SPECTRAL CHARACTERISTICS OF FREE AND LINKED PYRENE-TYPE CHROMOPHORES IN SOLUTION,POLYMER MATRICES,AND INTERPENETRATING NETWORKS

Monomers, 1-pyrenylmethyl methacrylate (PyMMA), 1-pyrenylbutyl methacrylate (PyBMA), 4-(1-pyrenyl)methoxymethyl styrene (PyMMS) and allyl-(1-pyrenylmehtyl) ether (PyMAE), with pyrene as chromophore, were prepared. Their spectral properties (absorption, emission and emission decay) in solution, and doped or bonded in polymer matrices and complex polymer systems as interpenetrating polymer networks (IPN), were investigated. Spectral properties of pyrene-containing monomers doped in polystyrene (PS), polymethylmethacrylate (PMMA), polyvinylchloride (PVC), polyethylene (PE) and grafted on PE as well as copolymerized in buthylmethacrylate-co-styrene copolymer (BMA-co-S) have been compared. Absorption and emission spectra of pyrene type probes in solution and in IPN matrices exhibit typical absorption of the pyrene moiety. For IPN with grafted probes on PE, the absorption is slightly shifted to red wavelength. For monomers, PyMMA, PyBMA and PyMAE grafted to PE, the shape of the emission spectrum depends on the wavelength of excitation. The ratio of intensity of the vibrational band, I₁/I₃, (I₁ peak at 377 nm and I₃ peak at 388 nm) has been a quite useful indicator of polarity of IPN. The relative quantum yields of fluorescence in IPN matrices are lower in comparison to polymer matrices of PE, PS, PMMA for all probes under study. The fluorescence life-times for bound and free probes have been in the range 100–200 ns, which is substiantialy shorter than for the parent pyrene chromophore under the same or similar condition. Grafted probes on PE alone, or as a part of IPN, exhibit substantially shorter life-time around 10 ns and decay is rather complex.     

Elastomeric Properties of Polysiloxane Networks. Bimodal Elastomers that are Spatially Inhomogeneous and Others that are Very Broadly Multimodal

End‐linking poly(dimethylsiloxane) was used to prepare bimodal elastomers networks so as to have inhomogeneous nanostructures, and also to prepare others having very broadly multimodal chain‐length distributions. Macroscopic phase separation, probably high crosslink density clusters, was observed to occur in some of the bimodal networks. The mechanical properties in simple extension and in equilibrium swelling were measured. The bimodal elastomers that were not obviously inhomogeneous showed very good mechanical properties, but the macroscopically phase‐separated networks, and the broadly multimodal network were weak. Analysis of the Mooney‐Rivlin profiles suggests that the reinforcing mechanism could have a structural component in addition to that from the limited extensibilities of the short chains. The mechanical properties and the extents of swelling support the cluster conjecture, in accord with previous morphological studies on spatially‐inhomogeneous polysiloxane elastomers.     

Prediction of High Performance Fibers Strength Using Back Propagation Neural Network

Nowadays, quantification of the effects of basic parameters such as precursor, temperature oxidation, residence time, low temperature carbonization (LTC) and high temperature carbonization (HTC) on production process polyacrylonitrile based carbon fibers is not completely understood. In this way, there is not a completely theoretical model that accomplishes to quantitatively describe production process carbon fibers very accurately which needs to be used by engineers in design, simulation and operation of that process. This paper presents the development of a back propagation neural network model for the prediction of carbon fibers produced from PAN fibers. The model is based on experimental data. The precursors, temperature oxidation, residence time, LTC and HTC have been considered as the input parameters and the strength as output parameter to develop the model. The developed model is then compared with experimental results and it is found that the results obtained from the neural network model are accurate in predicting the strength of carbon fibers.     

Protein Secondary Structure Prediction with Partially Recurrent Neural Networks

Abstract

Partially recurrent neural networks with different topologies are applied for secondary structure prediction of proteins. The state of some activations in the network is available after a pattern presentation via feedback connections as additional input during the processing of the next pattern in a sequence. A reference data set containing 91 proteins in the training set and 15 non-homologous proteins in the test set is used for training and testing a network with a modified, hierarchical Elman architecture. The network predicts the secondary structures α-helix, β-sheet, and “coil” for each amino acid. The percentage of correctly classified amino acids is 67.83% on the training set and 63.98% on the test set. The best performance of a three-layer feedforward network is 62.7% on the same test set. A cascaded network, where the outputs of the recurrent network are processed by a second net with 13 × 3 inputs, four hidden and three output units has a predictive performance of 64.49%. The best corresponding feedforward net has a performance of 64.3%.     

