Evolution of Wurtzite Structured GaAs Shells Around InAs Nanowire Cores.

GaAs was radially deposited on InAs nanowires by metal-organic chemical vapor deposition and resultant nanowire heterostructures were characterized by detailed electron microscopy investigations. The GaAs shells have been grown in wurtzite structure, epitaxially on the wurtzite structured InAs nanowire cores. The fundamental reason of structural evolution in terms of material nucleation and interfacial structure is given.

Durability and photo-electric characteristics of a mille-feuille structured amorphous selenium (a-Se)-arsenic selenide (As2Se3) multi-layered thin film

A mille-feuille structured amorphous selenium (a-Se)-arsenic selenide (As2Se3) multi-layered thin film and a mixed amorphous Se-As2Se3 film is compared from a durability perspective and photo-electric perspective. The former is durable to incident laser induced degradation after numerous laser scans and does not crystallise till 105 of annealing, both of which are improved properties from the mixed evaporated film. In terms of photo-electric properties, the ratio between the photocurrent and the dark current improved whereas the increase of the dark current was higher than that of As2Se3 due to the unique current path developed within the mille-feuille structure. Implementing this structure into various amorphous semiconductors may open up a new possibility towards structure-sensitive amorphous photoconductors. © 2013 Elsevier B.V.

Bayesian Structured Prediction Using Gaussian Processes

We introduce a conceptually novel structured prediction model, GPstruct, which is kernelized, non-parametric and Bayesian, by design. We motivate the model with respect to existing approaches, among others, conditional random fields (CRFs), maximum margin Markov networks (M3N), and structured support vector machines (SVMstruct), which embody only a subset of its properties. We present an inference procedure based on Markov Chain Monte Carlo. The framework can be instantiated for a wide range of structured objects such as linear chains, trees, grids, and other general graphs. As a proof of concept, the model is benchmarked on several natural language processing tasks and a video gesture segmentation task involving a linear chain structure. We show prediction accuracies for GPstruct which are comparable to or exceeding those of CRFs and SVMstruct.

Hierarchically structured nanocarbon electrodes for flexible solid lithium batteries

The ever increasing demand for storage of electrical energy in portable electronic devices and electric vehicles is driving technological improvements in rechargeable batteries. Lithium (Li) batteries have many advantages over other rechargeable battery technologies, including high specific energy and energy density, operation over a wide range of temperatures (-40 to 70. °C) and a low self-discharge rate, which translates into a long shelf-life (~10 years) [1]. However, upon release of the first generation of rechargeable Li batteries, explosions related to the shorting of the circuit through Li dendrites bridging the anode and cathode were observed. As a result, Li metal batteries today are generally relegated to non-rechargeable primary battery applications, because the dendritic growth of Li is associated with the charging and discharging process. However, there still remain significant advantages in realizing rechargeable secondary batteries based on Li metal anodes because they possess superior electrical conductivity, higher specific energy and lower heat generation due to lower internal resistance. One of the most practical solutions is to use a solid polymer electrolyte to act as a physical barrier against dendrite growth. This may enable the use of Li metal once again in rechargeable secondary batteries [2]. Here we report a flexible and solid Li battery using a polymer electrolyte with a hierarchical and highly porous nanocarbon electrode comprising aligned multiwalled carbon nanotubes (CNTs) and carbon nanohorns (CNHs). Electrodes with high specific surface area are realized through the combination of CNHs with CNTs and provide a significant performance enhancement to the solid Li battery performance. © 2013 Elsevier Ltd.

Revealing lithium-silicide phase transformations in nano-structured silicon-based lithium ion batteries via in situ NMR spectroscopy.

Nano-structured silicon anodes are attractive alternatives to graphitic carbons in rechargeable Li-ion batteries, owing to their extremely high capacities. Despite their advantages, numerous issues remain to be addressed, the most basic being to understand the complex kinetics and thermodynamics that control the reactions and structural rearrangements. Elucidating this necessitates real-time in situ metrologies, which are highly challenging, if the whole electrode structure is studied at an atomistic level for multiple cycles under realistic cycling conditions. Here we report that Si nanowires grown on a conducting carbon-fibre support provide a robust model battery system that can be studied by (7)Li in situ NMR spectroscopy. The method allows the (de)alloying reactions of the amorphous silicides to be followed in the 2nd cycle and beyond. In combination with density-functional theory calculations, the results provide insight into the amorphous and amorphous-to-crystalline lithium-silicide transformations, particularly those at low voltages, which are highly relevant to practical cycling strategies.

A thermalization energy analysis of the threshold voltage shift in amorphous indium gallium zinc oxide thin film transistors under simultaneous negative gate bias and illumination

It has been previously observed that thin film transistors (TFTs) utilizing an amorphous indium gallium zinc oxide (a-IGZO) semiconducting channel suffer from a threshold voltage shift when subjected to a negative gate bias and light illumination simultaneously. In this work, a thermalization energy analysis has been applied to previously published data on negative bias under illumination stress (NBIS) in a-IGZO TFTs. A barrier to defect conversion of 0.65-0.75 eV is extracted, which is consistent with reported energies of oxygen vacancy migration. The attempt-to-escape frequency is extracted to be 10 6-107 s-1, which suggests a weak localization of carriers in band tail states over a 20-40 nm distance. Models for the NBIS mechanism based on charge trapping are reviewed and a defect pool model is proposed in which two distinct distributions of defect states exist in the a-IGZO band gap: these are associated with states that are formed as neutrally charged and 2+ charged oxygen vacancies at the time of film formation. In this model, threshold voltage shift is not due to a defect creation process, but to a change in the energy distribution of states in the band gap upon defect migration as this allows a state formed as a neutrally charged vacancy to be converted into one formed as a 2+ charged vacancy and vice versa. Carrier localization close to the defect migration site is necessary for the conversion process to take place, and such defect migration sites are associated with conduction and valence band tail states. Under negative gate bias stressing, the conduction band tail is depleted of carriers, but the bias is insufficient to accumulate holes in the valence band tail states, and so no threshold voltage shift results. It is only under illumination that the quasi Fermi level for holes is sufficiently lowered to allow occupation of valence band tail states. The resulting charge localization then allows a negative threshold voltage shift, but only under conditions of simultaneous negative gate bias and illumination, as observed experimentally as the NBIS effect. © 2014 AIP Publishing LLC.