Parameterization of solar cells

The aggregation (sorting) of the individual solar cells into an array is commonly based on a single operating point on the current-voltage (I-V) characteristic curve. An alternative approach for cell performance prediction and cell screening is provided by modeling the cell using an equivalent electrical circuit, in which the parameters involved are related to the physical phenomena in the device. These analytical models may be represented by a double exponential I-V characteristic with seven parameters, by a double exponential model with five parameters, or by a single exponential equation with four or five parameters. In this article we address issues concerning methodologies for the determination of solar cell parameters based on measured data points of the I-V characteristic, and introduce a procedure for screening of solar cells for arrays. We show that common curve fitting techniques, e.g., least squares, may produce many combinations of parameter values while maintaining a good fit between the fitted and measured I-V characteristics of the cell. Therefore, techniques relying on curve fitting criteria alone cannot be directly used for cell parameterization. We propose a consistent procedure which takes into account the entire set of parameter values for a batch of cells. This procedure is based on a definition of a mean cell representing the batch, and takes into account the relative contribution of each parameter to the overall goodness of fit. The procedure is demonstrated on a batch of 50 silicon cells for Space Station Freedom

Processing asymmetry of transitions between order and disorder in human auditory cortex

Purpose: To develop an algorithm to resolve intrinsic problems with dose calculations using pencil beams when particles involved in each beam are overreaching a lateral density interface or when they are detouring in a laterally heterogeneous medium. Method and Materials: A finding on a Gaussian distribution, such that it can be approximately decomposed into multiple narrower, shifted, and scaled ones, was applied to dynamic splitting of pencil beams implemented in a dose calculation algorithm for proton and ion beams. The method was tested in an experiment with a range-compensated carbon-ion beam. Its effectiveness and efficiency were evaluated for carbon-ion and proton beams in a heterogeneous phantom model. Results: The splitting dose calculation reproduced the detour effect observed in the experiment, which amounted to about 10% at a maximum or as large as the lateral particle-disequilibrium effect. The proton-beam dose generally showed large scattering effects including the overreach and detour effects. The overall computational times were 9 s and 45 s for non-splitting and splitting carbon-ion beams and 15 s and 66 s for non-splitting and splitting proton beams. Conclusions: The beam-splitting method was developed and verified to resolve the intrinsic size limitation of the Gaussian pencil-beam model in dose calculation algorithms. The computational speed slowed down by factor of 5, which would be tolerable for dose accuracy improvement at a maximum of 10%, in our test case.AAPM Annual Meeting 200

Human Auditory cortical processing of changes in interaural correlation

Sensitivity to the similarity of the acoustic waveforms at the two ears, and specifically to changes in similarity, is crucial to auditory scene analysis and extraction of objects from background. Here, we use the high temporal resolution of magnetoencephalography to investigate the dynamics of cortical processing of changes in interaural correlation, a measure of interaural similarity, and compare them with behavior. Stimuli are interaurally correlated or uncorrelated wideband noise, immediately followed by the same noise with intermediate degrees of interaural correlation. Behaviorally, listeners' sensitivity to changes in interaural correlation is asymmetrical. Listeners are faster and better at detecting transitions from correlated noise than transitions from uncorrelated noise. The cortical response to the change in correlation is characterized by an activation sequence starting from ∼50 ms after change. The strength of this response parallels behavioral performance: auditory cortical mechanisms are much less sensitive to transitions from uncorrelated noise than from correlated noise. In each case, sensitivity increases with interaural correlation difference. Brain responses to transitions from uncorrelated noise lag those from correlated noise by ∼80 ms, which may be the neural correlate of the observed behavioral response time differences. Importantly, we demonstrate differences in location and time course of neural processing: transitions from correlated noise are processed by a distinct neural population, and with greater speed, than transitions from uncorrelated noise

Municipal Voter Turn-Out In Ontario: An Analysis of Community Theories and Their Application to a Prescription for Higher Voter Turn-Out in Municipal Elections

This paper examines voter turnout as a proxy for civic engagement by applying the analytical lenses of Robert Putnam’s social capital theory and Richard Florida’s creative capital theory to test critical assumptions regarding the impact of size (population), diversity (immigration), creativity (education and employment), and mobility (length of residency) on voter turnout. A sample of 30 Ontario urban municipalities was analyzed based on data from the 2006 Census. The findings reveal that there is a negative correlation between voter turnout and population size and density; a negative correlation between voter turnout and non-official mother tongue and immigrant status; a negative correlation between voter turnout and creative field of study; a very weak negative correlation between voter turnout and creative occupations; a weak negative correlation between voter turnout and the number of new residents who lived outside the municipality one year prior; and a strong negative correlation between voter turnout and the number of residents who lived outside the municipality five years prior

Convection and chemistry effects in CVD: A 3-D analysis for silicon deposition

The computational fluid dynamics code FLUENT has been adopted to simulate the entire rectangular-channel-like (3-D) geometry of an experimental CVD reactor designed for Si deposition. The code incorporated the effects of both homogeneous (gas phase) and heterogeneous (surface) chemistry with finite reaction rates of important species existing in silane dissociation. The experiments were designed to elucidate the effects of gravitationally-induced buoyancy-driven convection flows on the quality of the grown Si films. This goal is accomplished by contrasting the results obtained from a carrier gas mixture of H2/Ar with the ones obtained from the same molar mixture ratio of H2/He, without any accompanying change in the chemistry. Computationally, these cases are simulated in the terrestrial gravitational field and in the absence of gravity. The numerical results compare favorably with experiments. Powerful computational tools provide invaluable insights into the complex physicochemical phenomena taking place in CVD reactors. Such information is essential for the improved design and optimization of future CVD reactors

Extracts from the World Medical Journal

No Abstract