Qsar Models for Predicting the Acute Toxicity of Selected Organic Chemicals with Diverse Structures to Aquatic Non-Vertebrates and Humans

Abstract

The linear and non-linear relationships of acute toxicity (as determined on five aquatic non-vertebrates and humans) to molecular structure have been investigated on 38 structurally-diverse chemicals. The compounds selected are the organic chemicals from the 50 priority chemicals prescribed by the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme. The models used for the evaluations are the best combination of physico-chemical properties that could be obtained so far for each organism, using the partial least squares projection to latent structures (PLS) regression method and backpropagated neural networks (BPN). Non-linear models, whether derived from PLS regression or backpropagated neural networks, appear to be better than linear models for describing the relationship between acute toxicity and molecular structure. BPN models, in turn, outperform non-linear models obtained from PLS regression. The predictive power of BPN models for the crustacean test species are better than the model for humans (based on human lethal concentration). The physico-chemical properties found to be important to predict both human acute toxicity and the toxicity to aquatic non-vertebrates are the n?octanol water partition coefficient (Pow) and heat of formation (HF). Aside from the two former properties, the contribution of parameters that reflect size and electronic properties of the molecule to the model is also high, but the type of physico-chemical properties differs from one model to another. In all of the best BPN models, some of the principal component analysis (PCA) scores of the ¹³C-NMR spectrum, with electron withdrawing/accepting capacity (LUMO, HOMO and IP) are molecular size/volume (VDW or MS1) parameters are relevant. The chemical deviating from the QSAR models include non-pesticides as well as some of the pesticides tested. The latter type of chemical fits in a number of the QSAR models. Outliers for one species may be different from those of other test organisms.     

Modeling Interfacial Tension of n-Alkane/Water-Salt System Using Artificial Neural Networks

In this paper, a feed forward neural network is built and trained using experimental data reported in the literature to model interfacial tension of n-alkane/water-salt systems. Temperature, pressure, molecular weight of n-alkane, and ionic strength of electrolyte solution are used as input to the neural network. The model succeeded to predict interfacial tension of liquid n-alkane/water system with or without the presence of electrolyte and yielded average absolute deviation of 0.58% over all data points. The performance of the model is analyzed and compared against the performance of the other alternative models. It was found out that the proposed model outperforms the other alternatives.     

Photosensitive cholesteric copolymers with spiropyran-containing side groups II. Kinetic features of the photo- and thermo-chromic processes

Kinetic features of the photo- and thermo-chromic behaviour of new cholesteric triple copolymers with photosensitive spiropyran-containing side groups are considered. The kinetics of the back thermal process at different temperatures have been studied; activation energies for this process for the copolymers with different contents of the dye units have been obtained. The photochromic homopolymer and copolymers with a low content of dye units are shown to possess maximum values of the activation energy.     

Supramolecular main-chain liquid crystalline polymers and networks with competitive hydrogen bonding

A series of supramolecular polymers and networks with variable liquid crystalline characteristics have been created. These species are formed though the benzoic acid/pyridine associations of a flexible bisacid and a mixture of a rigid bispyridyl and a non-mesogenic tetrapyridyl. The networked systems displayed liquid crystalline characteristics up to and including 22.5% netpoint inclusion. Above this concentration, only crystalline and melting behaviours were observed. This observed phenomenon would seem to be linked to the statistical correlation of hydrogen bond acceptors and donors. There was also no observed phase segregation of the species after multiple heat/cool cycles and extended periods of time in the isotropic state. This would indicate that the thermodynamically more stable mesogenic phase cannot out-compete the non-liquid crystalline network. Computational analysis indicates no significant difference in hydrogen bond strength between the two different hydrogen bond acceptors.     

由氢键连接的三个金属-有机网状化合物的合成、结构及半导体性质

以2,4,6-三(1-吡唑基)-1,3,5-三嗪(TPTz)与不同金属离子进行溶剂热反应,得到了3个氢键连接的金属-有机网状化合物。实验发现TPTz的水解产物6-(1-吡唑基)-1,3,5-三嗪-2,4-二酚(H₂L)在反应中起到了实际的配位作用。单晶结构分析表明,它们是同构化合物,分子式为[M(HL)₂]·2H₂O(M=Zn,1;Co,2;Mn,3)。每个中心金属原子分别与2个吡唑基上的N、2个吡嗪环上的N和2个水分子中的O形成六配位的结构。2个HL-与1个中心金属配位形成一个零维的金属-有机配合物小分子,这些小分子通过氢键连接进一步拓展为二维层状结构。紫外-可见漫反射(UV-VisDRS)分析结果表明,这3种化合物都是宽系半导体材料,其带隙宽度分别为3.80(Zn),3.30(Co),3.27(Mn)eV,其半导体性质同中心金属原子表现出明显的相关性。