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.     

Cure Kinetics of Poly(acrylonitrile-butadiene-styrene) Modified Epoxy–Amine System

The cure kinetics of epoxy based on the diglycidyl ether of bisphenol A (DGEBA) modified with different amounts of poly(acrylonitrile-butadiene-styrene) (ABS) and cured with 4,4′-diaminodiphenylsulfone (DDS) was investigated by employing differential scanning calorimetry (DSC). The curing reaction was followed by using an isothermal approach over the temperature range 150–180°C. The amount of ABS in the blends was 3.6, 6.9, 10 and 12.9 wt%. Blending of ABS in the epoxy monomer did not change the reaction mechanism of the epoxy network formation, but the reaction rate seems to be decreased with the addition of the thermoplastic. A phenomenological kinetic model was used for kinetic analysis. Activation energies and kinetic parameters were determined by fitting the kinetic model with experimental data. Diffusion control was incorporated to describe the cure in the latter stages, predicting the cure kinetics over the whole range of conversion. The reaction rates for the epoxy blends were found to be lower than that of the neat epoxy. The reaction rates decreased when the ABS contents was increased, due to the dilution effect caused by the ABS on the epoxy/amine reaction mixture.     

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.