Growth kinetics and uniform scaling-up of graphene synthesis

Chemical vapor deposition on copper is the most widely used method to synthesize graphene at large scale. However, the clear understanding of the fundamental mechanisms that govern this synthesis is lacking. Using a vertical-flow, cold-wall reactor with short gas residence time we observe the early growths to study the kinetics of chemical vapor deposition of graphene on copper foils and demonstrate uniform synthesis at wafer scale. Our results indicate that the growth is limited by the catalytic dissociative dehydrogenation on the surface and copper sublimation hinders the graphene growth. We report an activation energy of 3.1 eV for ethylene-based graphene synthesis. © The Electrochemical Society.

Spray drying: An alternative synthesis method for polycationic oxide compounds

Synthesis of polycationic compounds by the spray-drying technique is an interesting alternative in the domain of aqueous precursor synthesis methods. Spray drying yields high quality samples with good reproducibility. The possibility of scaling up for production of large quantities with fast processing time is well established by the commercial availability of powders of various compositions. In this paper, we have discussed the advantages and limitations of this method and demonstrated its interest by synthesizing a few polycationic compounds selected for their attractive properties of thermoelectricity [Bi1.68Ca2Co1.69O 8, La0.95A0.05CoO3 (A=Ca, Sr, Ba)] or magnetoresistance [La0.70A0.30MnO3 (A=Sr, Ba)]. We have confirmed the quality of these samples by reporting their structure, magnetic and transport properties. © 2010 Elsevier Ltd All rights reserved.

Scaling of transitionally-rough flow structures in DNSes of channels with riblets up to Reτ=550

The linear, drag-reducing effect of vanishingly small riblets breaks down once their size is in the transitionally-rough regime. We have previously reported that this breakdown is caused by the additional Reynolds stresses produced by the appearance of elongated spanwise rollers just above the riblet surface. These rollers are related with the Kelvin--Helmholtz instability of free shear layers, and to similar structures appearing over other rough and porous surfaces. However, because of the limited Reτ=180 in our previous DNSes, it could not be determined whether those structures scaled in inner or outer units. Furthermore, it is questionable if results in the transitionally-rough regime at Reτ=180 can be extrapolated to configurations of practical interest. At such small Reynolds numbers, roughness of transitional size can perturb a large portion of the boundary layer, which is not the case in most industrial and atmospheric applications. To clarify these issues we have conducted a set of DNSes at Reτ=550. Our results indicate that the spanwise rollers scale in wall units, and support the validity of the extrapolation to configurations of practical interest.

Scaling the iHMM: Parallelization versus Hadoop

This paper compares parallel and distributed implementations of an iterative, Gibbs sampling, machine learning algorithm. Distributed implementations run under Hadoop on facility computing clouds. The probabilistic model under study is the infinite HMM [1], in which parameters are learnt using an instance blocked Gibbs sampling, with a step consisting of a dynamic program. We apply this model to learn part-of-speech tags from newswire text in an unsupervised fashion. However our focus here is on runtime performance, as opposed to NLP-relevant scores, embodied by iteration duration, ease of development, deployment and debugging. © 2010 IEEE.