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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Exploring the potential of hydrogen in decarbonizing China's light-duty vehicle market

The Chinese government has pledged to achieve overall carbon neutrality by 2060. Currently, the transportation sector contributes to about 10% of total greenhouse gas (GHG) emissions in China. Hence, China has created a well-defined energy vehicle development strategy to reduce GHG emissions from the transportation sector, further expanding into hydrogen vehicle technologies. In this study, the Transportation Energy Analysis Model (TEAM) investigates the potential of hydrogen internal combustion engine vehicles (H2- ICEVs) and fuel cell vehicles (FCEVs) as a reliable pathway towards the government's aspiration of carbon neutrality in the transportation sector. According to TEAM, by adopting FCEVs and H2-ICEVs in the vehicle market, hydrogen demand could reach 25% of the total light-duty transportation energy demand in 2050. Consequently, this will lead to an annual reduction of more than 35 million tons GHG compared to only counting on the electrification pathway in the decarbonization task. Besides, FCEVs would take longer to penetrate the light-duty vehicle market compared to H2-ICEVs, as the current fuel cell technology still requires much improvement to attain a competitive vehicle cost of production.

Life cycle analysis↗
DOE OSTI2015

A generalized method for high throughput in-situ experiment data analysis: An example of battery materials exploration

A generalized method is introduced to extract critical information from series of ranked correlated data. The method is generally applicable to all types of spectra evolving as a function of any arbitrary parameter. This approach is based on correlation functions and statistical scedasticity formalism. Numerous challenges in analyzing high throughput experimental data can be tackled using the herein proposed method. We applied this method to understand the reactivity pathway and formation mechanism of a Li-ion battery cathode material during high temperature synthesis using in-situ highenergy X-ray diffraction. We demonstrate that Pearson's correlation function can easily unravel all major phase transition and, more importantly, the minor structural changes which cannot be revealed by conventionally inspecting the series of diffraction patterns. Furthermore, a two-dimensional (2D) reactivity pattern calculated as the scedasticity along all measured reciprocal space of all successive diffraction pattern pairs unveils clearly the structural evolution path and the active areas of interest during the synthesis. The methods described here can be readily used for on-the-fly data analysis during various in-situ operando experiments in order to quickly evaluate and optimize experimental conditions, as well as for post data analysis and large data mining where considerable amount of data hinders the feasibility of the investigation through point-by-point inspection.

25 ENERGY STORAGE↗
DOE OSTI2015

Exploring the Impact of Nuclear Data Uncertainties in Ultra-high Resolution Gamma Spectroscopy for Isotopic Analysis Using Approximate Bayesian Computation

High purity germanium (HPGe) currently provides the highest readily available resolution gamma detection for a broad range of radiation measurements, but microcalorimetry is a developing option that has considerably higher resolution even than HPGe. Superior microcalorimetry resolution offers the potential to better distinguish closely spaced X-rays and gamma-rays, a common challenge for the low energy spectral region near 100 keV from special nuclear materials, and the higher signal-to-background ratio also confers an advantage in detection limit. As microcalorimetry continues to develop, it is timely to assess the impact of uncertainties in detector and item response functions and in basic nuclear data, such as branching ratios and half-lives, used to interpret spectra in terms of the contributory radioactive isotopes. We illustrate that a new inference option known as approximate Bayesian computation (ABC) is effective and convenient both for isotopic inference and for uncertainty quantification for microcalorimetry. The ABC approach opens a pathway to new and more powerful implementations for practical applications than currently available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Computational Exploration of the Li-Electrode|Electrolyte Interface in the Presence of a Nanometer Thick Solid-Electrolyte Interphase Layer [Computational exploration of the Li-electrode|electrolyte interface complicated by a nanometer thin solid-electrolyte interphase (SEI) layer]

A nanometer thick passivation layer will spontaneously form on Li-metal in battery applications due to electrolyte reduction reactions. This passivation layer in rechargeable batteries must have “selective” transport properties: blocking electrons from attacking the electrolytes, while allowing Li + ion to pass through so the electrochemical reactions can continue. The classical description of the electrochemical reaction, Li + + e → Li 0 , occurring at the Li-metal|electrolyte interface is now complicated by the passivation layer and will reply on the coupling of electronic and ionic degrees of freedom in the layer. We consider the passivation layer, called “solid electrolyte interphase (SEI)”, as “the most important but the least understood in rechargeable Li-ion batteries,” partly due to the lack of understanding of its structure–property relationship. In predictive modeling, starting from the ab initio level, we find that it is an important tool to understand the nanoscale processes and materials properties governing the interfacial charge transfer reaction at the Li-metal|SEI|electrolyte interface. Here, we demonstrate pristine Li-metal surfaces indeed dissolve in organic carbonate electrolytes without the SEI layer. Based on joint modeling and experimental results, we point out that the well-known two-layer structure of SEI also exhibits two different Li + ion transport mechanisms. The SEI has a porous (organic) outer layer permeable to both Li + and anions (dissolved in electrolyte), and a dense (inorganic) inner layer facilitate only Li + transport. This two-layer/two-mechanism diffusion model suggests only the dense inorganic layer is effective at protecting Li-metal in electrolytes. This model suggests a strategy to deconvolute the structure–property relationships of the SEI by analyzing an idealized SEI composed of major components, such as Li 2 CO 3 , LiF, Li 2 O, and their mixtures. After sorting out the Li+ ion diffusion carriers and their diffusion pathways, we design methods to accelerate the Li + ion conductivity by doping and by using heterogonous structure designs. We will predict the electron tunneling barriers and connect them with measurable first cycle irreversible capacity loss. We note that the SEI not only affects Li + and e – transport, but it can also impose a potential drop near the Li-metal|SEI interface. Our challenge is to fully describe the electrochemical reactions at the Li - metal|SEI|electrolyte interface. This will be the subject of ongoing efforts.

30 DIRECT ENERGY CONVERSION↗