99 resultados para Ge ion


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Taper-free and vertically oriented Ge nanowires were grown on Si (111) substrates by chemical vapor deposition with Au nanoparticle catalysts. To achieve vertical nanowire growth on the highly lattice mismatched Si substrate, a thin Ge buffer layer was first deposited, and to achieve taper-free nanowire growth, a two-temperature process was employed. The two-temperature process consisted of a brief initial base growth step at high temperature followed by prolonged growth at lower temperature. Taper-free and defect-free Ge nanowires grew successfully even at 270 °C, which is 90 °C lower than the bulk eutectic temperature. The yield of vertical and taper-free nanowires is over 90%, comparable to that of vertical but tapered nanowires grown by the conventional one-temperature process. This method is of practical importance and can be reliably used to develop novel nanowire-based devices on relatively cheap Si substrates. Additionally, we observed that the activation energy of Ge nanowire growth by the two-temperature process is dependent on Au nanoparticle size. The low activation energy (∼5 kcal/mol) for 30 and 50 nm diameter Au nanoparticles suggests that the decomposition of gaseous species on the catalytic Au surface is a rate-limiting step. A higher activation energy (∼14 kcal/mol) was determined for 100 nm diameter Au nanoparticles which suggests that larger Au nanoparticles are partially solidified and that growth kinetics become the rate-limiting step. © 2011 American Chemical Society.

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The growth of epitaxial Ge nanowires is investigated on (100), (111) B and (110) GaAs substrates in the growth temperature range from 300 to 380 °C. Unlike epitaxial Ge nanowires on Ge or Si substrates, Ge nanowires on GaAs substrates grow predominantly along the [Formula: see text] direction. Using this unique property, vertical [Formula: see text] Ge nanowires epitaxially grown on GaAs(110) surface are realized. In addition, these Ge nanowires exhibit minimal tapering and uniform diameters, regardless of growth temperatures, which is an advantageous property for device applications. Ge nanowires growing along the [Formula: see text] directions are particularly attractive candidates for forming nanobridge devices on conventional (100) surfaces.

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Significant improvements in the spatial and temporal uniformities of device switching parameters are successfully demonstrated in Ge/TaOx bilayer-based resistive switching devices, as compared with non-Ge devices. In addition, the reported Ge/TaOx devices also show significant reductions in the operation voltages. Influence of the Ge layer on the resistive switching of TaOx-based resistive random access memory is investigated by X-ray spectroscopy and the theory of Gibbs free energy. Higher uniformity is attributed to the confinement of the filamentary switching process. The presence of a larger number of interface traps, which will create a beneficial electric field to facilitate the drift of oxygen vacancies, is believed to be responsible for the lower operation voltages in the Ge/TaO x devices. © 1980-2012 IEEE.

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An integrated 2-D model of a lithium ion battery is developed to study the mechanical stress in storage particles as a function of material properties. A previously developed coupled stress-diffusion model for storage particles is implemented in 2-D and integrated into a complete battery system. The effect of morphology on the stress and lithium concentration is studied for the case of extraction of lithium in terms of previously developed non-dimensional parameters. These non-dimensional parameters include the material properties of the storage particles in the system, among other variables. We examine particles functioning in isolation as well as in closely-packed systems. Our results show that the particle distance from the separator, in combination with the material properties of the particle, is critical in predicting the stress generated within the particle. © 2012 Springer-Verlag.

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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.

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We used a cyclic reactive ion etching (RIE) process to increase the Co catalyst density on a cobalt disilicide (CoSi2) substrate for carbon nanotube (CNT) growth. Each cycle of catalyst formation consists of a room temperature RIE step and an annealing step at 450 °C. The RIE step transfers the top-surface of CoSi2 into cobalt fluoride; while the annealing reduces the fluoride into metallic Co nanoparticles. We have optimized this cyclic RIE process and determined that the catalyst density can be doubled in three cycles, resulting in a final CNT shell density of 6.6 × 10 11 walls·cm-2. This work demonstrates a very effective approach to increase the CNT density grown directly on silicides. © 2014 AIP Publishing LLC.

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How do neurons develop, control, and maintain their electrical signaling properties in spite of ongoing protein turnover and perturbations to activity? From generic assumptions about the molecular biology underlying channel expression, we derive a simple model and show how it encodes an "activity set point" in single neurons. The model generates diverse self-regulating cell types and relates correlations in conductance expression observed in vivo to underlying channel expression rates. Synaptic as well as intrinsic conductances can be regulated to make a self-assembling central pattern generator network; thus, network-level homeostasis can emerge from cell-autonomous regulation rules. Finally, we demonstrate that the outcome of homeostatic regulation depends on the complement of ion channels expressed in cells: in some cases, loss of specific ion channels can be compensated; in others, the homeostatic mechanism itself causes pathological loss of function.