Numerical study of the thermoelectric power factor in ultra-thin Si nanowires

Low dimensional structures have demonstrated improved thermoelectric (TE) performance because of a drastic reduction in their thermal conductivity, {\kappa}l. This has been observed for a variety of materials, even for traditionally poor thermoelectrics such as silicon. Other than the reduction in {\kappa}l, further improvements in the TE figure of merit ZT could potentially originate from the thermoelectric power factor. In this work, we couple the ballistic (Landauer) and diffusive linearized Boltzmann electron transport theory to the atomistic sp3d5s*-spin-orbit-coupled tight-binding (TB) electronic structure model. We calculate the room temperature electrical conductivity, Seebeck coefficient, and power factor of narrow 1D Si nanowires (NWs). We describe the numerical formulation of coupling TB to those transport formalisms, the approximations involved, and explain the differences in the conclusions obtained from each model. We investigate the effects of cross section size, transport orientation and confinement orientation, and the influence of the different scattering mechanisms. We show that such methodology can provide robust results for structures including thousands of atoms in the simulation domain and extending to length scales beyond 10nm, and point towards insightful design directions using the length scale and geometry as a design degree of freedom. We find that the effect of low dimensionality on the thermoelectric power factor of Si NWs can be observed at diameters below ~7nm, and that quantum confinement and different transport orientations offer the possibility for power factor optimization.Comment: 42 pages, 14 figures; Journal of Computational Electronics, 201

Cross-Language Retrieval with the Twenty-One System

The EU project Twenty-One will support cross language queries in a multilingual document base. A prototype version of the Twenty-One system has been subjected to the Cross Language track tests in order to set baseline performances. The runs were based on query translation using dictionaries and corpus based disambiguation methods

The Mirror DBMS at TREC-8

The database group at University of Twente participates in TREC8 using the Mirror DBMS, a prototype database system especially designed for multimedia and web retrieval. From a database perspective, the purpose has been to check whether we can get sufficient performance, and to prepare for the very large corpus track in which we plan to participate next year. From an IR perspective, the experiments have been designed to learn more about the effect of the global statistics on the ranking

Twenty-One at TREC-8: using Language Technology for Information Retrieval

This paper describes the official runs of the Twenty-One group for TREC-8. The Twenty-One group participated in the Ad-hoc, CLIR, Adaptive Filtering and SDR tracks. The main focus of our experiments is the development and evaluation of retrieval methods that are motivated by natural language processing techniques. The following new techniques are introduced in this paper. In the Ad-Hoc and CLIR tasks we experimented with automatic sense disambiguation followed by query expansion or translation. We used a combination of thesaurial and corpus information for the disambiguation process. We continued research on CLIR techniques which exploit the target corpus for an implicit disambiguation, by importing the translation probabilities into the probabilistic term-weighting framework. In filtering we extended the use of language models for document ranking with a relevance feedback algorithm for query term reweightin

Retrieving Web Pages using Content, Links, URLs and Anchors

For this year’s web track, we concentrated on the entry page finding task. For the content-only runs, in both the ad-hoc task and the entry page finding task, we used an information retrieval system based on a simple unigram language model. In the Ad hoc task we experimented with alternatieve approaches to smoothing. For the entry page task, we incorporated additional information into the model. The sources of information we used in addition to the document’s content are links, URLs and anchors. We found that almost every approach can improve the results of a content only run. In the end, a very basic approach, using the depth of the path of the URL as a prior, yielded by far the largest improvement over the content only results

A Visual Interactive Environment for Making Sense of Experimental Data

We present the Visual Information Retrieval Tool for Upfront Evaluation (VIRTUE) which is an interactive and visual system supporting two relevant phases of the experimental evaluation process: performance analysis and failure analysis. © 2014 Springer International Publishing Switzerland