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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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Assessing the Binding of Plastics Additives at Brønsted Acid Sites of Zeolites
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Electrochemical Conversion of CO 2 to Methyl Formate in a Flow Electrolyzer with Mixed Propylene Carbonate/Methanol Catholyte
Despite the promise of electrochemical carbon dioxide reduction as a technology for the production of clean fuels and decarbonization of the chemical industry, research has mostly focused on aqueous systems with a relatively limited set of products that have been achieved via electrosynthesis. Increasingly, CO 2 electroreduction in nonaqueous solvents is being pursued to develop new avenues for expanding the suite of products that can be made with high selectivity. CO 2 reduction in alcohols coupled with in situ esterification to produce esters is one such route that utilizes nonaqueous electrolyte. To be practical, such electrochemical syntheses need to be translated to a high-performance reactor such as a flow electrolyzer. However, many organic solvents, such as alcohols, wet and flood porous electrodes, thus impeding reactor performance. In this work, methanol was mixed with propylene carbonate as a catholyte for a gas-fed CO 2 flow electrolyzer that avoided cathode flooding. Simultaneously, a dual aqueous anolyte was used for water oxidation as a scalable and sustainable anodic half-reaction. The performance effect of methanol concentration, catholyte acidity, CO 2 flow rate, and dilute water in the catholyte were investigated. With 10 vol % methanol in 90 vol % propylene carbonate, 63% faradaic efficiency for methyl formate ester product was sustained without cathode flooding. However, improvements are still needed to lower the cell resistance and further increase the operating current density.
The Future is Garbage: Repurposing of Food Waste to an Integrated Biorefinery
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4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique
The temporally and spatially resolved tracking of lithium intercalation and electrode degradation processes are crucial for detecting and understanding performance losses during the operation of lithium-batteries. Here, high-throughput X-ray computed tomography has enabled the identification of mechanical degradation processes in a commercial Li/MnO 2 primary battery and the indirect tracking of lithium diffusion; furthermore, complementary neutron computed tomography has identified the direct lithium diffusion process and the electrode wetting by the electrolyte. Virtual electrode unrolling techniques provide a deeper view inside the electrode layers and are used to detect minor fluctuations which are difficult to observe using conventional three dimensional rendering tools. Moreover, the 'unrolling' provides a platform for correlating multi-modal image data which is expected to find wider application in battery science and engineering to study diverse effects e.g. electrode degradation or lithium diffusion blocking during battery cycling.
Observation of reduced thermal conductivity in a metal-organic framework due to the presence of adsorbates
Whether the presence of adsorbates increases or decreases thermal conductivity in metalorganic frameworks (MOFs) has been an open question. Here we report observations of thermal transport in the metal-organic framework HKUST-1 in the presence of various liquid adsorbates: water, methanol, and ethanol. Experimental thermo-reflectance measurements were performed on single crystals and thin films, and theoretical predictions were made using molecular dynamics simulations. We find that the thermal conductivity of HKUST-1 decreases by 40 – 80% depending on the adsorbate, a result that cannot be explained by effective medium approximations. Our findings demonstrate that adsorbates introduce additional phonon scattering in HKUST-1, which particularly shortens the lifetimes of low frequency phonon modes. As a result, the system thermal conductivity is lowered to a greater extent than the increase expected by the creation of additional heat transfer channels. Finally, we show that thermal diffusivity is even more greatly reduced than thermal conductivity by adsorption.
Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties
Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.