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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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An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Rapid electrochemical diagnosis of battery health and failure is critical for ensuring reliable battery performance and battery safety. Traditional battery health diagnostics such as capacity measurements and DC pulse tests are reliable and well-understood, however, these measurements of battery capacity and resistance do not capture all aspects of battery degradation. Other aspects of degradation, such as electrolyte decomposition, lithium-plating, and particle cracking are difficult to detect electrochemically but are crucial to measure to get a full picture of battery safety and flag out potential failures. In this work, lab- and field-aged commercial lithium-ion batteries and modules of various chemistries and formats are tested using a variety of traditional electrochemical characterization methods as well as using 2-minute pseudo-random DC pulse sequences at rest and during charge/discharge. The electrochemical measurements are compared to physical cell measurements, cell efficiency, drive cycle performance, physical and thermal heterogeneity, and qualitative safety metrics using statistical and machine-learning methods to discover if a comprehensive "battery health map" can be accurately identified using only rapid DC measurements.
With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell to cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in recent 5 years there are a surge of small sample preparation methods developed for robust effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: specific device- and standard PCR tube- or multi-well plate-based methods. Herein we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of a MS-compatible surfactant, DDM (n-Dodecyl-ß-D-maltoside), and standard low-bind PCR tube or multi-well plate for ‘all-in-one’ one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in the biological and biomedical research.
The production of research isotopes at the Radiochemical Engineering Development Center (REDC) invariably leads to the accumulation of radioactive waste. Storage of this waste onsite at ORNL serves as an interim solution prior to shipment to long term storage facilities, however onsite capacity is limited. Proper characterization of the activity of waste products is essential for determining the appropriate waste stream and, ultimately, mitigating the cost of disposal. This is typically done via gamma spectrometry and use of the In-Situ Object Counting System (ISOCS), a software package from Mirion that serves as an accepted community standard. However, variability in the contents, density, and activity distribution in waste containers can introduce large errors in ISOCS quantification. A measurement campaign using a mockup of the proposed setup in Cell G seeks to quantify the magnitude and source of these systematic errors. Analysis of this data will guide the creation of ISOCS geometry templates and measurement methods designed to minimize overall uncertainty in reported activities.
Experimental measurements or computational model predictions of the post-translational regulation of enzymes needed in a metabolic pathway is a difficult problem. Consequently, regulation is mostly known only for well-studied reactions of central metabolism in various model organisms. In this study, we use two approaches to predict enzyme regulation policies and investigate the hypothesis that regulation is driven by the need to maintain the solvent capacity in the cell. The first predictive method uses a statistical thermodynamics and metabolic control theory framework while the second method is performed using a hybrid optimization–reinforcement learning approach. Efficient regulation schemes were learned from experimental data that either agree with theoretical calculations or result in a higher cell fitness using maximum useful work as a metric. As previously hypothesized, regulation is herein shown to control the concentrations of both immediate and downstream product concentrations at physiological levels. Model predictions provide the following two novel general principles: (1) the regulation itself causes the reactions to be much further from equilibrium instead of the common assumption that highly non-equilibrium reactions are the targets for regulation; and (2) the minimal regulation needed to maintain metabolite levels at physiological concentrations maximizes the free energy dissipation rate instead of preserving a specific energy charge. The resulting energy dissipation rate is an emergent property of regulation which may be represented by a high value of the adenylate energy charge. In addition, the predictions demonstrate that the amount of regulation needed can be minimized if it is applied at the beginning or branch point of a pathway, in agreement with common notions. The approach is demonstrated for three pathways in the central metabolism of E. coli (gluconeogenesis, glycolysis-tricarboxylic acid (TCA) and pentose phosphate-TCA) that each require different regulation schemes. It is shown quantitatively that hexokinase, glucose 6-phosphate dehydrogenase and glyceraldehyde phosphate dehydrogenase, all branch points of pathways, play the largest roles in regulating central metabolism.
CdTe solar cells suffer from a non-ideal back contact which can strongly affect the equivalent circuit model and complicate capacitance measurements. Here, five different back contact materials are deposited on identical CdTe absorbers and their influence on capacitance measurements is characterized. A five-element equivalent circuit model is shown to represent a CdTe solar cell with a non-ideal back contact, and capacitance-frequency (C-f) measurements on each sample clearly show the influence of this contact. Capacitance-voltage (C-V) measurements on each sample show the influence of frequency on measured capacitance. In the AlGaOx/Au sample, temperature dependent C-fs show the back barrier height to be 240 meV, and ongoing measurements will give a comparison of back barrier heights for all samples. This study provides insight into the efficacy of various back contacts and highlights potential errors in the interpretation of capacitance measurements due to the presence of the back contact.
