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

Dependence of DC characteristics of CNT MOSFETs on bandstructure models

http://www.gianlucafiori.org/articles/CNTieeenano.pd

Posture and isokinetic shoulder strength in female water polo players

Background: Being overhead athletes, water polo players can present with muscular imbalances of the shoulder, between the internal rotators (IR) and external rotators (ER), leading to changes in posture and an increased risk of injury.Objectives: To assess posture and isokinetic shoulder strength of female club-level water polo players.Methods: A descriptive study assessing posture and isokinetic strength of the IR and ER shoulder muscles in 15 female club-level South African water polo players (age: 21.3 ± 1.5 years) was conducted. Posture was assessed using a posture grid. Isokinetic shoulder rotator muscle strength was tested over five repetitions concentrically and eccentrically at 60°/sec using a Biodex system 3 isokinetic dynamometer. The bilateral, reciprocal and functional dynamic control ratios (DCR) were calculated.Results: Typical postures noted were a forward head, rounded shoulders, increased thoracic spine kyphosis, elevated non-dominant shoulder and mild scapula winging. The mean concentric reciprocal ratios for the dominant (52.2 ± 7%) and non-dominant (51.9 ± 6.4%) sides indicated ER muscle weakness. DCR values were within normal limits for the group. (D: 0.75 ± 0.2 and ND: 0.75 ± 0.1).Conclusion: There is a trend for these female water polo players to have rounded shoulders and forward head postures, as well as ER muscle strength weakness, the combination of which could predispose the athletes to shoulder injury

Effect of coat-protein concentration on the self-assembly of bacteriophage MS2 capsids around RNA

Self-assembly is a vital part of the life cycle of certain icosahedral RNA viruses. Furthermore, the assembly process can be harnessed to make icosahedral virus-like particles (VLPs) from coat protein and RNA in vitro. Although much previous work has explored the effects of RNA-protein interactions on the assembly products, relatively little research has explored the effects of coat-protein concentration. We mix coat protein and RNA from bacteriophage MS2, and we use a combination of gel electrophoresis, dynamic light scattering, and transmission electron microscopy to investigate the assembly products. We show that with increasing coat-protein concentration, the products transition from well-formed MS2 VLPs to "monster" structures consisting of multiple partial capsids to RNA-protein condensates consisting of large networks of RNA and protein. We argue that the variation in structure arises because the assembly follows a nucleation-and-growth pathway in which the nucleation rate depends sensitively on the coat-protein concentration. At high coat-protein concentration, multiple nuclei can form on each RNA strand, leading to malformed structures. Monte Carlo simulations with coarse-grained models of capsomers and RNA validate this physical picture. Our results provide insight into an important biophysical process and could inform design rules for making VLPs for various applications

Modeling cross-national differences in automated vehicle acceptance

The technology that allows fully automated driving already exists and it may gradually enter the market over the forthcoming decades. Technology assimilation and automated vehicle acceptance in different countries is of high interest to many scholars, manufacturers, and policymakers worldwide. We model the mode choice between automated vehicles and conventional cars using a mixed multinomial logit heteroskedastic error component type model. Specifically, we capture preference heterogeneity assuming a continuous distribution across individuals. Different choice scenarios, based on respondents’ reported trip, were presented to respondents from six European countries: Cyprus, Hungary, Iceland, Montenegro, Slovenia, and the UK. We found that large reservations towards automated vehicles exist in all countries with 70% conventional private car choices, and 30% automated vehicles choices. We found that men, under the age of 60, with a high income who currently use private car, are more likely to be early adopters of automated vehicles. We found significant differences in automated vehicles acceptance in different countries. Individuals from Slovenia and Cyprus show higher automated vehicles acceptance while individuals from wealthier countries, UK, and Iceland, show more reservations towards them. Nontrading mode choice behaviors, value of travel time, and differences in model parameters among the different countries are discussed

An efficient algorithm to calculate intrinsic thermoelectric parameters based on Landauer approach

The Landauer approach provides a conceptually simple way to calculate the intrinsic thermoelectric (TE) parameters of materials from the ballistic to the diffusive transport regime. This method relies on the calculation of the number of propagating modes and the scattering rate for each mode. The modes are calculated from the energy dispersion (E(k)) of the materials which require heavy computation and often supply energy relation on sparse momentum (k) grids. Here an efficient method to calculate the distribution of modes (DOM) from a given E(k) relationship is presented. The main features of this algorithm are, (i) its ability to work on sparse dispersion data, and (ii) creation of an energy grid for the DOM that is almost independent of the dispersion data therefore allowing for efficient and fast calculation of TE parameters. The inclusion of scattering effects is also straight forward. The effect of k-grid sparsity on the compute time for DOM and on the sensitivity of the calculated TE results are provided. The algorithm calculates the TE parameters within 5% accuracy when the K-grid sparsity is increased up to 60% for all the dimensions (3D, 2D and 1D). The time taken for the DOM calculation is strongly influenced by the transverse K density (K perpendicular to transport direction) but is almost independent of the transport K density (along the transport direction). The DOM and TE results from the algorithm are bench-marked with, (i) analytical calculations for parabolic bands, and (ii) realistic electronic and phonon results for $Bi_{2}Te_{3}$.Comment: 16 Figures, 3 Tables, submitted to Journal of Computational electronic

Secretion of an Argonaute protein by a parasitic nematode and the evolution of its siRNA guides

Extracellular RNA has been proposed to mediate communication between cells and organisms however relatively little is understood regarding how specific sequences are selected for export. Here, we describe a specific Argonaute protein (exWAGO) that is secreted in extracellular vesicles (EVs) released by the gastrointestinal nematode Heligmosomoides bakeri, at multiple copies per EV. Phylogenetic and gene expression analyses demonstrate exWAGO orthologues are highly conserved and abundantly expressed in related parasites but highly diverged in free-living genus Caenorhabditis. We show that the most abundant small RNAs released from the nematode parasite are not microRNAs as previously thought, but rather secondary small interfering RNAs (siRNAs) that are produced by RNA-dependent RNA Polymerases. The siRNAs that are released in EVs have distinct evolutionary properties compared to those resident in free-living or parasitic nematodes. Immunoprecipitation of exWAGO demonstrates that it specifically associates with siRNAs from transposons and newly evolved repetitive elements that are packaged in EVs and released into the host environment. Together this work demonstrates molecular and evolutionary selectivity in the small RNA sequences that are released in EVs into the host environment and identifies a novel Argonaute protein as the mediator of this