of droplets emerged. These different transitions of surface morphologies were discussed in terms of individual material property.

Study on QSPR of alcohols with a novel edge connectivity index F-m

A novel edge degree f(i) for heteroatom and multiple bonds in molecular graph is derived on the basis of the edge degree delta(e(r)). A novel edge connectivity index F-m is introduced. The multiple linear regression by using the edge connectivity index F-m and alcohol-type parameter delta, alcohol-distance parameter L can provide high-quality QSPR models for the normal boiling points (BPs), molar volumes (MVs), molar refraction (MRs), water solubility(log(1/S)) and octanol/water partition (logP) of alcohols with up to 17 non-hydrogen atoms. The results imply that these physical properties may be expressed as a liner combination of the edge connectivity index and alcohol-type parameter, 6, alcohol-distance parameter, L. For the models of the five properties, the correlation coefficient r and the standard errors are 0.9969,3.022; 0.9993, 1.504; 0.9992, 0.446; 0.9924,0.129 and 0.9973,0.123 for BPs, MVs, MRs, log(1/S) and logP, respectively. The cross-validation by using the leave-one-out method demonstrates the models to be highly reliable from the point of view of statistics.

Three-dimensional structural features and the toxicity of aminobenzenes and phenols

For a QSAR of the toxicity of aminobenzenes in environment and their structures, the projection areas of the molecules in 3D space were calculated. The combinations of the projection areas and quantum chemical as well as topological parameters were performed for the methods of regression analysis and neural network, and much better results than that by using CoMFA were achieved.

Correlation analysis of the structures and stability constants of gadolinium(III) complexes

To simplify the abstraction of descriptors, for the correlation analysis of the stability constants of gadolinium(III) complexes and their ligand structures, aiming at gadolinium(III) complexes, we only considered the ligands and ignored the common parts of the structures, i.e., the metal ions. Quantum-chemical descriptors and topological indices were calculated to describe the structures of the ligands. Multiple regression analysis and neural networks were applied to construct the models between the ligands and the stability constants of gadolinium(III) complexes and satisfactory results were obtained.

Graphical representation and the similarity of DNA primary sequences

In this article, graphical representations of DNA primary sequences were generated. Topological indices and molecular connectivity indices were calculated and used for the comparison of similarities among eight different DNA segments. The satisfactory results were achieved by this analysis.

Polydispersity of ethylene sequence length in metallocene ethylene/alpha-olefin copolymers. II. Influence on crystallization and melting behavior

In this work, crystallization and melting behavior of metallocene ethylene/alpha-olefin copolymers were investigated by differential scanning calorimetry (DSC) and atomic force microscopy (AFM). The results indicated that the crystallization and melting temperatures for all the samples were directly related to the long ethylene sequences instead of the average sequence length (ASL), whereas the crystallization enthalpy and crystallinity were directly related to ASL, that is, both parameters decreased with a decreasing ASL. Multiple melting peaks were analyzed by thermal analysis. Three phenomena contributed to the multiple melting behaviors after isothermal crystallization, that is, the melting of crystals formed during quenching, the melting-recrystallization process, and the coexistence of different crystal morphologies. Two types of crystal morphologies could coexist in samples having a high comonomer content after isothermal crystallization. They were the chain-folded lamellae formed by long ethylene sequences and the bundlelike crystals formed by short ethylene sequences. The coexistence phenomenon was further proved by the AFM morphological observation.

The study on automorphism group of ESESOC

It is necessary to generate the automorphism group of a chemical graph in computer-aided structure elucidation. In this paper, an algorithm was developed by the all-paths topological symmetry algorithm to build the automorphism group of a chemical graph. A comparison of several topological symmetry algorithms reveals that the all-paths algorithm (APA) could yield the correct class of a chemical graph. It lays a foundation for the ESESOC system in computer-aided structure elucidation.

Prediction of molar absorptivities of color reagents and their color reactions with yttrium by artificial neural networks

The new topological indices A(x1)-A(x3) suggested in our laboratories were applied to the study of structure-property relationships between color reagents and their color reactions with yttrium. The topological indices of twenty asymmetrical phosphone bisazo derivatives of chromotropic acid were calculated. The work shows that QSPR can be used as a novel aid to predict the molar absorptivities of color reactions and in the long term to be helpful tool in-color reagent design. Multiple regression analysis and neural network were employed simultaneously in this study. The results demonstrated the feasibility and the effectiveness of the method.

Automorphism group algorithm in computer-aided structure elucidation

It is necessary to generate automorphism group of chemical graph in computer-aided structure eluciation. In this paper, an algorithm is developed by all-path topological symmetry algorithm to build automorphism group of chemical graph. A comparison of several topological symmetry algorithm reveals that all-path algorthm can yield correct of class of chemical graph. It lays a foundation for ESESOC system for computer-aided structure elucidation.

A QSAR of the toxicity of amino-benzenes and their structures

The quantum chemical parameters and the topological indices have been calculated for the prediction of the toxicity of amino-benzenes in the environment, and work has been done on the multiple regression and neural networks. The combination of CoMFA with formation heat yields greatly improved results. A good model has been obtained which provides a basis for the studies of the toxic action mechanism.

Correlation analysis of the structures and gas-liquid chromatographic retention indices of amines

Quantitative structure-retention relationship(QSRR) was studied for amines to gas-liquid chromatography on three stationary phases of different polarities with the topological indices A(m) (A(m1), A(m2), A(m3)) and gravitational index GI. The algorithm of "Leaps and Bounds" was performed for selection of the variables. And the multi-regression and the quasi-Newton neural networks were employed for the calculation with better results.

Quantitative structure-property relationship research to the analysis of photoionization sensitivity of organic compounds in gas chromatography

The A(m) index and molecular connectivity index were used for studying the photoionization sensitivity of some organic compounds in gas chromatography. The analysis of structure-property relationship between the photoionization sensitivity of the compounds and the A(m) indices or molecular connectivity indices has been carried out. The genetic algorighm was used to build the correlation model in this field. The results demonstrate that the property of compounds can be described by both A(m) indices and molecular connectivity indices, and the mathematical model obtained by the genetic algorithm was better than that by multivariate regression analysis.

Comparison of different methods for variable selection

In chemistry for chemical analysis of a multi-component sample or quantitative structure-activity/property relationship (QSAR/QSPR) studies, variable selection is a key step. In this study, comparisons between different methods were performed. These methods include three classical methods such as forward selection, backward elimination and stepwise regression; orthogonal descriptors; leaps-and-bounds regression and genetic algorithm. Thirty-five nitrobenzenes were taken as the data set. From these structures quantum chemical parameters, topological indices and indicator variable were extracted as the descriptors for the comparisons of variable selections. The interesting results have been obtained. (C) 2001 Elsevier Science B.V. All rights reserved.