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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Additives for high voltage lithium ion batteries

This invention relates to a method for preparing an electrochemical cell comprising the sequential steps of preparing a solution of a lithium salt in an non-aqueous solvent containing an additive compound, and maintaining the solution at a temperature in the range of about 20 to about 30° C. for about 5 to 10 days to form an aged electrolyte; assembling an electrochemical cell from an anode, a cathode, and the aged electrolyte; and electrochemically subjecting the electrochemical cell to formation cycling. The additive compound comprises one or more compounds selected from the group consisting of: (R3SiO)3B, (R3SiO)3XY, (R3SiO)3P, (R′O)3PO, (R3Si)3X′, R3SiOS(O)2R′; (R3Si)OC(═O)R′; wherein each R and R′ independently is a hydrocarbyl group; X is P or B; Y is O or S; X is Ti or Al. Electrochemical cells and batteries also are described.

Peebles, Cameron↗
DOE OSTI2021

Thermal and Mechanical Design of a High-Voltage Power Electronics Package: Preprint

Thermal and mechanical design aspects of a power electronic package with 5-kV GaN devices are presented. Through finite element analyses, the impact of different cooling configurations and device location on the thermal performance and reliability of the package was investigated. It was found that placing the devices closer to the direct-bond-copper substrate as opposed to a centered approach in the proposed double-sided-cooling configuration resulted in improved heat dissipation. This approach also reduced the total number of attachment layers, thereby likely improving the reliability of the package. Furthermore, simulations revealed that the device location had a negligible impact on the thermomechanical behavior of the attachment layers, as they are more prone to the local coefficient of thermal expansion mismatch.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Method and apparatus for using compression to improve performance of low voltage caches

A method of operating a cache in a computing device includes, in response to receiving a memory access request at the cache, determining compressibility of data specified by the request, selecting in the cache a destination portion for storing the data based on the compressibility of the data and a persistent fault history of the destination portion, and storing a compressed copy of the data in a non-faulted subportion of the destination portion, wherein the persistent fault history indicates that the non-faulted subportion excludes any persistent faults.

Kalamatianos, John↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