Deactivation of metal catalysts in liquid phase organic reactions

The paper gives a general survey of the factors contributing to the deactivation of metal catalysts employed in liquid phase reactions for the synthesis of fine or intermediate chemicals. The main causes of catalyst deactivation are particle sintering, metal and support leaching, deposition of inactive metal layers or polymeric species, and poisoning by strongly adsorbed species. Weakly adsorbed species, poisons at low surface coverage and solvents, may act as selectivity promoters or modifiers. Three examples of long term stability studies carried out in trickle-bed reactor (glucose to sorbitol hydrogenation on Ru/C catalysts, hydroxypropanal to 1,3-propanediol hydrogenation on Ru/TiO₂ catalysts, and wet air oxidation of paper pulp effluents on Ru/TiO₂) are discussed.     

Interaction between dietary protein and fat in triglyceride metabolism in the rat: Effects of soy protein and menhaden oil

The objective of the present study was to determine the mechanisms by which dietary proteins interact with dietary lipids in the regulation of triglyceridemia in rats. Male Sprague-Dawley rats (n=56) were subjected to 28-d experimental diets containing different combinations of proteins (20% w/w) and lipid sources (14% w/w): (i) casein-menhaden oil, (ii) casein-beef tallow, (iii) soy protein-menhaden oil, and (iv) soy protein-beef tallow. Significant protein-lipid interactions were observed on triglyceridemia and hepatic cholesterol in fasted rats. The combination of casein and beef tallow was associated with high plasma TG and hepatic cholesterol concentrations, which were reduced by substitution either of soy for casein or of menhaden oil for beef tallow. Therefore, triglyceridemia and liver cholesterol remained low with soy protein feeding, independently of the lipid source, as well as with menhaden oil feeding, regardless of the protein source. The menhaden oil diets reduced plasma cholesterol, hepatic TG, and TG secretion compared with beef tallow diets independently of the dietary protein source. Modifying the source of dietary proteins and lipids had no effect on post-heparin plasma lipoprotein lipase activity. These results demonstrate that soy protein can lower rat triglyceridemia relative to casein when associated with beef tallow consumption, whereas menhaden oil can attenuate hypertriglyceridemia when rats are fed casein. The data further suggest that part of the hypotriglyceridemic effect of soy protein in the rat may be mediated by reduced hepatic lipid synthesis, as is the case for menhaden oil.     

NH_3 Plasma Surface Treatments of Engineering Fluoropolymers: A Way to Enhance Adhesion of Ni or Cu Thin Films Deposited by Electroless Plating

FLUOROPOLYMERS(FPs)are thermoplasticmaterials which exhibit a number of unique chemicaland physical characteristics that no other man-madeplastic product gets together.For example,FPs showvery good resistance to almost all chemicals,excellentwater vapor barrier properties,high thermal stability,outstanding electrical insulation properties(lowdielectric constant and dissipation factors),extremelylow frictional coefficient giving them high auto-lubrication properties,high resistance to rad…     

Dynamic Model Adaptation for Multiscale Simulation of Hyperbolic Systems with Relaxation

In numerous industrial CFD applications, it is usual to use two (or more) different codes to solve a physical phenomenon: where the flow is a priori assumed to have a simple behavior, a code based on a coarse model is applied, while a code based on a fine model is used elsewhere. This leads to a complex coupling problem with fixed interfaces. The aim of the present work is to provide a numerical indicator to optimize to position of these coupling interfaces. In other words, thanks to this numerical indicator, one could verify if the use of the coarser model and of the resulting coupling does not introduce spurious effects. In order to validate this indicator, we use it in a dynamical multiscale method with moving coupling interfaces. The principle of this method is to use as much as possible a coarse model instead of the fine model in the computational domain, in order to obtain an accuracy which is comparable with the one provided by the fine model. We focus here on general hyperbolic systems with stiff relaxation source terms together with the corresponding hyperbolic equilibrium systems. Using a numerical Chapman–Enskog expansion and the distance to the equilibrium manifold, we construct the numerical indicator. Based on several works on the coupling of different hyperbolic models, an original numerical method of dynamic model adaptation is proposed. We prove that this multiscale method preserves invariant domains and that the entropy of the numerical solution decreases with respect to time. The reliability of the adaptation procedure is assessed on various 1D and 2D test cases coming from two-phase flow modeling.     

