Activation of a Au/TiO2 Catalyst by Loading a Large Amount of Fe–Oxide: Oxidation of CO Enhanced by H2 and H2O

Catalytic activity of a 1 wt% Au/TiO₂ catalyst is markedly improved by loading a large amount of FeO_x, on which the oxidation of CO in excess H₂ is selectively promoted at temperature lower than 60 °C. Oxidation of CO with O₂ on the FeO_x/Au/TiO₂ catalyst is markedly enhanced by H₂, and H₂O moisture also enhances the oxidation of CO but its effect is not so large as the promotion by H₂. We deduced that activation of Au/TiO₂ catalyst by loading FeO_x is not caused by the size effect of Au particles but a new reaction path via hydroxyl carbonyl intermediate is responsible for the superior activity of the FeO_x/Au/TiO₂ catalyst.     

Kinetics of thermal decomposition of unsaturated polyester resins with reduced flammability

In this article, the kinetics of thermal decomposition of unsaturated maleic–phthalic polyester resins, flame‐retarded with zinc hydroxystannate, was studied by thermogravimetric analysis at different heating rates. At the first stage, it was found, on the basis of isoconversional analysis by the methods of Friedman and of Ozawa–Flynn–Wall, that the value of the (apparent) activation energy (E) characteristically changes in three steps during the degradation. Further kinetic studies using nonlinear regression methods revealed the best fits for both pristine and stabilized resins. It was observed that the course of E versus the degree of conversion (α) during degradation of zinc hydroxystannate‐containing resins (α > 0.8) was characterized by higher values of E—this phenomenon can be explained in terms of the flame‐retardation action of zinc hydroxystannate, which is believed to operate primarily in the condensed phase. At the next stage, kinetic analysis by the nonregression method was performed to find the kinetic model [f(α) function] of the decomposition process; hence, for pristine resin, the best fit was found for the Avrami–Yerofeeyev model (nuclei growth), and for stabilized samples, the nth‐order function with catalysis proved to be the best approximation. The obtained kinetic parameters in the form of E, the preexponential factor A, and the model function f(α) allow a prediction of the polyester resin's thermal behavior in an extrapolated range of degree of conversion, time, and temperature. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 2851–2857, 2003     

A Framework for Moving Least Squares Method with Total Variation Minimizing Regularization

In this paper, we propose a computational framework to incorporate regularization terms used in regularity based variational methods into least squares based methods. In the regularity based variational approach, the image is a result of the competition between the fidelity term and a regularity term, while in the least squares based approach the image is computed as a minimizer to a constrained least squares problem. The total variation minimizing denoising scheme is an exemplary scheme of the former approach with the total variation term as the regularity term, while the moving least squares method is an exemplary scheme of the latter approach. Both approaches have appeared in the literature of image processing independently. By putting schemes from both approaches into a single framework, the resulting scheme benefits from the advantageous properties of both parties. As an example, in this paper, we propose a new denoising scheme, where the total variation minimizing term is adopted by the moving least squares method. The proposed scheme is based on splitting methods, since they make it possible to express the minimization problem as a linear system. In this paper, we employed the split Bregman scheme for its simplicity. The resulting denoising scheme overcomes the drawbacks of both schemes, i.e., the staircase artifact in the total variation minimizing based denoising and the noisy artifact in the moving least squares based denoising method. The proposed computational framework can be utilized to put various combinations of both approaches with different properties together.     

Enhancing decisions with life cycle analysis for risk management

Although corporate financial distress is an infrequent occurrence, it has an extremely debilitating effect on the stability of a firm when it does occur. For this reason, an accurate risk assessment mechanism is needed in numerous industry sectors, particularly in financial institutions and banking. Based on corporation life cycle theory and risk management, this study develops a risk pre-warning model, namely the RSVMDT model, to eliminate serious financial punching and to examine the effectiveness of transparency and the full disclosure index (TFDI) during each life cycle stage. The RSVMDT model includes three techniques: random forest (RF), support vector machines (SVMs), and decision trees (DTs). The RF is used to determine the essential attributes of firms and therefore decrease the computational complexity of financial analysis and improve the classification accuracy. The SVM is employed as a classifier to identify corporations in financial distress. Finally, the DT is utilized as a rule generator that allows decision makers to adjust the financial structures of firms at specific life cycle stages. Together, these three techniques can increase the probability of corporate survival in a highly competitive environment. Additionally, the study further evaluates the importance of the TFDI during a turbulent economy. The public sectors can benefit from this evaluation by formulating future policies based on the rules derived from the developed RSVMDT model.     

