Architectural View of Flexible Aliphatic –OH Group Coordinated Hemi-Directed Pb(II)-Salen Coordination Polymer: Synthesis,Crystal Structure,Spectroscopic Insights,Supramolecular Topographies,and DFT Perspective

Journal of Inorganic and Organometallic Polymers and Materials - We serendipitously designed one novel 1D hetero-binuclear Zn(II)-Pb(II) coordination polymer, namely...     

Free radical crosslinking of unsaturated bacterial polyesters obtained from soybean oily acids

Summary Poly(-3-hydroxy alkanoate) containing unsaturated side chains, PHA-soybean, were produced by feeding Pseudomonas oleovorans with soybean oily acids obtained from soybean oil. Unsaturation of PHA-soybean were found to be 10 mol-% of unsaturated side chains. Main saturated part of the biopolymer was Poly(3-hydroxy octanoate) with minor hexanoate and decanoate units. PHA films were crosslinked via free radical mechanism by means of thermally or under UV irradiation in the presence of benzoyl peroxide, benzophenon, and /or ethylene glycol dimethacrylate (EGDM). Crosslinking yield of the PHA films were found to be from 81 to 93 wt.-% from the sol-gel analysis. Swelling properties of the crosslinked PHA films in chloroform and toluene were also studied. Mc values of crosslinked PHAs were also calculated using Flory-Rehner equation. The crosslinked biopolyester obtained by thermally at 60 °C with benzoyl peroxide indicated the highest crosslinking density. Glass transition temperatures (Tg) of crosslinked biopolyester samples were changed from −33 to −45 °C while that of PHA-soybean was −60 °C. Received: 16 June 2000/Revised version: 22 January 2001/Accepted: 20 May 2001     

Effects of limestone replacement ratio on the sulfate resistance of Portland limestone cement mortars exposed to extraordinary high sulfate concentrations

A comparative study has been performed on the sulfate resistance of Portland limestone cement (PLC) mortars exposed to extraordinary high sulfate concentrations (200 g/l). PLCs have been prepared by using two types of clinkers having different C₃S/C₂S ratios and interstitial phase morphologies. Blended cements have been prepared by replacing 5%, 10%, 20% and 40% of clinker with limestone. Cubic (50 × 50 × 50 mm) and prismatic (25 × 25 × 285 mm) cement mortars were prepared. After two months initial water curing, these samples were exposed to three different sulfate solutions (Na₂SO₄ at 20 °C and 5 °C, MgSO₄ at 5 °C). Solutions were not refreshed and pH values of solutions were monitored during the testing stage. The compressive strength and length changes of samples have been monitored for a period of 1 year. Additional microstructural analyses have been conducted by XRD and SEM/EDS studies. Results indicated that in general, limestone replacement ratio and low temperature negatively affect the sulfate resistance of cement mortars. Additionally, clinkers of high C₃S/C₂S ratios with dendritic interstitial phase structure were found to be more prone to sulfate attack in the presence of high amounts of limestone.From the results, it is postulated that in the absence of solution change, extraordinary high sulfate content modified the mechanism of sulfate reactions and formation of related products. At high limestone replacement ratios, XRD and SEM/EDS studies revealed that while ettringite is the main deterioration product for the samples exposed to Na₂SO₄, gypsum and thaumasite formation were dominant products of deterioration in the case of MgSO₄ attack. It can be concluded that, the difference between reaction mechanisms of Na₂SO₄ and MgSO₄ attack to limestone cement mortars strongly depends on the pH change of sulfate solutions.     

Plasmid stability in a recombinant S cerevisiae strain secreting a bifunctional fusion protein

The recombinant Saccharomyces cerevisiae strain, YPB‐G, producing and secreting Bacillus subtilis α‐amylase and Aspergillus awamori glucoamylase as a fusion protein yielded efficient utilisation of starch. A segregated population balance model has been used to determine the probability of plasmid loss and plasmid copy number. The kinetics of cell growth and product (fusion protein) formation were based on a genetically structured model. The predictions were compared with the experimental observations obtained for the unstable recombinant S cerevisiae cells in a 1.5 dm^?3 batch bioreactor with 30 g dm³ initial starch under non‐aerated conditions. The main advantage of the present model is that three different genetic classes were defined on the basis of the existence of plasmid and of the expression of the enzymes, ie cells containing plasmids and expressing the gene product, x₁; cells containing plasmids and but not expressing the gene product, x₂; and cells without plasmids, x₃. It is confirmed by this model that the cells without plasmids outgrow and dominate in the fermentation medium (2.27 g dm^?3 vs 0.51 g dm^?3) as more and more glucose becomes available by the degradation of starch. © 2001 Society of Chemical Industry     

Role of Learning Algorithm in Neural Network-Based Backcalculation of Flexible Pavements

Nondestructive testing (NDT) methods are widely used for the performance evaluation of flexible pavements. Falling weight deflectometer (FWD), which measures time-domain deflections resulting from applied impulse loads, is the most popular technique among all NDT methods. The evaluation of the FWD data requires the inversion of mechanical pavement properties using a backcalculation tool that includes both a forward pavement response model and an optimization algorithm. Neural networks (NNs) have also emerged as alternative tools that can be employed for pavement backcalculation problems relative to their real-time processing abilities. However, there have been no comprehensive analyses in previous studies that focus on the learning algorithm and the architecture of a NN model, which considerably affect backcalculation results. In this study, 284 different NN models were developed using synthetic training and testing databases obtained by layered elastic theory. Results indicated that both the learning algorithm and network architecture play important roles in the performance of the NN based backcalculation process.