Copolymerization of N‐tert‐Butylacrylamide with Ethylene Glycol Dimethacrylate

N‐tert‐butylacrylamide (NtBA) was copolymerized with ethylene glycol dimethacrylate (EDMA) in butanone solution over a wide composition and conversion range, using dibenzoyl peroxide (Bz₂O₂) as a free‐radical initiator. The copolymer composition was determined from the nitrogen content. Using only low conversion (≤20%) collected for the copolymerization reactions, monomer reactivity ratios were estimated using the Kelen‐Tüdos graphical method and were found to be r₁=0.26 (NtBA) and r₂=7.05 (EDMA). In order to get a better insight into the mechanism of nanoporous copolymers of NtBA with EDMA preparation by thermal degradation of copolymers of N‐acryl‐N,N′‐di‐tert‐butylurea (A‐DitBuU) with EDMA, nonporous copolymers (model compound), of the same chemical structure and composition, were prepared by performing copolymerization of NtBA with EDMA up to the high conversion of 97–100%. Thermal behavior of nanoporous and nonporous copolymers of NtBA with EDMA was studied.     

Spectral representation of reduced protein models

We consider a spectrum-like two-dimensional graphical representation of proteins based on a reduced protein model in which 20 amino acids are grouped into five classes. This particular grouping of amino acids was suggested by Riddle and co-workers in 1997. The graphical representation is based on depicting sequentially the amino acids on five horizontal lines at equal separations. One-letter codes, B, O, U, X and Y, to which numerical values 1 to 5 have been assigned, are suggested as labels for the fictional amino acids that represent all the amino acids within each group. The approach is illustrated on ND6 proteins of eight species having from 168 to 175 amino acids. While visual inspection of the novel spectral graphical representations of proteins may reveal local similarities and dissimilarities of protein sequences, arithmetic manipulations of spectra offer an elegant route to graphic visualization of the degree of similarity for selected pairs of proteins.     

Physicochemical and Graph Theoretical Descriptors in Developmental Toxicity SAR: A Comparative Study

Abstract

Chemical insults to the developing fetus can lead to growth retardation, malformation, death, and functional deficits. The present study seeks to determine if physicochemical and/or graph theoretical parameters can be used to determine a structure-activity relationship (SAR) for developmental toxicity, and if consistency is observed among the selected features. The biological data utilized consists of a diverse series of compounds evaluated within the Chernoff-Kavlock in vivo mouse assay. Physicochemical parameters calculated correspond to electronic, steric, and transport properties. Graph theoretical parameters calculated include the simple, valence, and kappa indices. Both sets of parameters were independently applied to derive SARs in order to compare the quality of the respective models. Multiple random sampling, without replacement, was utilized to obtain ten training/test partitions. Models were built by linear discriminant analysis, decision trees, and neural networks respectively. Comparisons on identical sets of data were carried out to determine if any of the model building procedures had a significant advantage in terms of predictive performance. Furthermore, comparison of the features selected within and across the model building processes led to the determination of model consistency. Our results indicate that consistent features related to developmental toxicity are observed and that both physicochemical and graph theoretical parameters have equal utility.     

Implementation of depth-dependent soil concentrations in multimedia mass balance models

In standard multimedia mass balance models, the soil compartment is modeled as a box with uniform concentrations, which often does not correspond with actual field situations. Therefore, the theoretically expected decrease of soil concentrations with depth was implemented in the multimedia model SimpleBox 3.0. The effects of this implementation on the model outcomes were explored for nine compounds in four environmental compartments. For compounds with a low penetration depth, the new model predicts substantially higher or lower concentrations in the vegetation compartment than the old model. For those compounds, predicted concentrations in surface water and air were higher in the new model, but the deviations from the old model were smaller than in the vegetation compartment. For compounds with a large penetration depth, the model adaptations show little effect. No field study was carried out to validate the results of the model calculations, but we did collect measured data on concentrations in vertical soil profiles from literature. According to those data, we concluded that the implementation of depth dependent soil concentrations might be a useful extension for steady state multimedia mass balance models. More field study has to be carried out to validate the model outcomes.     

Synthesis of CuCorePtShell Nanoparticles as Model Structures for Core–Shell Electrocatalysts by Direct Platinum Electrodeposition on Copper

The synthesis of Cu(core)Pt(shell) model catalysts by the direct electrochemical deposition of Pt on Cu particles is presented. Cu particles with an average diameter of 200 nm have been deposited on glassy‐carbon electrodes by double pulse electrodeposition from a copper sulfate solution. Subsequent deposition from a platinum nitrate solution under potential control allows for a high selectivity of the Pt deposition towards Cu. Using a combination of cyclic voltammetry, XPS and sputtering, the structure of the generated particles has been analyzed and their core–shell configuration proven. It is shown that the electrocatalytic activity for the oxygen reduction is similar to that of other PtCu catalyst systems. The synthesized structures could allow for the analysis of structure–activity relations of core–shell catalysts on the way to the simple and controlled synthesis of supported Cu(core)Pt(shell) nanoparticles as oxygen reduction catalysts.     

原子转移自由基聚合的动力学模型化研究

原子转移自由基聚合(ATRP)是“活性”/可控自由基聚合方法中研究最为广泛的一种,它不仅适用单体广泛、反应条件温和,而且可以方便地对聚合物进行结构设计.为了能够更深入地了解和控制聚合过程,通过ATRP动力学模型化并耦合不同操作方式下的反应器模型已成为必然,它可以更精确地控制大分子链结构,如分子量及其分布、共聚组成及组成分布,同时还能优化聚合条件.从传统自由基聚合理论入手并结合ATRP与传统 自由基聚合的异同,本文首先论述了ATRP动力学模型化过程;其次系统综述了已有的ATRP动力学模型研究,着重对三类不同的数学模型处理方法(矩方法,蒙特卡罗法、商业软件包-PREDICI,GEPASI等)进行了总结.