Application of SVR,Taguchi loss function,and the artificial bee colony algorithm to resolve multiresponse parameter design problems: a case study on optimizing the design of a TIR lens

Multiresponse parameter design problems have become increasingly important and have received considerable attention from both researchers and practitioners since there are usually several quality characteristics that must be optimized simultaneously in most modern products/processes. This study applies support vector regression (SVR), Taguchi loss function, and the artificial bee colony (ABC) algorithm to develop a six-staged procedure that resolves these common and complicated parameter design problems. SVR is used to model the mathematical relationship between input control factors and output responses, and the ABC algorithm is used to find the optimal control factor settings by searching the well-constructed SVR models in which the Taguchi loss function is applied to evaluate the overall performance of a product/process. The feasibility and effectiveness of the proposed approach are demonstrated via a case study in which the design of a total internal reflection (TIR) lens is optimized while fabricating an MR16 light-emitting diode lamp. Experimental results indicate that the proposed solution procedure can provide highly robust design parameter settings for TIR lenses that can be directly applied in real manufacturing processes. Comparisons with the Taguchi method reveal that the Taguchi method is an undesirable and inappropriate method for resolving multiple-response parameter design problems, while the ABC algorithm can search the solution spaces in continuous domains modeled via SVR instead of in the limited discrete experiment levels, thus finding a more robust design than that obtained by the traditional analysis of variance. Consequently, the proposed integrated approach in this study can be considered feasible and effective and can be popularized as a useful tool for resolving general multiresponse parameter design problems in the real world.     

Mechanical properties and thermal stability of double‐shell thermal‐energy‐storage microcapsules

Double‐shell‐structured microcapsules encapsulating phase‐change materials (micro‐PCMs) with an average diameter of 5–10 μm were successfully fabricated with a melamine–formaldehyde resin as the coating material. The mechanical properties of the obtained piled micro‐PCMs, tested under compression, were evaluated with a pressure sensor. Typical stress–strain curves showed that both the single‐shell‐ and double‐shell‐structured microcapsules had yield points and maximum point pressures. The morphological changes in the shell surface confirmed the existence of yield points by scanning electron microscopy. When the pressure was beyond the yield point, the microcapsules showed conventional plastic behavior, and the double‐shell structure was more mechanically stable than the single‐shell one. Differential scanning calorimetry analysis results revealed that the properties of the phase‐change materials experienced no variation after coating with a single‐shell‐ or double‐shell‐structured polymer. Thermogravimetric analysis showed that the double‐shell‐structured micro‐PCMs experienced a weight loss of only about 5% from 86.3 to 232°C but did so more rapidly from 232 to 416°C. Thermoregulation was determined with periodical heating and cooling tests. The data showed that the micro‐PCMs changed temperature in a narrow range of 20–25°C with a time lag of 20 min to reach the maximum or minimum temperature in comparison with a reference temperature of 18–28°C. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1295–1302, 2007     

过硼酸钠在有机合成中新的应用

介绍了过硼酸钠在有机合成中的一些新的应用。综述了过硼酸钠与芳胺、芳酰胺、有机硼化物、醛等化合物的氧化,取代、酯化反应。     

Effect of chromium aging on the structural and thermal properties of chromium polyacrylate

The effects of aging time of Cr(III) solutions on the structural, thermal, magnetic, and morphological properties of chromium polyacrylate complexes were studied. Chromium retention was found to increase with longer aging periods. IR spectra revealed the formation of polychelate structures with noticeable changes on aging. The interaction of multivalent, polynuclear Cr(III) species with the polymer backbone resulted in a decrease in thermal stability for the complexes prepared from olated chromium solutions. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 490–493, 2005     

高柔韧性聚氨酯丙烯酸酯的合成及应用

选用不同结构的多元醇作骨架，合成一系列高性能的聚氨酯丙烯酸树脂，并通过对聚氨酯丙烯酸树脂性能的对比研究，发现以聚丁二烯二元醇为骨架的聚氨酯丙烯酸酯树脂具有极佳的柔韧性和优异的低温耐曲折性。     

化学反应蚁群优化算法

针对化学反应优化对反馈信息利用不足导致后期求解效率低的问题,提出化学反应蚁群优化算法.该算法利用化学反应优化生成较优解,通过信息素转换策略将较优解转换为蚁群算法的初始信息素,最后由蚁群算法累积更新信息素得到最优解.以TSP为例进行仿真,结果表明,与化学反应优化、蚁群算法、模拟退火算法相比,所提算法具有更高的寻优能力、收敛效率和计算效率.