A memetic algorithm to solve an unrelated parallel machine scheduling problem with auxiliary resources in semiconductor manufacturing

In this paper, we propose a metaheuristic for solving an original scheduling problem with auxiliary resources in a photolithography workshop of a semiconductor plant. The photolithography workshop is often a bottleneck, and improving scheduling decisions in this workshop can help to improve indicators of the whole plant. Two optimization criteria are separately considered: the weighted flow time (to minimize) and the number of products that are processed (to maximize). After stating the problem and giving some properties on the solution space, we show how these properties help us to efficiently solve the problem with the proposed memetic algorithm, which has been implemented and tested on large generated instances. Numerical experiments show that good solutions are obtained within a reasonable computational time.     

Binarised regression tasks: methods and evaluation metrics

Some supervised tasks are presented with a numerical output but decisions have to be made in a discrete, binarised, way, according to a particular cutoff. This binarised regression task is a very common situation that requires its own analysis, different from regression and classification—and ordinal regression. We first investigate the application cases in terms of the information about the distribution and range of the cutoffs and distinguish six possible scenarios, some of which are more common than others. Next, we study two basic approaches: the retraining approach, which discretises the training set whenever the cutoff is available and learns a new classifier from it, and the reframing approach, which learns a regression model and sets the cutoff when this is available during deployment. In order to assess the binarised regression task, we introduce context plots featuring error against cutoff. Two special cases are of interest, the \( UCE \) and \( OCE \) curves, showing that the area under the former is the mean absolute error and the latter is a new metric that is in between a ranking measure and a residual-based measure. A comprehensive evaluation of the retraining and reframing approaches is performed using a repository of binarised regression problems created on purpose, concluding that no method is clearly better than the other, except when the size of the training data is small.     

The Cost of Environmental Constraints in Traffic Networks: Assessing the Loss of Optimality

Increasing numbers of hard environmental constraints are being imposed in urban traffic networks by authorities in an attempt to mitigate pollution caused by traffic. However, it is not trivial for authorities to assess the cost of imposing such hard environmental constraints. This leads to difficulties when setting the constraining values as well as implementing effective control measures. For that reason, quantifying the cost of imposing hard environmental constraints for a certain network becomes crucial. This paper first indicates that for a given network, such cost is not only related to the attribution of environmental constraints but also related to the considered control measures. Next, we present an assessment criterion that quantifies the loss of optimality under the control measures considered by introducing the environmental constraints. The criterion can be acquired by solving a bi-level programming problem with/without environmental constraints. A simple case study shows its practicability as well as the differences between this framework and other frameworks integrating the environmental aspects. This proposed framework is widely applicable when assessing the interaction of traffic and its environmental aspects.     

Second-order shape derivatives along normal trajectories,governed by Hamilton-Jacobi equations

In this paper we introduce a new variant of shape differentiation which is adapted to the deformation of shapes along their normal direction. This is typically the case in the level-set method for shape optimization where the shape evolves with a normal velocity. As all other variants of the original Hadamard method of shape differentiation, our approach yields the same first order derivative. However, the Hessian or second-order derivative is different and somehow simpler since only normal movements are allowed. The applications of this new Hessian formula are twofold. First, it leads to a novel extension method for the normal velocity, used in the Hamilton-Jacobi equation of front propagation. Second, as could be expected, it is at the basis of a Newton optimization algorithm which is conceptually simpler since no tangential displacements have to be considered. Numerical examples are given to illustrate the potentiality of these two applications. The key technical tool for our approach is the method of bicharacteristics for solving Hamilton-Jacobi equations. Our new idea is to differentiate the shape along these bicharacteristics (a system of two ordinary differential equations).     

Viscosity measurements of liquids under pressure by using the quartz crystal resonators

A quartz crystal viscometer has been developed for measuring viscosity in liquids under pressure. It employs an AT-cut quartz crystal resonator of fundamental frequency 3 MHz inserted in a variable-volume vessel designed for working up to 80 MPa. Viscosity is determined by two methods from resonance frequency and bandwidth measurements along up to eight different overtones. The resonance frequency allows an absolute measurement of the viscosity but leads to an accuracy limited to 5% whereas the bandwidth technique which works in a relative way provides an accuracy of 2%. The techniques were tested by carrying out measurements in two pure compounds: heptane and toluene. Measurement results demonstrate the feasibility of the technique in this viscosity range. The apparatus was also used to determine the viscosity of n-decane with dissolved methane. The results obtained with these mixtures reveal the applicability of the apparatus for reservoir fluids study.