Effect of the graft yield of maleic anhydride on the rheological behaviors,mechanical properties,thermal properties,and free volumes of maleic anhydride grafted high‐density polyethylene

The rheological behavior, thermal properties, and molecular mobility of a series of maleic anhydride (MA) grafted high‐density polyethylenes were characterized and evaluated. The rheological behavior was studied with a Haake minilaboratory. The viscosity of the samples in their melt state decreased with an increase in the graft yield, and this could be attributed to the higher molecular mobility for samples with a higher degree of grafting. The thermal properties were investigated with dynamic mechanical analysis and differential scanning calorimetry. Positron annihilation lifetime measurements were used to study the effect of the degree of grafting on the chemical environment and the atomic‐scale free‐volume properties. It was found that the grafted MA group played a significant chemical inhibition role in positronium formation when the graft yield was low. The results also indicated that the higher the degree of grafting was, the broader the free‐volume distribution was. The relationship between the microstructure and rheological behavior is discussed. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Synthesis and structural characterization of methacrylic acid/octadecyl acrylate‐graft‐poly(methylhydrosiloxane) by hydrosilylation

Methylmethacrylate (MMA) and octadecyl acrylate (OA) were grafted to poly(methylhydrosiloxane) (PMHS) by hydrosilylation, respectively, with hexachloroplatinic acid as catalyst, and the former was further hydrolyzed to prepare methacrylic acid (MAA)‐graft‐PMHS under the alkaline condition. Through orthogonal experiment, main factors affecting the graft reaction between OA and PMHS were discussed and arranged in a decreasing order according to their abilities of the effect on the hydrosilylation of OA with PMHS: catalyst dosage, reaction temperature, reaction time, material ratio, and solvent dosage. It was found that the hydrosilylation of OA with PMHS was easier to that of MMA with PMHS. Under optimal conditions, the grafting ratios of MMA with PMHS and OA with PMHS reached about 90 and 95%, respectively. FTIR and ¹H NMR spectra indicated that the hydrosilylation reactions followed the Markovnikov's rule and played a strong preference toward β‐1,2‐addition. The test of contact angle indicated that surface energy of a system was mainly dependent on the polar groups. The surface energy of OA‐graft‐PMHS (35.07 mN/m) was similar to those of PMHS (35.62 mN/m) and polyoctadecyl acrylate (36.57 mN/m), and lower than that of MAA‐graft‐PMHS (43.50 mN/m). © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2008     

Accelerated wear testing with a microfabricated surface to evaluate the lubrication ability of biomolecules on polyethylene

Wear of ultrahigh‐molecular‐weight polyethylene (UHMWPE) and wear‐particle‐induced osteolysis and bone resorption are the major factors causing the failure of total joint replacements. It is feasible to improve the lubrication and reduce the wear of artificial joints. We need further understanding of the lubrication mechanism of the synovial fluid. The objective of this study is to evaluate the lubricating ability of three major components in the synovial fluid: albumin, globulin, and phospholipids. An accelerated wear testing procedure in which UHMWPE is rubbed against a microfabricated surface with controlled asperities has been developed to evaluate the lubrication behavior. An analysis of the wear particle dimensions and wear amount of the tests has provided insights for comparing their lubrication performance. It is concluded that the presence of biomolecules at the articulating interface may reduce friction. A higher concentration of a biological lubricant leads to a decrease in the wear particle width. In addition, in combination with the wear results and mechanical analysis, the roles of individual biomolecules contributing to friction and wear at the articulating interface are discussed. These results can help us to identify the role of the biomolecules in the boundary lubrication of artificial joints, and further development of lubricating additives for artificial joints may be feasible. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Towards a new definition of EPOC parameters for anionic electrochemical catalysts: case of propene combustion

The electrochemical promotion of catalysis (EPOC) of propene combustion was investigated using Pt sputtered thin film on an O²⁻ conductor, 8 mol% Y₂O₃-stabilized-ZrO₂ (YSZ). In order to separate the influence of the thermal migration of the O²⁻ oxide ions from the electrolyte to the catalyst surface and the impact of an electrical polarization on the catalytic activity, several light-off experiments (cool down and heat up procedures) were successively performed under different polarizations, i.e. OCV, +2 and −2 V. These experiments have clearly shown that the presence of O²⁻ (thermally or electrochemically induced) inhibits the catalytic activity of the platinum for the propene deep oxidation. These results demonstrate the importance to define a normalized rate enhancement ratio, ρ _n , from a reference value of the catalytic rate corresponding to a Pt surface state free of O²⁻ ions.     

