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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Comparative Study of Zn(O,S) Buffer Layers and CIGS Solar Cells Fabricated by CBD, ALD, and Sputtering: Preprint

Zn(O,S) thin films were deposited by chemical bath deposition (CBD), atomic layer deposition, and sputtering. Composition of the films and band gap were measured and found to follow the trends described in the literature. CBD Zn(O,S) parameters were optimized and resulted in an 18.5% efficiency cell that did not require post annealing, light soaking, or an undoped ZnO layer. Promising resultswere obtained with sputtering. A 13% efficiency cell was obtained for a Zn(O,S) emitter layer deposited with 0.5%O2. With further optimization of process parameters and an analysis of the loss mechanisms, it should be possible to increase the efficiency.

14 SOLAR ENERGY↗
DOE OSTI2017

A Database for Comparative Electrochemical Performance of Commercial 18650-Format Lithium-Ion Cells

Lithium-ion batteries are a central technology to our daily lives with widespread use in mobile devices and electric vehicles. These batteries are also beginning to be widely used in electric grid infrastructure support applications which have stringent safety and reliability requirements. Typically, electrochemical performance data is not available for modelers to validate their simulations, mechanisms, and algorithms for lithium-ion battery performance and lifetime. In this paper, we report on the electrochemical performance of commercial 18650 cells at a variety of temperatures and discharge currents. We found that LiFePO 4 is temperature tolerant for discharge currents at or below 10 A whereas LiCoO 2 , LiNi x Co y Al 1-x-y O 2 , and LiNi 0.80 Mn 0.15 Co 0.05 O 2 exhibited optimal electrochemical performance when the temperature is maintained at 15°C. LiNi x Co y Al 1-x-y O 2 showed signs of lithium plating at lower temperatures, evidenced by irreversible capacity loss and emergence of a high-voltage differential capacity peak. Furthermore, all cells need to be monitored for self-heating, as environment temperature and high discharge currents may elicit an unintended abuse condition. Overall, this study shows that lithium-ion batteries are highly application-specific and electrochemical behavior must be well understood for safe and reliable operation. Additionally, data collected in this study is available for anyone to download for further analysis and model validation.

25 ENERGY STORAGE↗
DOE OSTI2020

Comparative PV LCOE Calculator (Comparative Photovoltaic Levelized Cost of Energy Calculator) [SWR-20-86]

The calculator calculates levelized cost of energy (LCOE) for photovoltaic (PV) systems based on cost, performance, and reliability inputs for a baseline and a proposed technology. The user can choose inputs and watch the effect on LCOE to determine whether a proposed technology is cost-effective, perform trade-off analysis among different technology options, and do break-even analysis of cost or performance.

Silverman, Timothy↗
NASA NTRS2012

An Analysis Technique/Automated Tool for Comparing and Tracking Analysis Modes of Different Finite Element Models

An analysis technique was developed to compare and track mode shapes for different Finite Element Models. The technique may be applied to a variety of structural dynamics analyses, including model reduction validation (comparing unreduced and reduced models), mode tracking for various parametric analyses (e.g., launch vehicle model dispersion analysis to identify sensitivities to modal gain for Guidance, Navigation, and Control), comparing models of different mesh fidelity (e.g., a coarse model for a preliminary analysis compared to a higher-fidelity model for a detailed analysis) and mode tracking for a structure with properties that change over time (e.g., a launch vehicle from liftoff through end-of-burn, with propellant being expended during the flight). Mode shapes for different models are compared and tracked using several numerical indicators, including traditional Cross-Orthogonality and Modal Assurance Criteria approaches, as well as numerical indicators obtained by comparing modal strain energy and kinetic energy distributions. This analysis technique has been used to reliably identify correlated mode shapes for complex Finite Element Models that would otherwise be difficult to compare using traditional techniques. This improved approach also utilizes an adaptive mode tracking algorithm that allows for automated tracking when working with complex models and/or comparing a large group of models.

Towner, Robert L.↗