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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An In-Depth Analysis of the Transformation of Tin Foil Anodes during Electrochemical Cycling in Lithium-Ion Batteries

Tin foils have an impressive lithium-storage capacity more than triple that of graphite anodes, and their adoption could facilitate a drastic improvement in battery energy density. However, implementation of a dense foil electrode architecture represents a significant departure from the standard blade-cast geometry with a distinct electrochemical environment, and this has led to confusion with regards to the first cycle efficiency of the system. In this work, we investigate the unique behavior of a tin active material in a foil architecture to understand its performance as an anode. We find shallow cycling of the foil results in an irreversible formation (< 40%) due to diffusional trapping, but intermediate and complete utilization allows for a remarkably reversible formation reaction (> 90%). This striking nonlinearity stems from an in situ transformation from bulk metal to porous electrode that occurs during formation cycles and defines electrode-level lithium-transport on subsequent cycles. As a result, an alternative cycling procedure for assessing the stability of foils is proposed to account for this chemomechanical effect.

25 ENERGY STORAGE↗
DOE OSTI2022

Across-Depth Heterogeneity and Irreversibility of Fast-Charge-Driven Lithium Plating

Enabling fast charging in lithium-ion batteries (LIBs) is a key factor for resolving consumers’ “range anxiety” concerns in choosing an electric vehicle over a gasoline-powered one. The best-known issue in the fast charging of current LIBs (based on LiNi x Mn y Co 1–x–y O 2 /graphite) is lithium plating, which is barely reversible and is accompanied by capacity loss over time. Therefore, understanding the reasons for the irreversibility of lithium plating driven by fast charging is critical to enhancing the fast-charging capability of LIBs. Here, a study of the irreversibility and heterogeneity of lithium plating is carried out by using electrochemical analyses, inductively coupled plasma mass spectroscopy, and X-ray photoelectron spectroscopy. Further, the study shows that the majority of the lithium plated during fast charging remains inactive even with very slow discharging rates, implying that most of the plated lithium is irreversibly lost. The study also reveals that chemical compounds such as LiF, Li 2 O and Li 2 (CO 3 ) are formed heterogeneously within the lithium plating and are responsible for some of the irreversibility of the plated lithium.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Depth-First Atmospheric River lifecycle Tracking (DART) v1

This algorithm will identify the genesis and track the lifecycle of atmospheric rivers. It can be applied in different global atmospheric river detection algorithms. It is one of the earliest atmospheric river lifecycle tracking algorithms.

Zhou, Yang↗
DOE OSTI2020

Depth-resolved soil data from DOE-LM Riverton Wyoming site, April-September 2017

Averaged (from 3 to 5 replicates) and QA/QC:d data for soil cores taken roughly every month in the period April 5 to September 13 in 2017 at a location close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site. The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Cores were separated into 5-20 cm segments based on soil horizonation and each segment was subsampled for microbial analyses (data available at the NCBI Single Read Archive (SRA) Database, https://www.ncbi.nlm.nih.gov/sra/, BioProject ID# PRJNA626616) in addition to the soil analyses included in this dataset. The soil analyses dataset includes aerobic and anaerobic respiration rate estimates (MicroResp method), water content estimates (on collected samples, not in situ), total C, N, S, Ca, K, Mg, Na, Fe, As, Mo, U, and organic-C concentrations, water extractable concentrations of the same elements, and HCl-extractable Fe(II) concentrations.There are four files included in this data package: metadataFile.csv, avgDataFile.csv, methodFile.csv, and RVT2017soilData.xlsx. The excel file contains the same information as the individual csv-files (in separate tabs).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Design, Optimization, and In-Depth Understanding of Front and Rear Junction Screen-Printed Double-Side Passivated Contacts Solar Cells

Investigate the efficiency potential of n-type screen-printed poly-Si based double-side tunnel oxide passivated contacts (DS-TOPCon) silicon solar cells Establish key material/device parameters and technologies to attain practically achievable DS-TOPCon cell efficiency by Quokka 2D Develop fundamental understanding of underlying mechanisms governing cell operation in front junction (FJ) and rear junction (RJ) cell designs to explain why RJ is a better choice for DS-TOPCon structure

14 SOLAR ENERGY↗
DOE OSTI2021

Uranium Holdup Monitoring with Compton Imaging as Function of Depth and Mass

Material Control and Accountability (MC&A) programs track masses of materials flowing through production processes, where some material remains in process equipment as holdup. Quantification of these masses using gamma emissions typically involves usage of a well characterized radiation detector and assumptions of geometric configuration to constrain detection efficiencies, where the Generalized Geometry Holdup (GGH) method is often used. Uncertainties on the order of ±50% are observed, where the difficulties arise based on the asymmetric and gradient distributions of material that do not fall within the bounds of GGH. Gamma imagers provide a possible means to improve this geometric knowledge. This work describes the process used in creating a series of mass standards to aid the development of imaging algorithms for quantification.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Deep Learning At Depth: Estimating subsurface parameters from geophysical monitoring data

Geophysical imaging techniques are a non-invasive way to image the subsurface and understand both subsurface solid (rock/soil) and fluid property distributions and their evolution in time. Inversions of the geophysical data, such as Electrical Resistance Tomography (ERT) data, are solved to estimate the subsurface property distributions, such as conductivity, and many inversion techniques smooth out sharp gradients in rock or fluid property distributions. Sharp gradients in subsurface properties tend to be present in situations with complex subsurface structures, which are common in many subsurface applications. We have successfully demonstrated that it is possible to inform, or constrain, inversions with neural networks trained on synthetic data with complex subsurface structures. Initial results suggest this process may be optimizable to yield property distributions that better represent the true property distributions than the same inversion process without the neural network constraint. Future work would optimize the neural network performance for this application and then apply the synthetic-data trained neural network to real data to understand the utility and performance of this technique for real data sets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The EGS Collab Project – Summaries of Experiments 2 and 3: Experiments at 1.25 km depth at the Sanford Underground Research Facility

The EGS Collab project performed well-monitored rock stimulation and flow tests at the 10-m scale in an underground research laboratory to inform challenges in implementing enhanced geothermal system (EGS) technology. This project, supported by the US Department of Energy, gathered data and observations from the field tests and compared these to simulation results to understand processes and to build confidence in numerical modeling of the processes.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

FRAM In-Depth [Slides]

FRAM is an isotopic analysis code nominally designed for plutonium and uranium. It can also analyze other materials such as spent fuel (off all ages), medical isotopes.

07 ISOTOPE AND RADIATION SOURCES↗