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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Imaging the Thickness of Passivation Layers for Crystalline Silicon with Micron‐Scale Spatial Resolution Using Spectral Photoluminescence

Thin films deposited on crystalline silicon surfaces are critical components of many silicon‐based devices, including high‐efficiency photovoltaic cells. Knowledge of their optical and electronic properties is important in designing and fabricating efficient solar cells, especially as the device complexity increases and includes micron‐scale features. Here, a camera‐based photoluminescence (PL) technique is developed to image the thickness of specific passivating films on silicon wafers. The technique is entirely contactless and nondestructive, requires minimal sample preparation, and provides a large dynamic range in terms of field of view, with micron‐scale spatial resolution possible. It retains the advantages of PL imaging, a mainstream technique for photovoltaic material and device characterization, and it has some extra capabilities similar to those of ellipsometry. This newly developed technique is demonstrated on hydrogenated amorphous silicon and silicon nitride films, two important passivation technologies for high‐efficiency silicon solar cells.

Nguyen, Hieu T.↗
DOE OSTI2015

Analysis of axial‐induction‐based wind plant control using an engineering and a high‐order wind plant model

Abstract Wind turbines are typically operated to maximize their performance without considering the impact of wake effects on nearby turbines. Wind plant control concepts aim to increase overall wind plant performance by coordinating the operation of the turbines. This paper focuses on axial‐induction‐based wind plant control techniques, in which the generator torque or blade pitch degrees of freedom of the wind turbines are adjusted. The paper addresses discrepancies between a high‐order wind plant model and an engineering wind plant model. Changes in the engineering model are proposed to better capture the effects of axial‐induction‐based control shown in the high‐order model. Copyright © 2015 John Wiley & Sons, Ltd.

Annoni, Jennifer↗
DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learning methods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with unform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10Gbps connections with 0-366ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss rates but become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Generalization Bounds↗
DOE OSTI2017

Use of Biosurfactants in Oil Recovery

Biosurfactant-mediated oil recovery has the potential to recover large amounts of crude oil that remain entrapped in oil reservoirs after current oil recovery technologies reach their economic limit. Lipopeptides (surfactins and lichenysins), rhamnolipids, and other glycolipids generate the low interfacial tensions and the appropriate rock wettabilities needed to mobilize entrapped oil. Biosurfactants are active over a wide range of temperatures, pH values, and salinities found in many oil reservoirs and are effective at low concentrations. A number of laboratory experiments show that biosurfactant-mediated oil recovery is effective in recovering large amounts of entrapped oil. Several field trials show that in situ biosurfactant production is possible and recovers additional oil. Biosurfactant-mediated oil recovery has been difficult to scale-up to a reservoir-wide technology due to the lack of understanding of how best to stimulate biosurfactant production in the reservoir. In addition, the relationship between biosurfactant concentration and oil recovery is still unclear. Ex-situ biosurfactant-mediated oil recovery where the biosurfactant is added to the injection fluids has not been implemented on a large scale, most likely due to the high production costs of biosurfactants. Multidisciplinary approaches are needed to move biosurfactant-mediated oil recovery from the laboratory to the reservoir.

02 PETROLEUM↗