Localized thinning for strain concentration in suspended germanium membranes and optical method for precise thickness measurement

We deposited Ge layers on (001) Si substrates by molecular beam epitaxy and used them to fabricate suspended membranes with high uniaxial tensile strain. We demonstrate a CMOS-compatible fabrication strategy to increase strain concentration and to eliminate the Ge buffer layer near the Ge/Si hetero-interface deposited at low temperature. This is achieved by a two-steps patterning and selective etching process. First, a bridge and neck shape is patterned in the Ge membrane, then the neck is thinned from both top and bottom sides. Uniaxial tensile strain values higher than 3% were measured by Raman scattering in a Ge membrane of 76 nm thickness. For the challenging thickness measurement on micrometer-size membranes suspended far away from the substrate a characterization method based on pump-and-probe reflectivity measurements was applied, using an asynchronous optical sampling technique.EC/FP7/628197/EU/Heat Propagation and Thermal Conductivity in Nanomaterials for Nanoscale Energy Management/HEATPRONAN

La estimación de proporciones mediante técnicas Bayesianas

The estimation procedures based on Bayes' Theorem are still an unusual option in many of the environments of classic parametric inference. The aim of this paper is to show an effective scheme for the use of Bayesian estimation of unknown parameters. We have opted to focus on the estimation of parameters under the assumption of a binomial model, so that it can be followed by all those situations that meet the aforementioned probabilistic model. This approximation was studied in comparison with the classic parametric approximation, both in its point version and by means of interval estimation. On a study, by simulating samples of several sizes, we obtained empirical evidence regarding the advantage of the Bayesian procedure.ResumenLos procedimientos de estimación basados en el teorema de Bayes son inusuales en los diferentes ámbitos de aplicación de la inferencia paramétrica clásica. El objetivo de este trabajo es presentar un esquema para la estimación bayesiana de parámetros bajo los supuestos de un modelo binomial. El procedimiento Bayes se estudia en comparación con la aproximación paramétrica cl??sica, ambas opciones, en su versión puntual y mediante intervalos de estimación. Se presenta también un estudio de simulación con diferentes tamaños muestrales en el que se ponen de manifiesto las ventajas del procedimiento bayesiano.AbstractThe estimation procedures based on Bayes' Theorem are still an unusual option in many of the environments of classic parametric inference. The aim of this paper is to show an effective scheme for the use of Bayesian estimation of unknown parameters. We have opted to focus on the estimation of parameters under the assumption of a binomial model, so that it can be followed by all those situations that meet the aforementioned probabilistic model. This approximation was studied in comparison with the classic parametric approximation, both in its point version and by means of interval estimation. On a study, by simulating samples of several sizes, we obtained empirical evidence regarding the advantage of the Bayesian procedure

Psychological profile of subjects facilitating responsible preventive behavior

Preventive behavior, Psychological profile,