A strategy for the electro-organic synthesis of new hydrocaffeic acid derivatives

Electrochemical treatment processes can significantly contribute to the protection of the environment through the minimization of waste and toxic materials in effluents. From a pharmaceutical point of view and due to the existing resemblance between the electrochemical and biological reactions, it can be assumed that the oxidation mechanisms on the electrode and in the body share similar principles. In this paper, the application of electrochemical studies in the design of an environmentally friendly method was delineated for the new hydrocaffeic acid (HCA, 3,4-dihydroxy hydrocinnamic acid) derivatives synthesis at carbon electrodes in an undivided cell. In this cell, the EC mechanism reaction was involved, comprising two steps alternatively; (1) electrochemical oxidation and (2) chemical reaction. In particular, the electro-organic reactions of HCA, an important biological molecule, were studied in a water–acetonitrile (90:10 v/v) mixture in the presence of benzenesulfinic acid (3) and p-toluenesulfinic acid (4). The research included the use of a variety of experimental techniques, such as cyclic voltammetry, controlled-potential electrolysis and product spectroscopic identification.     

NiCoFe/C cathode electrocatalysts for direct ethanol fuel cells

A direct ethanol fuel cell (DEFC), which is less prone to ethanol crossover, is reported. The cell consists of PtRu/C catalyst as the anode, Nafion^® 117 membrane, and Ni–Co–Fe (NCF) composite catalyst as the cathode. The NCF catalyst was synthesized by mixing Ni, Co, and Fe complexes into a polymer matrix (melamine-formaldehyde resins), followed by heating the mixture at 800 °C under inert atmosphere. TEM and EDX experiments suggest that the NCF catalyst has alloy structures of Ni, Co and Fe. The catalytic activity of the NCF catalyst for the oxygen reduction reaction (ORR) was compared with that of commercially available Pt/C (CAP) catalyst at different ethanol concentrations. The decrease in open circuit voltage (V_oc) of the DEFC equipped with the NCF catalysts was less than that of CAP catalyst at higher ethanol concentrations. The NCF catalyst was less prone to ethanol oxidation at cathode even when ethanol crossover occurred through the Nafion^®117 film, which prevents voltage drop at the cathode. However, the CAP catalyst did oxidize ethanol at the cathode and caused a decrease in voltage at higher ethanol concentrations.     

On the effectiveness of early life cycle defect prediction with Bayesian Nets

Standard practice in building models in software engineering normally involves three steps: collecting domain knowledge (previous results, expert knowledge); building a skeleton of the model based on step 1 including as yet unknown parameters; estimating the model parameters using historical data. Our experience shows that it is extremely difficult to obtain reliable data of the required granularity, or of the required volume with which we could later generalize our conclusions. Therefore, in searching for a method for building a model we cannot consider methods requiring large volumes of data. This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. The approach supports (1) and (2), does not require (3), yet still makes accurate defect predictions (an R ² of 0.93 between predicted and actual defects). Since our method does not require detailed domain knowledge it can be applied very early in the process life cycle. The model incorporates a set of quantitative and qualitative factors describing a project and its development process, which are inputs to the model. The model variables, as well as the relationships between them, were identified as part of a major collaborative project. A dataset, elicited from 31 completed software projects in the consumer electronics industry, was gathered using a questionnaire distributed to managers of recent projects. We used this dataset to validate the model by analyzing several popular evaluation measures (R ², measures based on the relative error and Pred). The validation results also confirm the need for using the qualitative factors in the model. The dataset may be of interest to other researchers evaluating models with similar aims. Based on some typical scenarios we demonstrate how the model can be used for better decision support in operational environments. We also performed sensitivity analysis in which we identified the most influential variables on the number of residual defects. This showed that the project size, scale of distributed communication and the project complexity cause the most of variation in number of defects in our model. We make both the dataset and causal model available for research use.