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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Ni5Ga3 Catalysts for CO2 Reduction to Methanol: Exploring the Role of Ga Surface Oxidation/reductions on Catalytic Activity

Ad-Ni5Ga3/SiO2 catalyst, which is highly active and stable for thermal CO2 hydrogenation to methanol, was investigated to understand its surface dynamics during reaction conditions. The catalyst was prepared, tested and characterized using a multitude of techniques, including ex-situ XRD, TEM, H2-TPR, CO chemisorption and in-situ ETEM and APXPS. The formation of Ga2O3 upon air exposure was observed and the consequences on catalytic activity were investigated. Results revealed that upon air exposure Ga migrates from the subsurface region to the surface of the nanoparticles forming a Ga-oxide shell surrounding a metallic core. The oxide shell can be reduced completely at high temperatures and the temperature of the reduction activation treatment plays a crucial role on the catalytic activity. This air exposure-reduction procedure results in a redistribution of the Ga species in the surface/subsurface region, promoted by a higher Ga affinity for oxygen. XRD analysis of the post-reaction samples provide evidence for the partial transformation of a Ni5Ga3 intermetallic phase into a Ni-rich Ni3Ga phase. APXPS data indicate that the Ni-rich phase forms in the subsurface region. A Ga-rich phase exists on the surface, where the Ni/Ga ratio reaches 2/3 upon activation in hydrogen. At low reduction temperatures an amorphous Ga2O3 shell remains, indicating a promotion effect on methanol synthesis activity.

Ni-Ga, intermetallic, methanol synthesis, in-situ ↗
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↗