Does the orbital degeneracy play any role in the high thermopower of lamellar cobaltites?

This article investigates the role of the CoO6 octahedron distortion on the electronic properties and more particularly on the high value of the Seebeck coefficient in the BiCaCoO lamellar cobaltites. Our measurements provide clues indicating that the t2g orbital degeneracy lifting has to be considered to account for the observed high temperature limit of the thermopower. They also provide experimental arguments for locating the a1g and eg′ orbitals levels on the energy scale, through the compression of the octahedron. These results are in agreement with recent ab initio calculation including the electronic correlations and concluding for the inversion of these levels as compared to the expectation from the crystal field theory. © 2007 American Institute of Physics.

Forward Smoothing Using Sequential Monte Carlo

Sequential Monte Carlo (SMC) methods are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. We propose a new SMC algorithm to compute the expectation of additive functionals recursively. Essentially, it is an on-line or "forward only" implementation of a forward filtering backward smoothing SMC algorithm proposed by Doucet, Godsill and Andrieu (2000). Compared to the standard \emph{path space} SMC estimator whose asymptotic variance increases quadratically with time even under favorable mixing assumptions, the non asymptotic variance of the proposed SMC estimator only increases linearly with time. We show how this allows us to perform recursive parameter estimation using an SMC implementation of an on-line version of the Expectation-Maximization algorithm which does not suffer from the particle path degeneracy problem.

Performance prediction of graphene nanoribbon and carbon nanotube transistors

Carbon nanotubes (CNTs) and graphene nanoribbons (GNRs) field-effect transistor (FET) can be the basis for a quasi-one- dimensional (Q1D) transistor technology. Recent experiments show that the on-off ratio for GNR devices can be improved to level exploration of transistor action is justified. Here we use the tight-binding energy dipersion approximation, to assess the performance of semiconducting CNT and GNR is qualitatively in terms of drain current drive strength, bandgap and density of states for a specified device. By reducing the maximum conductance 4e2/h by half, we observed that our model has a particularly good fit with 50 nm channel single walled carbon nanotube (SWCNT) experimental data. Given the same bandgap, CNTs outperform GNRs due to valley degeneracy. Nevertheless, the variation of the device contacts will decide which transistor will exhibit better conductivity and thus higher ON currents. © 2011 American Institute of Physics.