21,516 research outputs found
Silicon resistor to measure temperature during rapid thermal annealing
A resistor composed of a piece of Si wafer and two thin silver wires attached to it, can reliably sense the temperature during rapid thermal annealing (RTA). As constant electric current passes through the Si piece, the resistivity change of Si with temperature produces a voltage signal that can be readily calibrated and converted to an actual temperature of the samples. An accuracy better than ±10 °C is achieved between 300° and 600 °C
Heterobimetallic Complexes of Rhenium and Zinc: Potential Catalysts for Homogeneous Syngas Conversion
6-(Diphenylphosphino)-2,2′-bipyridine (PNN) coordinates to rhenium carbonyls in both κ^1(P) and κ^2(N,N) modes; in the former, the free bpy moiety readily binds to zinc alkyls and halides. [Re(κ^1(P)-PNN)(CO)_5][OTf] reacts with dialkylzinc reagents to form [Re(κ^1(P)-PNN·ZnR)(CO)_4(μ_(2-)C(O)R)][OTf] (R = Me, Et, Bn), in which an alkyl group has been transferred to a carbonyl carbon and the resulting monoalkyl Zn is bound both to the bpy nitrogens and the acyl oxygen. ZnCl_2 binds readily to the bpy group in Re(κ^1(P)-PNN)(CO)_4Me, and the resulting adduct undergoes facile migratory insertion, assisted by the Lewis acidic pendent Zn, to yield Re(κ^1(P)-PNN·ZnCl)(μ_(2-)Cl)(CO)_3(μ_(2-)C(O)Me), in which one of the chlorides occupies the sixth coordination site on Re. Migratory insertion is inhibited by THF or other ethers that can coordinate to ZnCl_2. Migratory insertion is also observed for Re(κ1(P)-PNN)(CO)_4(CH_2Ph) but not for Re(κ^1(P)-PNN)(CO)_4(CH_2OCH_3); coordination of the methoxy oxygen to Zn appears to block its ability to coordinate to the carbonyl oxygen and facilitate migratory insertion. Intramolecular Lewis acid promoted hydride transfer from [(dmpe)_2PtH][PF_6] to a carbonyl in [Re(κ^1(P)-PNN)(CO)_5][OTf] results in formation of a Re–formyl species; additional hydride transfer leads to a novel Re–Zn-bonded product along with some formal dehyde
Comparison of the device physics principles of planar and radial p-n junction nanorod solar cells
A device physics model has been developed for radial p-n junction nanorod solar cells, in which densely packed nanorods, each having a p-n junction in the radial direction, are oriented with the rod axis parallel to the incident light direction. High-aspect-ratio (length/diameter) nanorods allow the use of a sufficient thickness of material to obtain good optical absorption while simultaneously providing short collection lengths for excited carriers in a direction normal to the light absorption. The short collection lengths facilitate the efficient collection of photogenerated carriers in materials with low minority-carrier diffusion lengths. The modeling indicates that the design of the radial p-n junction nanorod device should provide large improvements in efficiency relative to a conventional planar geometry p-n junction solar cell, provided that two conditions are satisfied: (1) In a planar solar cell made from the same absorber material, the diffusion length of minority carriers must be too low to allow for extraction of most of the light-generated carriers in the absorber thickness needed to obtain full light absorption. (2) The rate of carrier recombination in the depletion region must not be too large (for silicon this means that the carrier lifetimes in the depletion region must be longer than ~10 ns). If only condition (1) is satisfied, the modeling indicates that the radial cell design will offer only modest improvements in efficiency relative to a conventional planar cell design. Application to Si and GaAs nanorod solar cells is also discussed in detail
Photoluminescence-based measurements of the energy gap and diffusion length of Zn_3P_2
The steady-state photoluminescence spectra of zinc phosphide (Zn_3P_2) wafers have revealed a fundamental indirect band gap at 1.38 eV, in close proximity to the direct band gap at 1.50 eV. These values are consistent with the values for the indirect and direct band gaps obtained from analysis of the complex dielectric function deduced from spectroscopic ellipsometric measurements. Bulk minority carrier lifetimes of 20 ns were observed by time-resolved photoluminescence decay measurements, implying minority-carrier diffusion lengths of ≥ 7 µm
Preprocessing Solar Images while Preserving their Latent Structure
Telescopes such as the Atmospheric Imaging Assembly aboard the Solar Dynamics
Observatory, a NASA satellite, collect massive streams of high resolution
images of the Sun through multiple wavelength filters. Reconstructing
pixel-by-pixel thermal properties based on these images can be framed as an
ill-posed inverse problem with Poisson noise, but this reconstruction is
computationally expensive and there is disagreement among researchers about
what regularization or prior assumptions are most appropriate. This article
presents an image segmentation framework for preprocessing such images in order
to reduce the data volume while preserving as much thermal information as
possible for later downstream analyses. The resulting segmented images reflect
thermal properties but do not depend on solving the ill-posed inverse problem.
This allows users to avoid the Poisson inverse problem altogether or to tackle
it on each of 10 segments rather than on each of 10 pixels,
reducing computing time by a factor of 10. We employ a parametric
class of dissimilarities that can be expressed as cosine dissimilarity
functions or Hellinger distances between nonlinearly transformed vectors of
multi-passband observations in each pixel. We develop a decision theoretic
framework for choosing the dissimilarity that minimizes the expected loss that
arises when estimating identifiable thermal properties based on segmented
images rather than on a pixel-by-pixel basis. We also examine the efficacy of
different dissimilarities for recovering clusters in the underlying thermal
properties. The expected losses are computed under scientifically motivated
prior distributions. Two simulation studies guide our choices of dissimilarity
function. We illustrate our method by segmenting images of a coronal hole
observed on 26 February 2015
Modeling the mobility of living organisms in heterogeneous landscapes: Does memory improve foraging success?
Thanks to recent technological advances, it is now possible to track with an
unprecedented precision and for long periods of time the movement patterns of
many living organisms in their habitat. The increasing amount of data available
on single trajectories offers the possibility of understanding how animals move
and of testing basic movement models. Random walks have long represented the
main description for micro-organisms and have also been useful to understand
the foraging behaviour of large animals. Nevertheless, most vertebrates, in
particular humans and other primates, rely on sophisticated cognitive tools
such as spatial maps, episodic memory and travel cost discounting. These
properties call for other modeling approaches of mobility patterns. We propose
a foraging framework where a learning mobile agent uses a combination of
memory-based and random steps. We investigate how advantageous it is to use
memory for exploiting resources in heterogeneous and changing environments. An
adequate balance of determinism and random exploration is found to maximize the
foraging efficiency and to generate trajectories with an intricate
spatio-temporal order. Based on this approach, we propose some tools for
analysing the non-random nature of mobility patterns in general.Comment: 14 pages, 4 figures, improved discussio
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