1,548 research outputs found
SPECIAL HEAT TRANSFER PHENOMENA FOR SUPERCRITICAL FLUIDS
Present-day knowledge concerning the molecular structure of supercritical fluids is briefly reviewed. It is shown that liquid-like and gas-like phases may coexist at supercritical pressures, although they may not be in equllibrium with each other. it is postulated that on the basis of the coexistence of these two phases a "boiling-like" phenomenon may provide the mechanism of heat transfer to supercritical fluids at high heat fluxes and certain other conditions. An unusual mode of heat transfer was actually observed at supercritical pressures during tests which produced the high heat fluxes and other conditions under which such "boiling" would be expected. The tests and the various conditions are briefly described. An emission of high-frequeney, high-intensity sounds usually accompanied these tests. It is shown that similar screaming sounds were heard during boiling at subcritical pressures, giving further support to the hypothesis that "boiling" may occur at supercritical pressures. A seeond possible explanation for the unusual mode of heat transfer is based on boundarylayer stability considerations. At high heat fluxes large density differences exist between the bulk of the fluid and the fluid in the boundary layer near the wall. A breakdown of the boundary layer may be caused by the build-up of ripples between its low-density fluid and the high-density bulk fluid, in a manner quite similar to the breaking of ocean waves at high wind velocities. It is pointed out that the density variation of supercritical fluids may be used to advantage by certrifuging boundary layers. (auth
Natural linewidth analysis of d-band photoemission from Ag(110)
We report a high-resolution angle-resolved study of photoemission linewidths
observed for Ag(110). A careful data analysis yields kdd\tau_h \geq 22
d$-hole dynamics in Cu (I.\
Campillo et al., Phys. Rev. Lett., in press) we interpret the lifetime
enhancement by a small scattering cross-section of - and -states below
the Fermi level. With increasing distance to the -hole lifetimes get
shorter because of the rapidly increasing density of d-states and contributions
of intra--band scattering processes, but remain clearly above
free-electron-model predictions.Comment: 14 pages, 7 figure
Density of bulk trap states in organic semiconductor crystals: discrete levels induced by oxygen in rubrene
The density of trap states in the bandgap of semiconducting organic single
crystals has been measured quantitatively and with high energy resolution by
means of the experimental method of temperature-dependent
space-charge-limited-current spectroscopy (TD-SCLC). This spectroscopy has been
applied to study bulk rubrene single crystals, which are shown by this
technique to be of high chemical and structural quality. A density of deep trap
states as low as ~ 10^{15} cm^{-3} is measured in the purest crystals, and the
exponentially varying shallow trap density near the band edge could be
identified (1 decade in the density of states per ~25 meV). Furthermore, we
have induced and spectroscopically identified an oxygen related sharp hole bulk
trap state at 0.27 eV above the valence band.Comment: published in Phys. Rev. B, high quality figures:
http://www.cpfs.mpg.de/~krellner
Hole mobility in organic single crystals measured by a "flip-crystal" field-effect technique
We report on single crystal high mobility organic field-effect transistors
(OFETs) prepared on prefabricated substrates using a "flip-crystal" approach.
This method minimizes crystal handling and avoids direct processing of the
crystal that may degrade the FET electrical characteristics. A chemical
treatment process for the substrate ensures a reproducible device quality. With
limited purification of the starting materials, hole mobilities of 10.7, 1.3,
and 1.4 cm^2/Vs have been measured on rubrene, tetracene, and pentacene single
crystals, respectively. Four-terminal measurements allow for the extraction of
the "intrinsic" transistor channel resistance and the parasitic series contact
resistances. The technique employed in this study shows potential as a general
method for studying charge transport in field-accumulated carrier channels near
the surface of organic single crystals.Comment: 26 pages, 7 figure
Field-induced charge transport at the surface of pentacene single crystals: a method to study charge dynamics of 2D electron systems in organic crystals
A method has been developed to inject mobile charges at the surface of
organic molecular crystals, and the DC transport of field-induced holes has
been measured at the surface of pentacene single crystals. To minimize damage
to the soft and fragile surface, the crystals are attached to a pre-fabricated
substrate which incorporates a gate dielectric (SiO_2) and four probe pads. The
surface mobility of the pentacene crystals ranges from 0.1 to 0.5 cm^2/Vs and
is nearly temperature-independent above ~150 K, while it becomes thermally
activated at lower temperatures when the induced charges become localized.