Today's highest-efficiency silicon solar cells typically operate near the threshold between low-level and high-level injection. It is not well understood if pushing further into a regime in which the cell operating point is solidly in high-level injection at all times of the day has further benefits for the solar cell performance. From a reliability perspective, cells fabricated on lower doped silicon have a larger breakdown voltage. This advantage can affect the design of modules allowing higher voltages and a relaxation of the number of bypass diodes needed. In this project, we present a comprehensive assessment, both experimental and using simulation, of how bulk resistivity, light intensity, and operation temperature impact the performance of the silicon solar cell. This work incorporates a comprehensive device physics analysis assisted by numerical simulation. The source code is now available under General Public License (GPL3), and to further leverage the findings of this project and outreach people outside of the scientific community, we are working with www.pveducation.org (which receives >1 million visitors a year) to create interactive content using our simulation results. The simulation results indicate that high bulk resistivity wafers (>>10 Ωcm) require bulk Shockley-Read-Hall (SRH) lifetimes in the millisecond range to outperform wafers with standard bulk resistivities (<10 Ωcm). Additionally, above bulk resistivities of 10 Ωcm (the exact value depends on the bulk characteristics of the wafer), the cell efficiency is weakly dependent on the bulk resistivity. As a result, ingot manufactures may have an opportunity to further reduce wafer cost by growing higher resistivity ingots that are more tolerant to resistivity variations. This project is particularly relevant today, as solar cell architectures with improved surface passivation and milliseconds lifetimes wafers are commercially available, leveraging potential benefits of using higher bulk resistivities. Outside of interdigitated back contact (IBC) cell, reported studies on high resistivity silicon (>100 Ωcm) are very limited. To the best of our knowledge, this project provides for the first-time experimental insight on solar cells fabricated on wafers with bulk resistivities up to several thousand Ωcm, delivering a comprehensive vision of their performance under real-world temperature and light intensity operation conditions. We manufactured and characterized solar cells with bulk resistivities in the range of 1 Ωcm to >15k Ωcm. Under standard testing conditions (STC), we measured solar cells efficiencies over 20% over the entire range of bulk resistivities, using our baseline cell processing. To evaluate the cell performance in real-world operation conditions, the solar cells were measured at different temperatures (25-80°C) and at different light intensities (0.1-1 suns). The measurements show that the bulk resistivity does not impact the solar cell response to temperature and light intensity. Similar thermal coefficients (TC) were measured for standard and high bulk resistivities, and they are comparable with the TC values reported in the literature for standard bulk resistivities <10 Ωcm. After light soaking, the solar cell didn’t show signs of light-induced degradation (LID). This result was expected since n-type float zone (FZ) wafers were used in this work, i.e. low traces of boron and low concentration of oxygen (oxygen is typically found in the seed end of Czochralski (CZ) ingots). We measured for high bulk resistivities (>10 Ωcm) extremely high breakdown voltages (>1000V). In conclusion, the insight provided by this project can positively impact the levelized cost of energy (LCOE) of the photovoltaic systems through its effect on cell and ingot manufacturing yield, silicon cell power output, and module reliability.
Angiopoietin like 4 (ANGPTL4) has been proved to play an important role in lipid and glucose metabolism disorders and related cardiovascular diseases, but its role in the formation of cirrhosis still needs to be further explored. Therefore, the aim of this study was to investigate the role of ANGPTL4 in the development of liver cirrhosis and its mechanism, as well as its effect on Kupffer cell polarization and hepatic stellate cell activation. The ELISA and RT-qPCR assay were used to detect the content of ANGPTL4 in serum and mRNA expression in cells and tissues respectively. The expression of ANGPTL4, Arg1 and Mrc2 in Kupffer cells was measured by Western blot. The percentage of CD163{sup +} and CD206{sup +} cells was measured by flow cytometry. Mice cirrhosis model was established, and the expression of ANGPTL4 was interfered by injecting sh-ANGPTL4 lentiviral vector into caudal vein. The results revealed that ANGPTL4 was significantly up-regulated in liver cirrhosis patients and HBV induced liver injury cell models. Further studies found that interference with ANGPTL4 regulated CD163 and inhibited the polarization and proinflammatory effects of KCsas well as inhibited the activation of hepatic stellate cells (HSCs) and fibrosis. More importantly, Interference with ANGPTL4 inhibits the progression of liver cirrhosis in mice. What's more, TLR4/NF-κB pathway was involved in the molecular mechanism of ANGPTL4 on Kupffer cells and hepatic stellate cells. It is suggested that the mechanism of sh-ANGPTL4 suppressing the polarization of KCs and the activation of hepatic stellate cells (HSCs) is to regulate the TLR4/NF-κB signaling pathways.