Simulation of aerated lagoon using artificial neural networks and multivariate regression techniques

The aim of this study was to develop an empirical model that provides accurate predictions of the biochemical oxygen demand of the output stream from the aerated lagoon at International Paper of Brazil, one of the major pulp and paper plants in Brazil. Predictive models were calculated from functional link neural networks (FLNNs), multiple linear regression, principal components regression, and partial least-squares regression (PLSR). Improvement in FLNN modeling capability was observed when the data were preprocessed using the PLSR technique. PLSR also proved to be a powerful linear regression technique for this problem, which presents operational data limitations.     

Interpenetrating polymer networks of poly(dimethyl siloxane–urethane) and poly(methyl methacrylate)

Simultaneous IPNs of poly(dimethyl siloxane-urethane) (PDMSU)/poly(methyl methacrylate) (PMMA) and related isomers have been prepared by using new oligomers of bis(β-hydroxyethoxymethyl)poly(dimethyl siloxane)s (PDMS diols) and new crosslinkers biuret triisocyanate (BTI) and tris(β-hydroxylethoxymethyl dimethylsiloxy) phenylsilane (Si-triol). Their phase morphology have been characterized by DSC and SEM. The SEM phase domain size is decreased by increasing crosslink density of the PDMSU network. A single phase IPN of PDMSU/PMMA can be made at an M_c = 1000 and 80 wt % of PDMSU. All of the pseudo- or semi-IPNs and blends of PDMSU and PMMA were phase separated with phase domain sizes ranging from 0.2 to several micrometers. The full IPNs of PDMSU/PMMA have better thermal resistance compared to the blends of linear PDMSU and linear PMMA. © 1993 John Wiley & Sons, Inc.     

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP‐HPLC using feed‐forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP‐HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two‐dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An “early stopping” strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.     

Graft copolymer of polymethyl methacrylate-g-polycarbonate urethane and the fully gelled grafted networks

We have synthesized and characterized the graft copolymer of polymethyl methacrylate (PMMA)-graft-polycarbonate urethane (PCU) (designated PMMA-g-PCU) and the fully gelled mutually crosslinked network composed of both PMMA and PCU (designated as PMMA-PCU-N). Unlike the previously synthesized one phase PCU/PMMA simultaneous interpenetrating polymer networks (IPN's), both of these new materials exhibited two distinct T_g's (from DSC and DMA studies) at all compositions which we have studied. The two-phase nature of the graft and network polymer was confirmed by TEM with domain sizes smaller than those found in the blends of the linear PCU and PMMA chains. In comparison with the corresponding IPN's, the PMMA-g-PCU and the PMMA-PCU-N were thermally less stable and had a lower ultimate strength. © 1992 John Wiley & Sons, Inc.     

Preparation and properties of polyurethane networks based on α,ω-difunctional poly(hexafluoropropylene oxide)

Poly(hexafluoropropylene oxide), poly(HFPO), networks were prepared from functional polymers by end linking via urethane groups. The prepolymers were characterized by NMR spectroscopy and GPC. The networks were characterized by determination of the number of network chains from the shear modulus, and were snown to contain both trifunctional crosslinks and difunctional links. The properties of the networks were investigated by a range of techniques. Compared with fully-fluorinated networks formed via triazine cross-links, investigated previously, the urethane-linked networks were more readily prepared but were poorer elastomers, were less thermally stable, and were less resistant to swelling by common polar solvents. © 1995 John Wiley & Sons, Inc.     

Solute diffusion in swollen membranes VII. Diffusion in semicrystalline networks

A model is developed to express the solute diffusion coefficient through semicrystalline polymeric networks. The crystallites create impermeable diffusional barriers around the amorphous regions. Solute diffusion is determined by applying a transport model to the amorphous phase and incorporating the crosslinked polymer structure characteristics. This model is tested with theophylline and vitamin B₁₂ permeation experiments through semicrystalline poly(vinyl alcohol) membranes prepared by annealing of amorphous PVA membranes. The degree of crystallinity varies between 23.1 % and 40.5 % on a dry basis. The solute diffusion coefficients correlate well with various parameters of the model.     

Total spontaneous resolution of chiral covalent networks from stereochemically labile metal complexes

Stereochemically labile copper and zinc complexes with the N,N'-dimethylethylenediamine ligand (dmeda) have been shown to be promising precursors for the total spontaneous resolution of chiral covalent networks. (N,N')-[Cu(NO3)2(dmeda)]infinity crystallises as a conglomerate and yields either enantiopure (R,R)-1 or enantiopure (S,S)-1. A mixed-valence copper(I/II) complex, [{Cu(II)Br2(dmeda)}3(Cu(I)Br)2]infinity (2), which crystallises as a pair of interpenetrating chiral (10,3)-a nets, is formed from CuBr, CuBr2 and dmeda. One net contains ligands with solely (R,R) configuration and exhibits helices with (P) configuration while the other has solely (S,S)-dmeda ligands and gives rise to a net in which the helices have (M) configuration. The whole crystalline arrangement is racemic, because the interpenetrating chiral nets are of opposite handedness. With zinc chloride (R,S)-[ZnCl(dmeda)2]2[ZnCl4] (3) is obtained, which is a network structure, although not chiral. Total spontaneous resolution of stereochemically labile metal complexes formed from achiral or racemic building blocks is suggested as a viable route for the preparation of covalent chiral networks. Once the absolute structure of the compound has been determined by X-ray crystallography, a quantitative determination of the enantiomeric excess of the bulk product can be undertaken by means of solid-state CD spectroscopy.     

Artificial neural networks for quantification in unresolved capillary electrophoresis peaks

The application of the combination of experimental design (ED) and artificial neural networks (ANNs) for the quantification of overlapped peaks in capillary zone electrophoresis is described. When the total separation cannot be achieved by separation techniques, the use of ED-ANN can be a suitable approach. The unstability of EOF causes peak shift that has to be corrected in order to apply ED-ANN methods. In this work, normalization procedure of electropherograms with consequent application of ANNs for quantification purpose was developed. Both, spectra and electropherograms can be used as multivariate data. In general, both kinds of data were found to be suitable for unresolved peaks quantification by ED-ANN approach.     

电场对含高氯酸锂盐的互穿网络高分子快离子导体的电导的影响

研究了直流电场对含ＬｉＣｌＯ４的聚氧化乙烯（ＰＥＯ）４００与环氧树脂形成的液晶态互穿网络高分子忆禽子导体的电导率的影响。在室温至９０℃范围内，电导率随外加电压增加面降低。外加电压越高，对电导率变化的影响越大。