Atomistic study of the thermodynamic equilibrium of nano-sized helium cavities in βSiC

The estimation of the number of inert gas atoms contained at equilibrium in microscale bubbles in a solid usually relies on a well-known formula equilibrating the internal pressure of He to the surface energy of the bubble. This approach evidences a strong variation with temperature of He content for a given bubble. At the opposite, at the Angstrom scale, ab initio calculations for He contained in vacancy assemblies neglect temperature effects. In this work, empirical potential molecular dynamics simulations are used to study, in the case of helium inserted in cubic silicon carbide, the variation of the He content of sub-nanoscale cavities with temperature. To do so free energy for He atoms inserted in cavities made of a few vacancies (up to 29) are calculated. One then evidences the existence of a sub-surface segregation in interstitial sites close to the surface of the cavity. The variation of the He content with temperature is observed to be negligible at the nanoscale, thus validating the ab initio approach.     

Multiscale roughness analysis in injection‐molding process

The roughness of polymer surfaces is often investigated to guarantee both the surface integrity and the surface functionality. One of the major problems in roughness measurement analyses consists in determining both the evaluation length and the reference line (i.e., the degree of the polynomial equation) from which roughness parameters are computed. This article outlines an original generic method based on the generalized analysis of variance and experimental design methodology for estimating the most relevant roughness parameter p, the most pertinent scale, s, and finally, the degree of the polynomial fitting, d. This methodology is then applied to characterize the influence of four process parameters on the final roughness of poly(polypropylene) samples obtained by injection molding. This method allows us to determine the most efficient triplet (p, s, d) that best discriminates the effect of a process parameter q. It is shown that different (p, s, d) values are affected to each process parameter giving finally the scale on which each process parameter modifies the roughness of a polymeric surface obtained by injection molding. POLYM. ENG. SCI., 2008. © 2008 Society of Plastics Engineers     

Influence du niveau initial de sensibilité au conflit sur l'apprentissage de la conservation des quantités par une méthode de conflit cognitif.

In order to elucidate the problem raised by the usually observed differential efficacy of the induced learning of logical structures by children, the hypothesis was made that the progress observed in preoperational subjects (aged from 4;6 to 6;6), submitted to a training of the conservation of liquids with a technique based upon cognitive conflict, was a function of the subject's initial level of sensitivity to conflict. Subjects were first administered three predictive tests of sensitivity to conflict and then were trained on the conservation task by a method of cognitive conflict based on compensation and addition-subtraction. As predicted, it was found that the experimental group, when compared to the control group, performed better on two successive post-tests and that the progress observed was strongly related to the initial level of sensitivity to cognitive conflict as measured by the predictive test, without any significant correlation with chronological age. These findings seem to indicate that the three main aspects measured by the predictive tests (consistency in the use of concepts, presence of well-articulated functional schemata, ability to accept empirical facts) are important determinants in a child's capacity to profit by a training technique based on cognitive conflict. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Influence of flexible substrates on inverted organic solar cells using sputtered ZnO as cathode interfacial layer

Zinc oxide (ZnO) has recently shown to be of considerable interest for the development of interfacial buffer layers in inverted organic solar cells (OSCs). High quality ZnO thin films can indeed be prepared on large-area ITO-coated flexible substrates, using low temperature deposition techniques such as sputtering, a compatible technique with roll-to-roll process. However, further studies are still needed for a better understanding of the influence of the flexible substrate properties on the photovoltaic performances of those devices. In this work, ZnO films have been sputtered on ITO-coated flexible (PEN) substrates and annealed at different temperatures. The role of the surface morphology and the crystalline quality of ZnO films has been investigated. In the window of flexible compatible process, we found that moderate annealing temperatures of ZnO (?180 °C) lead to improved structural properties and performances. Interestingly, we achieve optimal performances for an annealing temperature of 160 °C, resulting in power conversion efficiency (PCE) equivalent to the highest performances usually achieved on rigid cells.     

Influence de l'induction des processus d'autorégulation sur le rendement à une tache cognitive.

Examined whether inducing self-regulatory processes through a concurrent verbal report technique could improve the performance of adult participants on a concept formation task. This technique consists of instructing Ss to state explicitly the reasons underlying each of the steps employed in the process of resolving a task. It is indicated that self-regulatory processes should be optimized when individuals have access to external feedback indicating success or failure of their cognitive enterprise. To examine and dissociate the respective effect of these 2 factors, 80 university students were randomly assigned to 1 of 4 experimental conditions in a 2 (with or without concurrent report)?×?2 (with or without feedback) crossed design. Results indicate that Ss who made a concurrent report performed better than those who did not. The presence of feedback seemed to hinder performance. Results are discussed in relation to the recent model of metacognition proposed by M. Lefebvre-Pinard and the 2nd author (in press). (20 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Large Scale Terrain Generation from Tectonic Uplift and Fluvial Erosion

At large scale, landscapes result from the combination of two major processes: tectonics which generate the main relief through crust uplift, and weather which accounts for erosion. This paper presents the first method in computer graphics that combines uplift and hydraulic erosion to generate visually plausible terrains. Given a user‐painted uplift map, we generate a stream graph over the entire domain embedding elevation information and stream flow. Our approach relies on the stream power equation introduced in geology for hydraulic erosion. By combining crust uplift and stream power erosion we generate large realistic terrains at a low computational cost. Finally, we convert this graph into a digital elevation model by blending landform feature kernels whose parameters are derived from the information in the graph. Our method gives high‐level control over the large scale dendritic structures of the resulting river networks, watersheds, and mountains ridges.     

Sparse representation of terrains for procedural modeling

In this paper, we present a simple and efficient method to represent terrains as elevation functions built from linear combinations of landform features (atoms). These features can be extracted either from real world data‐sets or procedural primitives, or from any combination of multiple terrain models. Our approach consists in representing the elevation function as a sparse combination of primitives, a concept which we call Sparse Construction Tree, which blends the different landform features stored in a dictionary. The sparse representation allows us to represent complex terrains using combinations of atoms from a small dictionary, yielding a powerful and compact terrain representation and synthesis tool. Moreover, we present a method for automatically learning the dictionary and generating the Sparse Construction Tree model. We demonstrate the efficiency of our method in several applications: inverse procedural modeling of terrains, terrain amplification and synthesis from a coarse sketch.