Ruling out the influence of electric contacts and crystal grain boundaries, the
results contribute to the microscopic understanding of trapping and detrapping
mechanisms in organic molecular crystals.Comment: 14 pages, 4 figures. Submitted to J. Appl. Phy
The time-course of a scrapie outbreak
BACKGROUND: Because the incubation period of scrapie has a strong host genetic component and a dose-response relationship, it is possible that changes will occur during an outbreak, especially in the genotypes of cases, age-at-onset of disease and, perhaps, the clinical signs displayed. We investigated these factors for a large outbreak of natural scrapie, which yielded sufficient data to detect temporal trends. RESULTS: Cases occurred mostly in two genotypes, VRQ/VRQ and VRQ/ARQ, with those early in the outbreak more likely to be of the VRQ/VRQ genotype. As the epidemic progressed, the age-at-onset of disease increased, which reflected changes in the genotypes of cases rather than changes in the age-at-onset within genotypes. Clinical signs of cases changed over the course of the outbreak. As the epidemic progressed VRQ/VRQ and VRQ/ARQ sheep were more likely to be reported with behavioural changes, while VRQ/VRQ sheep only were less likely to be reported with loss of condition. CONCLUSION: This study of one of the largest scrapie outbreaks in the UK allowed investigation of the effect of PrP genotype on other epidemiological parameters. Our analysis indicated that, although age-at-onset and clinical signs changed over time, the observed changes were largely, but not exclusively, driven by the time course of the PrP genotypes of cases
Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks
Data preprocessing is a crucial part of any machine learning pipeline, and it
can have a significant impact on both performance and training efficiency. This
is especially evident when using deep neural networks for time series
prediction and classification: real-world time series data often exhibit
irregularities such as multi-modality, skewness and outliers, and the model
performance can degrade rapidly if these characteristics are not adequately
addressed. In this work, we propose the EDAIN (Extended Deep Adaptive Input
Normalization) layer, a novel adaptive neural layer that learns how to
appropriately normalize irregular time series data for a given task in an
end-to-end fashion, instead of using a fixed normalization scheme. This is
achieved by optimizing its unknown parameters simultaneously with the deep
neural network using back-propagation. Our experiments, conducted using
synthetic data, a credit default prediction dataset, and a large-scale limit
order book benchmark dataset, demonstrate the superior performance of the EDAIN
layer when compared to conventional normalization methods and existing adaptive
time series preprocessing layers
Deep Time-Delay Reservoir Computing: Dynamics and Memory Capacity
The Deep Time-Delay Reservoir Computing concept utilizes unidirectionally
connected systems with time-delays for supervised learning. We present how the
dynamical properties of a deep Ikeda-based reservoir are related to its memory
capacity (MC) and how that can be used for optimization. In particular, we
analyze bifurcations of the corresponding autonomous system and compute
conditional Lyapunov exponents, which measure the generalized synchronization
between the input and the layer dynamics. We show how the MC is related to the
systems distance to bifurcations or magnitude of the conditional Lyapunov
exponent. The interplay of different dynamical regimes leads to a adjustable
distribution between linear and nonlinear MC. Furthermore, numerical
simulations show resonances between clock cycle and delays of the layers in all
degrees of the MC. Contrary to MC losses in a single-layer reservoirs, these
resonances can boost separate degrees of the MC and can be used, e.g., to
design a system with maximum linear MC. Accordingly, we present two
configurations that empower either high nonlinear MC or long time linear MC
M3C: Monte Carlo reference-based consensus clustering.
Genome-wide data is used to stratify patients into classes for precision medicine using clustering algorithms. A common problem in this area is selection of the number of clusters (K). The Monti consensus clustering algorithm is a widely used method which uses stability selection to estimate K. However, the method has bias towards higher values of K and yields high numbers of false positives. As a solution, we developed Monte Carlo reference-based consensus clustering (M3C), which is based on this algorithm. M3C simulates null distributions of stability scores for a range of K values thus enabling a comparison with real data to remove bias and statistically test for the presence of structure. M3C corrects the inherent bias of consensus clustering as demonstrated on simulated and real expression data from The Cancer Genome Atlas (TCGA). For testing M3C, we developed clusterlab, a new method for simulating multivariate Gaussian clusters
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