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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
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

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↗
DOE OSTI2021

Electrolyte for high voltage lithium-ion batteries

An electrolyte, electrochemical device, battery, capacitor, and/or the like include a salt; and a fluorinated organosulfate compound represented by Formula I: wherein, R1 is H, OR3, alkyl, alkenyl, alkynyl, aralkyl, or silyl; R2 is H, OR3, alkyl, alkenyl, alkynyl, aralkyl, or silyl; and R3 is H, alkyl, alkenyl, alkynyl, aryl, heterocyclyl, heteroaryl, or siloxy; or where R1 and R2 join together to form a cyclic compound incorporating the —O—S(O)2—O— group; wherein at least one R1 and R2 is fluorinated.

Amine, Khalil↗
DOE OSTI2021

Polyfluorinated carbonate electrolyte for high-voltage lithium batteries

A non-aqueous solvent composition for a lithium battery comprises a fluorinated solvent mixture that consists essentially of a 1,2-difluoroethylene carbonate and a fluoro-substituted dialkyl carbonate in a respective weight ratio of about 1:3 to about 1:1, and optionally up to about 30 wt % of an additional organic solvent. An electrolyte for a lithium ion battery comprises a lithium salt dissolved in a non-aqueous solvent composition comprising the fluorinated solvent mixture.

Zhang, Zhengcheng↗
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↗
DOE OSTI2022

Power supply circuit with multiple stages for converting high voltage to low voltage and power train having the same

A power supply circuit for converting a first voltage to a second voltage where the first voltage is greater than the second voltage, and a power train having the same, are provided. The power supply circuit may have multiple stages and each stage of the power supply circuit may include a first circuit block configured to provide a start-up power to a second circuit block; a second circuit block configured to generate a Pulse-Width-Modulation (PWM) signal that controls a pulse duration of a transistor; a third circuit block configured to activate or deactivate the transistor based on the PWM signal; a fourth circuit block configured to reset a magnetic flux in a transformer to a zero state when the transistor is deactivated; and a fifth circuit block configured to maintain an output of a stage below a predetermined value by adjusting a voltage across the transformer.

Singh, Brij N.↗
DOE OSTI2023

Partial discharge suppression in high voltage solid-state devices

Devices, methods and techniques are disclosed to suppress electrical discharge and breakdown in insulating or encapsulation material(s) applied to solid-state devices. In one example aspect, a multi-layer encapsulation film includes a first layer of a first dielectric material and a second layer of a second dielectric material. An interface between the first layer and the second layer is configured to include molecular bonds to prevent charge carriers from crossing between the first layer and the second layer. The multi-layer encapsulation configuration is structured to allow an electrical contact and a substrate of the solid-state device to be at least partially surrounded by the multi-layer encapsulation configuration.

Sampayan, Stephen↗